Tag Archives: Application Security

15 years of helping build a better Internet: a look back at Birthday Week 2025

Post Syndicated from Nikita Cano original https://blog.cloudflare.com/birthday-week-2025-wrap-up/

Cloudflare launched fifteen years ago with a mission to help build a better Internet. Over that time the Internet has changed and so has what it needs from teams like ours.  In this year’s Founder’s Letter, Matthew and Michelle discussed the role we have played in the evolution of the Internet, from helping encryption grow from 10% to 95% of Internet traffic to more recent challenges like how people consume content. 

We spend Birthday Week every year releasing the products and capabilities we believe the Internet needs at this moment and around the corner. Previous Birthday Weeks saw the launch of IPv6 gateway in 2011,  Universal SSL in 2014, Cloudflare Workers and unmetered DDoS protection in 2017, Cloudflare Radar in 2020, R2 Object Storage with zero egress fees in 2021,  post-quantum upgrades for Cloudflare Tunnel in 2022, Workers AI and Encrypted Client Hello in 2023. And those are just a sample of the launches.

This year’s themes focused on helping prepare the Internet for a new model of monetization that encourages great content to be published, fostering more opportunities to build community both inside and outside of Cloudflare, and evergreen missions like making more features available to everyone and constantly improving the speed and security of what we offer.

We shipped a lot of new things this year. In case you missed the dozens of blog posts, here is a breakdown of everything we announced during Birthday Week 2025. 

Monday, September 22

What

In a sentence …

Help build the future: announcing Cloudflare’s goal to hire 1,111 interns in 2026

To invest in the next generation of builders, we announced our most ambitious intern program yet with a goal to hire 1,111 interns in 2026.

Supporting the future of the open web: Cloudflare is sponsoring Ladybird and Omarchy

To support a diverse and open Internet, we are now sponsoring Ladybird (an independent browser) and Omarchy (an open-source Linux distribution and developer environment).

Come build with us: Cloudflare’s new hubs for startups

We are opening our office doors in four major cities (San Francisco, Austin, London, and Lisbon) as free hubs for startups to collaborate and connect with the builder community.

Free access to Cloudflare developer services for non-profit and civil society organizations

We extended our Cloudflare for Startups program to non-profits and public-interest organizations, offering free credits for our developer tools.

Introducing free access to Cloudflare developer features for students

We are removing cost as a barrier for the next generation by giving students with .edu emails 12 months of free access to our paid developer platform features.

Cap’n Web: a new RPC system for browsers and web servers

We open-sourced Cap’n Web, a new JavaScript-native RPC protocol that simplifies powerful, schema-free communication for web applications.

A lookback at Workers Launchpad and a warm welcome to Cohort #6

We announced Cohort #6 of the Workers Launchpad, our accelerator program for startups building on Cloudflare.

Tuesday, September 23

What

In a sentence …

Building unique, per-customer defenses against advanced bot threats in the AI era

New anomaly detection system that uses machine learning trained on each zone to build defenses against AI-driven bot attacks. 

Why Cloudflare, Netlify, and Webflow are collaborating to support Open Source tools

To support the open web, we joined forces with Webflow to sponsor Astro, and with Netlify to sponsor TanStack.

Launching the x402 Foundation with Coinbase, and support for x402 transactions

We are partnering with Coinbase to create the x402 Foundation, encouraging the adoption of the x402 protocol to allow clients and services to exchange value on the web using a common language

Helping protect journalists and local news from AI crawlers with Project Galileo

We are extending our free Bot Management and AI Crawl Control services to journalists and news organizations through Project Galileo.

Cloudflare Confidence Scorecards – making AI safer for the Internet

Automated evaluation of AI and SaaS tools, helping organizations to embrace AI without compromising security.

Wednesday, September 24

What

In a sentence …

Automatically Secure: how we upgraded 6,000,000 domains by default

Our Automatic SSL/TLS system has upgraded over 6 million domains to more secure encryption modes by default and will soon automatically enable post-quantum connections.

Giving users choice with Cloudflare’s new Content Signals Policy

The Content Signals Policy is a new standard for robots.txt that lets creators express clear preferences for how AI can use their content.

To build a better Internet in the age of AI, we need responsible AI bot principles

A proposed set of responsible AI bot principles to start a conversation around transparency and respect for content creators’ preferences.

Securing data in SaaS to SaaS applications

New security tools to give companies visibility and control over data flowing between SaaS applications.

Securing today for the quantum future: WARP client now supports post-quantum cryptography (PQC)

Cloudflare’s WARP client now supports post-quantum cryptography, providing quantum-resistant encryption for traffic. 

A simpler path to a safer Internet: an update to our CSAM scanning tool

We made our CSAM Scanning Tool easier to adopt by removing the need to create and provide unique credentials, helping more site owners protect their platforms.

Thursday, September 25

What

In a sentence …

Every Cloudflare feature, available to everyone

We are making every Cloudflare feature, starting with Single Sign On (SSO), available for anyone to purchase on any plan. 

Cloudflare’s developer platform keeps getting better, faster, and more powerful

Updates across Workers and beyond for a more powerful developer platform – such as support for larger and more concurrent Container images, support for external models from OpenAI and Anthropic in AI Search (previously AutoRAG), and more. 

Partnering to make full-stack fast: deploy PlanetScale databases directly from Workers

You can now connect Cloudflare Workers to PlanetScale databases directly, with connections automatically optimized by Hyperdrive.

Announcing the Cloudflare Data Platform

A complete solution for ingesting, storing, and querying analytical data tables using open standards like Apache Iceberg. 

R2 SQL: a deep dive into our new distributed query engine

A technical deep dive on R2 SQL, a serverless query engine for petabyte-scale datasets in R2.

Safe in the sandbox: security hardening for Cloudflare Workers

A deep-dive into how we’ve hardened the Workers runtime with new defense-in-depth security measures, including V8 sandboxes and hardware-assisted memory protection keys.

Choice: the path to AI sovereignty

To champion AI sovereignty, we’ve added locally-developed open-source models from India, Japan, and Southeast Asia to our Workers AI platform.

Announcing Cloudflare Email Service’s private beta

We announced the Cloudflare Email Service private beta, allowing developers to reliably send and receive transactional emails directly from Cloudflare Workers.

A year of improving Node.js compatibility in Cloudflare Workers

There are hundreds of new Node.js APIs now available that make it easier to run existing Node.js code on our platform. 

Friday, September 26

What

In a sentence …

Cloudflare just got faster and more secure, powered by Rust

We have re-engineered our core proxy with a new modular, Rust-based architecture, cutting median response time by 10ms for millions. 

Introducing Observatory and Smart Shield

New monitoring tools in the Cloudflare dashboard that provide actionable recommendations and one-click fixes for performance issues.

Monitoring AS-SETs and why they matter

Cloudflare Radar now includes Internet Routing Registry (IRR) data, allowing network operators to monitor AS-SETs to help prevent route leaks.

An AI Index for all our customers

We announced the private beta of AI Index, a new service that creates an AI-optimized search index for your domain that you control and can monetize.

Introducing new regional Internet traffic and Certificate Transparency insights on Cloudflare Radar

Sub-national traffic insights and Certificate Transparency dashboards for TLS monitoring.

Eliminating Cold Starts 2: shard and conquer

We have reduced Workers cold starts by 10x by implementing a new “worker sharding” system that routes requests to already-loaded Workers.

Network performance update: Birthday Week 2025

The TCP Connection Time (Trimean) graph shows that we are the fastest TCP connection time in 40% of measured ISPs – and the fastest across the top networks.

How Cloudflare uses performance data to make the world’s fastest global network even faster

We are using our network’s vast performance data to tune congestion control algorithms, improving speeds by an average of 10% for QUIC traffic.

Come build with us!

Helping build a better Internet has always been about more than just technology. Like the announcements about interns or working together in our offices, the community of people behind helping build a better Internet matters to its future. This week, we rolled out our most ambitious set of initiatives ever to support the builders, founders, and students who are creating the future.

For founders and startups, we are thrilled to welcome Cohort #6 to the Workers Launchpad, our accelerator program that gives early-stage companies the resources they need to scale. But we’re not stopping there. We’re opening our doors, literally, by launching new physical hubs for startups in our San Francisco, Austin, London, and Lisbon offices. These spaces will provide access to mentorship, resources, and a community of fellow builders.

We’re also investing in the next generation of talent. We announced free access to the Cloudflare developer platform for all students, giving them the tools to learn and experiment without limits. To provide a path from the classroom to the industry, we also announced our goal to hire 1,111 interns in 2026 — our biggest commitment yet to fostering future tech leaders.

And because a better Internet is for everyone, we’re extending our support to non-profits and public-interest organizations, offering them free access to our production-grade developer tools, so they can focus on their missions.

Whether you’re a founder with a big idea, a student just getting started, or a team working for a cause you believe in, we want to help you succeed.

Until next year

Thank you to our customers, our community, and the millions of developers who trust us to help them build, secure, and accelerate the Internet. Your curiosity and feedback drive our innovation.

It’s been an incredible 15 years. And as always, we’re just getting started!

Securing data in SaaS to SaaS applications

Post Syndicated from Michael Tremante original https://blog.cloudflare.com/saas-to-saas-security/

The recent Salesloft breach taught us one thing: connections between SaaS applications are hard to monitor and create blind spots for security teams with disastrous side effects. This will likely not be the last breach of this type.

To fix this, Cloudflare is working towards a set of solutions that consolidates all SaaS connections via a single proxy, for easier monitoring, detection and response. A SaaS to SaaS proxy for everyone.

As we build this, we need feedback from the community, both data owners and SaaS platform providers. If you are interested in gaining early access, please sign up here.

SaaS platform providers, who often offer marketplaces for additional applications, store data on behalf of their customers and ultimately become the trusted guardians. As integrations with marketplace applications take place, that guardianship is put to the test. A key breach in any one of these integrations can lead to widespread data exfiltration and tampering. As more apps are added the attack surface grows larger. Security teams who work for the data owner have no ability, today, to detect and react to any potential breach.

In this post we explain the underlying technology required to make this work and help keep your data on the Internet safe.

SaaS to SaaS integrations

No one disputes the value provided by SaaS applications and their integrations. Major SaaS companies implement flourishing integration ecosystems, often presented as marketplaces. For many, it has become part of their value pitch. Salesforce provides an AppExchange. Zendesk provides a marketplace. ServiceNow provides an Integration Hub. And so forth.

These provide significant value to any organisation and complex workflows. Data analysis or other tasks that are not supported natively by the SaaS vendor are easily carried out via a few clicks.

On the other hand, SaaS applications present security teams with a growing list of unknowns. Who can access this data? What security processes are put in place? And more importantly: how do we detect data leak, compromise, or other malicious intent?

Following the Salesloft breach, which compromised the data of hundreds of companies, including Cloudflare, the answers to these questions are top of mind.

The power of the proxy: seamless observability

There are two approaches Cloudflare is actively prototyping to address the growing security challenges SaaS applications pose, namely visibility into SaaS to SaaS connections, including anomaly detection and key management in the event of a breach. Let’s go over each of these, both relying on proxying SaaS to SaaS traffic.

1) Giving control back to the data owner

Cloudflare runs one of the world’s largest reverse proxy networks. As we terminate L7 traffic, we are able to perform security-related functions including blocking malicious requests, detecting anomalies, detecting automated traffic and so forth. This is one of the main use cases customers approach us for.

Cloudflare can proxy any hostname under the customer’s control.

It is this specific ability, often referred to as “vanity”, “branded” or “custom” hostnames, that allows us to act as a front door to the SaaS vendor on behalf of a customer. Provided a marketplace app integrates via a custom domain, the data owner can choose to use Cloudflare’s new SaaS integration protection capabilities.

For a customer (Acme Corp in this example) to access, say SaaS Application, the URL needs to become saas.acme.com as that is under Acme’s control (and not acme.saas.com).

This setup allows Cloudflare to be placed in front of SaaS Corp as the customer controls the DNS hostname. By proxying traffic, Cloudflare can be the only integration entity with programmatic access to SaaS Corp’s APIs and data and transparently “swap” authorisation tokens with valid ones and issue separate tokens, using key splitting, to any integrations. 


Note that in many cases, authorization and authentication flows fall outside any vanity/branded hostname. It is in fact very common for an OAuth flow to still hit the SaaS provider url oauth.saas.com. It is therefore required, in this setup, for marketplace applications to provide the ability to support vanity/branded URLs for their OAuth and similar flows, oauth.saas.acme.com in the diagram above.

Ultimately Cloudflare provides a full L7 reverse proxy for all traffic inbound/outbound to the given SaaS provider solving for the core requirements that would lessen the impact of a similar breach to the Salesloft example. Had Salesloft integrated via a Cloudflare-proxied domain, then data owners would be able to:

  • Gain visibility into who or what can access data, and where it’s accessed from, in the SaaS platform. Cloudflare already provides analytics and filtering tools to identify traffic sources, including hosting locations, IPs, user agents and other tools.

  • Instantly shut off access to the SaaS provider without the need to rotate credentials on the SaaS platform, as Cloudflare would be able to block access from the proxy.

  • Detects anomalies in data access by observing baselines and traffic patterns. For example a change in data exfiltration traffic flows would trigger an alert.

2) Improve SaaS platform security

The approach listed above assumes the end user is the company whose data is at risk. However, SaaS platforms themselves are now paying a lot of attention to marketplace applications and access patterns. From a deployment perspective, it’s actually easier to provide additional visibility to a SaaS provider as it is a standard reverse proxy deployment and we have tools designed for SaaS applications, such as Cloudflare for SaaS.


This deployment model allows Cloudflare to proxy all traffic to the SaaS vendor, including to all API endpoints therefore gaining visibility into any SaaS to SaaS connections. As part of this, we are building improvements to our API Shield solution to provide SaaS security teams with additional controls:

  • Token / session logging: Ability to keep track of OAuth tokens and provide session logs for audit purposes.

  • Session anomaly detection: Ability to warn when a given OAuth (or other session) shows anomalous behavior.

  • Token / session replacement: Ability to substitute SaaS-generated tokens with Cloudflare-generated tokens to allow for fast rotation and access lock down.

The SaaS vendor may of course expose some of the affordances to their end customer as part of their dashboard.

How key splitting enables secure token management

Both deployment approaches described above rely on our ability to control access without storing complete credentials. While we already store SSL/TLS private keys for millions of web applications, storing complete SaaS bearer tokens would create an additional security burden. To solve this, and enable the token swapping and instant revocation capabilities mentioned above, we use key splitting.

Key splitting cryptographically divides bearer tokens into two mathematically interdependent fragments called Part A and Part B. Part A goes to the fourth-party integration (like Drift or Zapier) while Part B stays in Cloudflare’s edge storage. Part A is just random noise that won’t authenticate to Salesforce or any SaaS platform expecting complete tokens, so neither fragment is usable alone.

This creates an un-bypassable control point. Integrations cannot make API calls without going through Cloudflare’s proxy because they only possess Part A. When an integration needs to access data, it must present Part A to our edge where we retrieve Part B, reconstruct the token in memory for microseconds, forward the authenticated request, and then immediately clear the token. This makes sure that the complete bearer token never exists in any database or log.

This forced cooperation means every API call flows through Cloudflare where we can monitor for anomalies, delete Part B to instantly revoke access (transforming incident response from hours to seconds), and maintain complete audit trails. Even more importantly, this approach minimizes our burden of storing sensitive credentials since a breach of our systems wouldn’t yield usable tokens.

If attackers compromise the integration and steal Part A, or somehow breach Cloudflare’s storage and obtain Part B, neither fragment can authenticate on its own. This fundamentally changes the security model from protecting complete tokens to managing split fragments that are individually worthless. It also gives security teams unprecedented visibility and control over how their data is accessed across third-party integrations.


Regaining control of your data

We are excited to develop solutions mentioned above to give better control and visibility around data stored in SaaS environments, or more generally, outside a customer’s network.

If you are a company worried about this risk, and would like to be notified to take part in our early access, please sign up here.

If you are a SaaS vendor who would like to provide feedback and take part in developing better API security tooling for third party integrations towards your platform, sign up here.

We are looking forward to helping you get better control of your data in SaaS to SaaS environments.

Many voices, one community: Three themes from RSA Conference 2025

Post Syndicated from Anne Grahn original https://aws.amazon.com/blogs/security/many-voices-one-community-three-themes-from-rsa-conference-2025/

RSA Conference (RSAC) 2025 drew 730 speakers, 650 exhibitors, and 44,000 attendees from across the globe to the Moscone Center in San Francisco, California from April 28 through May 1.

The keynote lineup was eclectic, with 37 presentations featuring speakers ranging from NBA Hall of Famer Earvin “Magic” Johnson to public and private-sector luminaries such as former US National Cyber Director Chris Inglis, U.S. Secretary of Homeland Security Kristi Noem, and cryptography experts Tal Rabin, Whitfield Diffie, and Adi Shamir.

Topics aligned with this year’s conference theme, “Many Voices. One Community,” and focused on the security industry’s shared drive to foresee risks, counter threats, and embrace new challenges.

Three themes caught our attention: agentic AI, cryptography, and public-private collaboration.

Agentic AI

The potential of agentic AI to augment human decision-making was a common thread among conversations at the conference. Numerous sessions touched on the topic, and the desire of attendees to understand the technology and learn how to balance its risks and opportunities was clear.

Separating hype from reality

An AI agent is a software program that can interact with its environment (as detailed in Figure 1), collect data, and use the data to perform self-determined tasks to meet predetermined goals.

Figure 1: Generative AI agents

Figure 1: Generative AI agents

Agentic systems offer a fundamentally different approach compared to traditional software, particularly in their ability to handle complex, dynamic, and domain-specific challenges. While traditional systems rely on rule-based automation and structured data, agentic systems use large language models (LLMs)—a subset of generative AI—to operate autonomously. Agents can learn from interactions with users, and make nuanced, context-aware decisions while keeping human analysts in the loop.

Numerous RSAC speakers alluded to AI agents as the next frontier in enterprise transformation. Gartner® predicts that: “By 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024,” and “at least 15% of day-to-day work decisions will be made autonomously through agentic AI, up from zero percent in 2024.”

However, as organizations build AI agents, understanding the concerns that come with them is critical.

“Agentic AI presents tremendous opportunities to deliver business value and innovative security outcomes. Production deployments require a balance between its capabilities, and robust security and trust mechanisms.”
—Hart Rossman, Global Services Security Vice President at AWS

In the RSAC keynote session The Five Most Dangerous New Attack Techniques…and What to Do for Each, Rob Lee, Chief of Research and Head of Faculty at SANS Institute noted that while security teams are embracing AI to amplify productivity, threat actors are doing the same. He pointed to MIT research that shows adversarial agent systems executing attack sequences are 47 times faster than human operators, with a 93 percent success rate in privilege escalation paths.

Safeguarding GenAI & Agentic Apps, Top 10 Risks in 2025, a half-day Open Worldwide Application Security Project (OWASP) event, focused on helping attendees distinguish real threats from hype. OWASP Gen AI Security Project team members and industry experts reviewed the 2025 OWASP Top 10 List for LLM and GenAI (shown in Figure 2), and introduced Agentic AI—Threats and Mitigations—the first in a series of guides from the OWASP Agentic Security Initiative (ASI) to provide a threat-model-based reference of emerging agentic threats and mitigations. Content feedback can be submitted to ASI in advance of the guide’s next release.

Figure 2: 2025 OWASP Top 10 for LLM Applications

Figure 2: 2025 OWASP Top 10 for LLM Applications

Agentic AI wins Cybersecurity Startup Accelerator

The second annual AWS and CrowdStrike Cybersecurity Startup Accelerator, in collaboration with the NVIDIA Inception program, took place during RSAC. A panel of judges—including George Kurtz, Founder and CEO of CrowdStrike, CJ Moses, Chief Information Security Officer at Amazon, and David Reber Jr., Chief Security Officer at NVIDIA—evaluated startups on innovation, market relevance, and go-to-market potential. Terra Security, a provider of agentic AI-powered, continuous web application penetration testing, was selected from a group of 10 finalists who pitched live. Two runners-up, Kenzo Security and Rig Security, were also recognized for their standout approaches to agentic AI-driven security.

Addressing AI risks

The need to consider your security posture when assessing overall AI readiness was emphasized throughout the conference. A defense-in-depth architecture can help mitigate risks with multiple layers of protection across both traditional and AI software components. Innovative solutions such as AI red teaming, AI behavioral sandboxing, and advanced tracing and evaluation of generative AI agents can enhance your security strategy with a proactive approach to securing AI.

Visit the following resources to help design, build, and operate AI systems: DevsecOps Revolution: Unleashing Generative AI for Automated Excellence, AWS generative AI security, responsible AI, and the Amazon AGI Labs Blog.

Cryptography

Encryption was another key topic. The FIDO Alliance hosted a half-day seminar that focused on developments in the global movement to passwordless technology such as passkeys—cryptographic keys designed to replace passwords by combining the power of public key cryptography with biometric authentication.

In Dude, Where’s My Password? The Challenges of Getting to Passwordless, Andy Ozment, Chief Technology Risk Officer and Executive Vice President at Capital One noted that 88 percent of data compromised in basic web application attacks reported in 2024 involved stolen credentials. Ozment pointed out that “going passwordless” through a combination of X.509 device certificates and FIDO2 passkeys presented Capital One with an opportunity to nearly eliminate entire classes of threats (as detailed in Figure 3), while increasing the quality of user experience.

Figure 3: Using passkeys to reduce risk while advancing user experience

Figure 3: Using passkeys to reduce risk while advancing user experience

Along the way, Ozment said, Capital One’s journey to passwordless was enabled by its transition from on-premises technology to going “all-in” on the public cloud. Watch the recording of his session or view the slides to learn more.

Post-quantum encryption

The state of post-quantum encryption was detailed in the popular Cryptographer’s Panel, moderated by Tal Rabin, Senior Principal Applied Scientist at AWS.

Panelist Vinod Vaikuntanathan, Professor at MIT underscored the impact of the quantum-resistant algorithm standardization process (Figure 4) started by the National Institute of Standards and Technology (NIST) in 2016. “We now have two public key encryption algorithms, and three new digital signature algorithms that are standardized,” he pointed out.

Figure 4: Post-quantum encryption algorithms

Figure 4: Post-quantum encryption algorithms

The panelists agreed that even though quantum computers aren’t here yet, the time to deploy these algorithms is now. NIST recommends phasing out existing encryption methods by 2030 in its Transition to Post-Quantum Cryptography Standards report. However, Vaikuntanathan and Adi Shamir, the “s” in the Rivest–Shamir–Adleman (RSA) public-key cryptosystem, advise organizations to take a hybrid approach that combines classic encryption algorithms such as RSA or Elliptic-curve Diffie–Hellman (ECDH) with post-quantum algorithms such as Module-Lattice-based Key Encapsulation Mechanism (ML-KEM). This approach, which is used by AWS and recommended by The European Commission, offers protection against both current and future threats.

RSAC Award for Excellence in the Field of Mathematics

Dr. Shai Halevi, Senior Principal Applied Scientist at AWS, was presented with the Award for Excellence in the Field of Mathematics for remarkable contributions to many areas of cryptography, including fundamental theory, advanced cryptographic primitives, secure multi-party computations, homomorphic encryption, and cryptographic code obfuscation.

Figure 5: Dr. Shai Halevi receives RSAC award for Excellence in the Field of Mathematics

Figure 5: Dr. Shai Halevi receives RSAC Award for Excellence in the Field of Mathematics

End-to-end encryption

Concerns about the recent US government group chat leak were also raised during the discussion. Public-key cryptography pioneer Whitfield Diffie noted that the use of an encrypted consumer messaging app to communicate classified information broke archiving laws. Because some commercial tools use 256-bit Advanced Encryption Standard (AES) encryption, which is “good enough” to protect communications, he predicted an increase in the use of consumer applications to protect sensitive information in unapproved ways.

The Cybersecurity and Infrastructure Security Agency (CISA) and the Federal Bureau of Investigation (FBI) recently advised individuals and organizations to start using encrypted messaging apps. However, as the role of these applications in business communication expands, it’s important not to lose sight of recordkeeping and compliance obligations. Organizations should consider solutions that offer administrative controls and data retention capabilities along with encryption.

AWS Wickr, for example, is a messaging and collaboration service that protects messaging, calling, file sharing, screen sharing, and location sharing with 256-bit end-to-end encryption. The data retention and administrative controls that it provides help customers meet regulatory requirements and manage user and device data remotely.

Wickr is Department of Defense Cloud Computing Security Requirements Guide Impact Level 5 (DoD CC SRG IL5) and Federal Risk and Authorization Management Program (FedRAMP) High authorized in the AWS GovCloud (US-West) Region. It also meets compliance programs and standards such as Health Insurance Portability and Accountability Act (HIPAA) eligibility, International Organization for Standardization (ISO) 27001, and System and Organization Controls (SOC) 1, 2, and 3.

Visit the AWS News Blog and the AWS Security Blog to learn about AWS passkey multi-factor authentication, how AWS is migrating to post quantum cryptography (PQC), and how we can help you implement a layered encryption strategy for your organization.

Public-private collaboration

Numerous sessions underlined the importance of collaboration to strengthening security. In his keynote, Johnson called attention to a lesson he learned on the basketball court—his peers made him stronger. “Larry Bird made me a better basketball player,” he said, relating his experience to the need for security teams to assist and learn from each other.

In Making America Safe Again Through Cyber Defense, Kristi Noem, U.S. Secretary of Homeland Security equated cybersecurity with national security, and insisted that building on public-private partnerships is “incredibly important.” “Our goal,” she said, “is to use our maximum effect of cooperation to make sure that we’re going after bad actors.”

After assuring attendees that CISA will continue to be America’s cyber defense agency, she urged congress to reauthorize the Cybersecurity Information Sharing Act of 2015. The law, which is set to expire in September, incentivizes businesses to share threat indicators with the Department of Homeland Security (DHS) and helps make sure that both the federal government and companies can take collaborative steps to address threats.

Panelists at an offsite threat intelligence discussion reiterated the ability of private industry to supplement government security capabilities. Adam Meyers, Senior VP, Counter Adversary Operations at CrowdStrike pointed out that technology companies often have more data and signals than governments. The CrowdStrike Falcon solution, he said, processes over 6 trillion events per day, and 55 million events per second at peak. This volume facilitates the detection of threat patterns that might otherwise go unnoticed.

Similarly, Moses noted that the size and scale of AWS infrastructure gives us unique visibility into internet traffic. Our global network of sensors and associated disruption tools observe over 700 million threat interactions every day, out of which 450 million can be classified as malicious. Internal threat intelligence tools such as MadPot, our sophisticated global honeypot system, produce high-fidelity findings (pieces of relevant information) that can be used to drive proactive intelligence sharing, and reduce investigative workloads.

“We’ll work together in order to be able to put a bow on a case and hand it to the FBI and DOJ, such that they don’t have to expend a great amount of resources in order to go forward and try to figure things out that we already know.” —CJ Moses, Chief Information Security Officer and VP of Security Engineering at Amazon

An example of this is the disruption of the cybercriminal group known as Anonymous Sudan. The group was responsible for tens of thousands of distributed denial-of-service (DDoS) attacks against critical infrastructure, corporate networks, and government agencies. With the help of tools like MadPot, AWS experts were able to identify the hosting provider infrastructure that the group used to launch the DDos attacks, and work with providers to disrupt them. Akamai SIRT, Cloudflare, CrowdStrike, DigitalOcean, Flashpoint, Google, Microsoft, PayPal, SpyCloud, and other private sector entities also assisted law enforcement, leading to the indictment of two Anonymous Sudan leaders.

The value of combined perspectives

RSA Conference 2025 might be over, but the learning continues. Additional highlights that include the west stage keynotes, the Innovation Sandbox, and dozens of insightful sessions on topics such as the changing role of the CISO, women in cyber, and of course—cloud security—are available on demand.

If there’s one key takeaway, it’s a collective sense of transition. As we explore the benefits and risks of emerging AI technologies, encryption strategies, and information sharing, it’s important to remember that we cannot effectively combat threats in isolation. Security is a collective endeavor; only by working together can we adapt to evolving challenges and build cyber resilience.

For more information about cloud security, register to join AWS, Google Cloud, and Microsoft online at the SANS 2025 Cloud Security Exchange on August 21.

Anne Grahn

Anne Grahn

Anne is a Senior Worldwide Security GTM Specialist at AWS, based in Chicago. She has 15 years of experience in the security industry and focuses on effectively communicating cybersecurity risk. She maintains a Certified Information Systems Security Professional (CISSP) certification.

Application security at re:Inforce 2025

Post Syndicated from Daniel Begimher original https://aws.amazon.com/blogs/security/application-security-at-reinforce-2025/

AWS re:Inforce 2025: June 16-18 in Philadelphia, PA

A full conference pass is $1,099. Register today with the code flashsale150 to receive a limited time $150 discount, while supplies last.

Join us in Philadelphia on June 16–18, 2025, for AWS re:Inforce, where you can enhance your skills and confidence in cloud security, compliance, identity, and privacy. As an attendee, you will have access to hundreds of technical and non-technical sessions, an Expo featuring Amazon Web Services (AWS) experts and AWS Security Competency Partners, and keynote sessions led by industry leaders. AWS re:Inforce offers a comprehensive focus on key security areas, including application security (AppSec).

Key AppSec themes for 2025

The AppSec track helps you understand and implement best practices for securing your applications throughout the development lifecycle. For 2025, we’re focusing on several key themes:

Organizational strategies to ship quickly and securely

Learn about security ownership, partnerships like DevSecOps, comprehensive application security programs, and scaling application security expertise into workload teams. These sessions explore how organizations can build security into their development processes without sacrificing speed, focusing on practical approaches that distribute security responsibility effectively.

Secure by design

Make embedding security principles into the early stages of software architecture and design to mitigate vulnerabilities early, minimize risks, and recognize security as a core business requirement. Learn how leading organizations implement security as a foundational element rather than an add-on consideration.

Security of the pipeline

Security of the pipeline includes tooling, reference architectures, and best practices for securing the pipeline, including Supply chain Levels for Software Artifacts (SLSA), Supply Chain Integrity, Transparency, and Trust (SCITT), and code signing. Discover how to protect the systems and processes that build and deploy your applications.

Security in the pipeline

Security in the pipeline is achieved in part through testing methodologies including static analysis, dynamic analysis, responsible AI testing, software composition analysis, formal methods (automated reasoning), and dependency tracking. These sessions demonstrate how to integrate comprehensive security testing throughout your development lifecycle.

In the following sections, you’ll find a subset of some of the most exciting sessions happening in our AppSec track this year. For the full list, visit the re:inforce 2025 catalog.

Breakout sessions, chalk talks, lightning talks, and code talks

APS204 | Breakout session | Scaling security with Sportsbet’s Security Guardians program
The Security Guardians program helps scale security across application teams by building and embedding security expertise. We dive deep on Sportsbet’s program where you will learn how to get started, key phases to consider, and the first learning steps for new guardians. Discover lessons learned, common challenges, and how to refine the program for long-term success. By integrating security into application teams early, Sportsbet fosters a culture of shared responsibility, improving security posture without slowing down development. We provide practical insights on launching and evolving a Security Guardians program to drive real impact across your organization.

APS301 | Breakout session | Improve code quality with Amazon Q Developer
Amazon Q Developer is a generative AI assistant that goes beyond writing code—it can also improve documentation, generate unit tests, and automate code reviews. In this session, discover how to integrate Amazon Q Developer into your software development lifecycle to detect security issues using software composition analysis (SCA), static application security testing (SAST), and other code quality checks. Learn how to improve your codebase quality using the capabilities of Amazon Q Developer within the integrated development environment (IDE) and DevSecOps tooling.

APS401 | Breakout session | Build verifiable apps using automated reasoning and generative AI
Large language models (LLMs) excel at generating creative solutions, while automated reasoning tools enable rigorous verification. This session explores methodologies for combining these complementary strengths to create more reliable AI systems. In this session, we introduce automated reasoning and demonstrate how formal methods can guide and constrain generative AI. By combining probabilistic and symbolic approaches, we show you how to build hybrid systems that maintain creative capabilities while ensuring verifiable outputs. We demonstrate how Amazon Q Developer and Amazon Bedrock Guardrails use automated reasoning to generate safe and logically correct output, free from hallucinations.

APS431 | Chalk talk | DevSecOps in action with Visual Studio Code & AWS IAM Access Analyzer
Organizations face a critical balance between developer productivity and security compliance when managing AWS Identity and Access Management (IAM) policies. In this session, discover how integrating AWS IAM Access Analyzer with Visual Studio Code empowers developers to create secure IAM policies during development. Learn to implement automated policy checks that catch overly permissive permissions early, validate against organizational standards, and provide real-time feedback. This proactive approach helps security teams maintain control while giving developers the autonomy they need, ultimately reducing deployment risks and saving valuable development time.

APS341 | Code talk | Move fast and stay secure: Lessons learned from the AWS prototyping team
When building prototypes and applications with technologies such as generative AI and serverless, it’s critical to move quickly and securely. In this code talk, learn how the AWS prototyping team successfully balances these goals. To meet user demand, AWS builds prototypes over a short amount of time while meeting a high bar for security expectations. Learn pointers, tips, and tricks to build quickly and securely, from threat modeling to using AWS Cloud Development Kit (AWS CDK) features, custom constructs, and blueprints to harden the security of your infrastructure and improve productivity.

APS441 | Code talk | Supercharge IaC security with AI: From commit to auto-remediation
Dive deep into building an automated security feedback loop that combines Git commit signatures, static analysis, and generative AI to revolutionize infrastructure as code (IaC) security. Through live coding, we’ll demonstrate how to use Amazon Q Developer and Amazon Bedrock to analyze IaC templates, automatically detect and resolve issues, and generate contextual fix recommendations. Learn how to implement commit-based tracking for security findings, automate issue creation, and integrate with continuous integration and delivery CI/CD pipelines. Watch as we build a complete system that reduces the time from vulnerability detection to remediation from days to minutes.

APS442 | Code talk | Create memory safe applications using open source verification tools
Memory-safety errors pose a significant security risk, enabling various attack vectors. At AWS, we prioritize memory-safety for unmanaged code handling customer data and processes. This talk presents two efforts to reduce memory-safety errors in Rust and C code. Both efforts involve developing verification tools for Rust and C code to check memory safety at scale that you can use. Our first effort verifies the Rust standard library, a core software resource, used by millions of developers. Our second effort uses a C model checker to verify C code for safety and correctness.

APS221 | Lightning talk | Building secure development into Amazon stores
Amazon.com has long been at the forefront of investing in robust security measures to protect customer data. As the digital landscape evolves, so do our strategies. This session explores our journey of continuous improvement in security practices, focusing on integration throughout the software development lifecycle using AWS services. We’ll share the cutting-edge methods used by Amazon.com for embedding security at every development stage and discuss successes and learnings. Join us to discover how we’ve adapted our tactics to meet changing developer and customer needs and to ensure our commitment to protecting customer data remains stronger than ever.

APS222 | Lightning talk | Transform threat modeling using generative AI
Discover how CRED, one of the biggest Fintech companies in India has used generative AI to automate threat modeling across their applications. Learn architectural patterns that enabled CRED to scale security analysis, improve risk identification, and enhance decision-making. See practical examples of integrating AI into security modeling workflows using Amazon Bedrock.

SEC221 | Lightning talk | Raising the tide: How AWS is shaping the future of secure AI for all
AI security is a top priority for AWS. By building AI solutions that are secure by design, AWS helps you innovate quickly with confidence while mitigating emerging threats. But securing AI goes beyond individual organizations—it requires industry-wide standards and best practices. AWS actively contributes to global AI security efforts, including participation in industry standards bodies such as The Coalition for Secure AI (CoSAI), to help ensure that AI technologies are safe, resilient, and trustworthy. This session will explore how AWS is leading AI security innovation, protecting customers, and collaborating to help shape the future of AI security for the entire industry.

Workshops and builders sessions

APS351 | Securing generative AI agents using AWS Well-Architected Framework
Learn hands-on how to build secure generative AI agent solutions following the AWS Well-Architected Framework Generative AI Lens security best practices. Work through practical implementations of endpoint security, prompt engineering guardrails, monitoring systems, and protection against excessive agency while building a production-ready generative AI agent. Through hands-on exercises, build a secure generative AI agent solution incorporating these controls on AWS, using Amazon Bedrock, Amazon CloudWatch, IAM, and more. You must bring your laptop to participate.

APS353 | Red-teaming your LLM security at scale
Step into the shoes of an AI-powered red team adversary in the GenAI Red Team Challenge. In this intensive workshop, you’ll deploy an AI security agent to orchestrate sophisticated attack chains against generative AI applications, systematically discovering and exploiting vulnerabilities from prompt injection to boundary testing while mastering automated security testing workflows. In addition, you’ll learn how to apply countermeasures, from prompt templating to guardrails. This hands-on, gamified experience helps you think like a threat actor and equips you with practical skills in automated vulnerability testing and risk mitigation against common MITRE and OWASP vulnerabilities for LLM-based applications. You must bring your laptop to participate.

APS354 | Secure your application using AWS services and open source tooling
AWS, open source, and partner tooling work together to accelerate your software development lifecycle. Learn how to use the Automated Security Helper (ASH), an open source application security tool, to quickly integrate various security testing tools into your software build and deployment flows. AWS experts guide you through the process of security testing locally on your machines and within a simulated pipeline using a sample generative AI application. Discover how to identify potential security issues in your applications through static analysis, software composition analysis, and infrastructure-as-code testing, and use Amazon Q Developer to review the results and generate remediation. You must bring your laptop to participate.

APS271 | Threat modeling for builders
In this workshop, you will learn threat modeling core concepts and how to apply them through a series of group exercises. Key topics include threat modeling personas, key phases, data flow diagrams, STRIDE (spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege), and risk response strategies. We introduce a threat grammar rule and an associated tool. Exercises will have you identify threats and mitigations through the lens of each of the threat modeling personas. You will assemble in groups and walk through a case study. AWS threat modeling subject matter experts will be on hand to guide you and provide feedback. You must bring your laptop to participate.

APS371 | Securing your generative AI applications on AWS
In this workshop, discover how to secure generative AI applications using AWS services and features. Explore how to deploy a vulnerable sample generative AI application and then layer security controls to protect, detect, and respond to security issues. Learn how to apply similar controls to the generative AI applications in your organization. You must bring your laptop to participate.

APS471 | Boost developer productivity with Amazon Q Developer and Amazon Bedrock
Accelerate development and drive innovation with Amazon Q Developer and Amazon Bedrock. Discover how AI-powered automation and intelligent code assistance can reduce friction, speed up development cycles, and improve code quality. Explore real-world use cases such as AI-driven code reviews, automated testing, and smart documentation generation. Learn how to seamlessly integrate these tools into your workflows to boost efficiency, enhance collaboration, and elevate the developer experience—all while making sure of security and compliance. Whether optimizing existing processes or adopting AI for the first time, this session provides actionable insights to supercharge your development teams. You must bring your laptop to participate.

Conclusion

This post showcases a subset of the exciting AppSec sessions available at the upcoming AWS re:Inforce 2025 conference. If you’re interested in these topics, we encourage you to register for re:Inforce 2025, where you can attend these sessions and many more across the other security domain tracks. To discover the full range of sessions across all security tracks, check out the complete AWS re:Inforce catalog.

If you have feedback about this post, submit comments in the Comments section below.

Daniel Begimher

Daniel Begimher

Daniel is a Senior Security Engineer specializing in cloud security and incident response solutions. He co-leads the Application Security focus area within the AWS Security and Compliance Technical Field Community, holds all AWS certifications, and authored Automated Security Helper (ASH), an open source code scanning tool. In his free time, Daniel enjoys gadgets, video games, and traveling.

Danny Cortegaca

Danny Cortegaca

Danny is a Security Specialist Solutions Architect and co-leads the Application Security focus area within the AWS Security and Compliance Technical Field Community. He joined AWS in 2021 and partners with some of the largest organizations in the world to help them navigate complex security and regulatory environments. He loves talking about application security with customers and has helped many adopt threat modeling into their practices.

AI lifecycle risk management: ISO/IEC 42001:2023 for AI governance

Post Syndicated from Abdul Javid original https://aws.amazon.com/blogs/security/ai-lifecycle-risk-management-iso-iec-420012023-for-ai-governance/

As AI becomes central to business operations, so does the need for responsible AI governance. But how can you make sure that your AI systems are ethical, resilient, and aligned with compliance standards?

ISO/IEC 42001, the international management system standard for AI, offers a framework to help organizations implement AI governance across the lifecycle. In this post, we walk through how ISO/IEC 42001 enables effective AI governance, review the risk management requirements, and explore how you can use threat modeling as a practical technique to meet those expectations.

AI governance

AI governance refers to the organizational structures, policies, and controls that enable AI systems to be used responsibly, ethically, and safely. Governance spans the entire AI lifecycle and includes the following activities:

  • Setting the intended purpose and stakeholder alignment
  • Managing data, models, and deployment risks
  • Designing in explainability, bias mitigation, and traceability
  • Establishing accountability, monitoring, and decommissioning practices

These activities are the foundation of a formal framework that you can use to establish governance processes, identify and manage risk, and implement processes for continuous improvement

AI lifecycle

While ISO 42001 provides a framework for AI governance, ISO/IEC 22989:2022 describes what an AI system is and how it evolves. Governance should be implemented at every stage of the AI lifecycle to manage AI risks effectively. According to the ISO/IEC 22989:2022 standard, an organization’s AI life cycle might include these stages:

  1. Inception: Identifying needs, goals, and feasibility
  2. Design and development: Defining system architecture, data flows, and training models
  3. Verification and validation: Testing and confirming that the system meets requirements and performs as intended
  4. Deployment: Releasing the system into its operational environment
  5. Operation and monitoring: Running the system, logging activity, and monitoring performance and outcomes
  6. Re-evaluation: Assessing whether the system continues to meet objectives under changing conditions
  7. Retirement: Decommissioning the system and addressing long-term data and access risks

Understanding the AI lifecycle, shown in Figure 1 that follows, is critical for identifying and mitigating AI risks. While these seven stages are provided directly in ISO 22989:2022, your organization might define its AI lifecycle stages differently to suit its business context. We refer to these stages as we explore the components of an AI management system, from initial AI system scoping, through threat monitoring and risk assessment, to monitoring the established governance program.

Figure 1: Example of AI system lifecycle model stages and high-level processes based on ISO/IEC 22989:2022

Figure 1: Example of AI system lifecycle model stages and high-level processes based on ISO/IEC 22989:2022

Risk management in ISO/IEC 42001:2023

After an organization has identified and assessed AI risks (Clause 6.1 of ISO/IEC 42001:2023), operational controls to mitigate those risks must be implemented (Clause 8.2), and those controls and the AI system itself should be continuously monitored, documented, and improved (Clauses 9 and 10). AI impact assessments (AIIAs) are critical in high-risk use cases, complementing baseline risk assessments by focusing on societal, ethical, and legal impacts. AIIAs are like data protection impact assessments (DPIAs) for high-risk personal data processing under many privacy regulations. DPIAs are specifically designed to assess risks to individuals’ privacy and data protection rights under laws such as the GDPR. While AIIAs help organizations maintain responsible AI governance, DPIAs can be used in parallel to help verify that AI systems comply with data protection laws, together providing a holistic view of risks and safeguards across both ethical and legal dimensions.

You are free to select the AIIA tools or methodologies that best fit your use case. Two widely accepted frameworks are:

  • ISO 31000: A general-purpose enterprise risk management standard that helps identify, evaluate, and treat risks in a structured and repeatable way. It aligns well with organizations seeking to embed AI risk into their broader enterprise risk management (ERM) programs.
  • NIST AI Risk Management Framework (AI RMF): A NIST framework specifically designed for AI systems. It introduces tailored concepts such as explainability, robustness, fairness, and accountability, with actionable guidance organized into four core functions: Map, measure, manage, and govern.

ISO 42001 provides structured methods to conduct risk and impact assessments. Threat modeling tools such as:

  • STRIDE (spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege). STRIDE aims to make sure that a system meets security requirements for confidentiality, integrity and availability.
  • DREAD (damage potential, reproducibility, exploitability, affected users, and discoverability) is a framework that can assess severity of individual threats.
  • OWASP (Open Worldwide Application Security Project) for machine learning (ML) enables analysis of AI system vulnerabilities, adversarial risks, and privacy threats.

Trustworthy AI is the result of strategic governance, structured methodologies, and technical analysis.

Figure 2 that follows shows the tiered structure of AI risk governance, moving from high-level governance to detailed technical assessments. On the left side, there’s a downward flow representing the increasing depth of controls, while the right side shows an upward scale indicating escalating AI risks.

  • At the top layer, ISO/IEC 42001:2023 defines formal requirements for AI governance, including risk assessment mandates, control implementation, and lifecycle oversight.
  • The middle layer features widely adopted risk assessment methodologies and frameworks, such as ISO 31000 and the NIST AI Risk Management Framework (RMF), which provide structured methods to identify, evaluate, and mitigate AI risks.
  • At the base, are detailed threat modeling tools—including STRIDE, DREAD, PASTA, LINDDUN, and OWASP for ML—that support deep analysis of AI systems for vulnerabilities related to security, privacy, data protection, and adversarial threats.

Together, these layers form a comprehensive approach to AI risk governance, aligning strategic oversight with operational and technical defenses.

Figure 2: A layered approach to AI risk management aligned with ISO/IEC 42001. ISO/IEC 42001 defines AI governance for responsible AI

Figure 2: A layered approach to AI risk management aligned with ISO/IEC 42001. ISO/IEC 42001 defines AI governance for responsible AI

Threat modeling for AI risk identification

Threat modeling identifies AI lifecycle technical risks such as exploit surfaces, adversarial threats, and misuse scenarios that complement organizational risk analysis and impact assessments. This post takes a broader AI lifecycle view, showing you how threat modeling complements other risk strategies within the context of ISO/IEC 42001:2023. Additionally, AWS has published AI threat modeling guidance, such as:

The following table is an example STRIDE threat model for a generative AI resource using AWS services by AI lifecycle stage and risk type. This illustrates technical threat remediation through AWS cloud native governance features.

STRIDE category Example threat Lifecycle stage Risk type AWS feature for governance
Spoofing A fake identity uses the AI system to generate phishing emails or misinformation Inception Security AWS IAM Identity Center and Amazon Cognito for multi-factor authentication (MFA), Amazon GuardDuty for threat detection
Tampering A malicious prompt injection or API injection alters the model behavior or bypasses filters Design development Integrity Amazon Bedrock Guardrails, Amazon API Gateway and AWS WAF rules, AWS CloudTrail for input auditing
Repudiation Users deny prompt activity or content creation, and there’s no logging Verification and validation Accountability CloudTrail, Amazon Bedrock invocation logs, Amazon SageMaker ML Lineage Tracking for traceability
Information disclosure Sensitive internal data—such as code or personally identifiable information (PII)—accidentally learned and reproduced by the large language model (LLM) Operation and monitoring Privacy, Security SageMaker Clarify, AWS VPC PrivateLink, AWS Key Management Service (AWS KMS) encryption, Amazon Bedrock data handling commitments
Denial of service Bad actors overload the AI endpoint with prompt spam, degrading service Deployment Availability AWS Shield, API rate limiting using API Gateway, auto scaling with SageMaker endpoints
Elevation of privilege An internal user modifies system prompts or updates to override content filters Reevaluation Ethics and access control AWS Identity and Access Management (IAM) roles, Amazon Bedrock Guardrails, AWS Config, service control policies (SCPs)

While STRIDE is used here for illustrative clarity, it’s just one of several threat modeling approaches that can be applied depending on the system context. Other widely recognized methods include:

By integrating these threat modeling practices into ISO/IEC 42001’s risk-based approach, organizations are not just “checking compliance boxes” they’re operationalizing trustworthy, secure, and accountable AI governance throughout the full system lifecycle.

Threat modeling touchpoints across the AI lifecycle

ISO 42001:2023 uses the STRIDE threat modeling framework to align specific security threats to each stage. Each lifecycle stage is associated with particular threat types, relevant Annex references from the ISO standard, and examples of what to monitor.

  • Inception (Annex A.8.1): Focuses on spoofing and fake identity input risks.
  • Design and Development (Annex A.9.1): Linked to tampering threats.
  • Verification and Validation (Annex A.7.1): Concerns around repudiation, such as lack of model decision logs.
  • Deployment (Annex A.5.1): Addresses information disclosure vulnerabilities.
  • Operation and Monitoring (Annex A.10.3): Maps to denial-of-service attacks.
  • Re-evaluation (Annex A.8.6): Highlights risks of privilege escalation.

AI threat modeling isn’t a one-time task but must be applied continuously across each lifecycle stage, supported by ISO 42001’s annexes and STRIDE categories.

Figure 3: An illustration of how organizations can use ISO/IEC 42001:2023 as a structured framework for AI risk management, using threat modeling as a key technique across the AI lifecycle

Figure 3: An illustration of how organizations can use ISO/IEC 42001:2023 as a structured framework for AI risk management, using threat modeling as a key technique across the AI lifecycle

AWS tools for AI governance and risk management

AWS governance service capabilities support the controls required in the Statement of Applicability (SoA) under ISO/IEC 42001. These services and features help organizations operationalize responsible AI practices at scale and align with ISO/IEC 42001’s emphasis on structured, accountable AI lifecycle management.

  • Amazon SageMaker Model Cards: Provides standardized documentation for ML models including purpose, performance, and limitations. In the governance context, model cards help maintain transparency, accountability, and auditability of model behavior and use.
  • Amazon SageMaker Clarify: Detects bias in datasets and models and supports explainability of predictions. This directly supports governance controls related to fairness, non-discrimination, and explainability.
  • Amazon SageMaker Ground Truth: Provides high-quality, human-in-the-loop data labeling workflows. It supports data governance by making sure labeled datasets are accurate, consistent, and traceable.
  • Amazon Bedrock Guardrails: Can be used to define safety filters for generative AI, such as avoiding toxic content or harmful outputs. This facilitates alignment with ethical and content governance policies.
  • AWS CloudTrail and AWS Config: Enable audit logging and continuous monitoring of system changes. These are essential for accountability, traceability, and compliance reporting within AI governance frameworks.
  • AWS Identity and Access Management (IAM), AWS Key Management Service (AWS KMS), and AWS PrivateLink: IAM controls access, AWS KMS provides encryption and key management, and PrivateLink enables private connectivity. These features are critical for enforcing access governance, securing data, and maintaining privacy standards.
  • AWS Generative AI Lens: A part of the AWS Well-Architected Framework tool. It provides structured guidance for evaluating and improving the design of generative AI systems. It helps organizations implement responsible AI practices, manage risks

Conducting AI impact assessments for high risk use cases

While general risk assessments (Clause 6.1 of ISO/IEC 42001) are required for AI systems, ISO/IEC 42001 also calls for AIIAs in situations where the AI system poses high potential impact to individuals, groups, or society. AIIAs should result in a documented report of identified risks associated with the target AI activity, in addition to the severity of potential negative outcomes. These risks should be integrated into the AI management system (AIM) and monitored over time. Several stakeholders and specialists might need to provide input in the assessment process, such as legal, risk, compliance, data management, and security teams. Identified risks should be mitigated where possible, and a determination made about whether the residual risk is acceptable.

AIIAs help answer questions such as:

  • Is the AI use justifiable, ethical, and proportionate?
  • Could the system cause discrimination, exclusion, or loss of rights?
  • What safeguards should be built to protect affected people?

AIIA is required:

  • If the system makes or informs decisions that materially affect people
  • If the system is deployed in sensitive domains (such as healthcare, finance, or public services)
  • If risks to fundamental rights, fairness, or trust are flagged during initial risk assessments

AIAA should cover:

  • Purpose and scope of the AI system
  • Stakeholder and impact mapping
  • Legal, ethical, and social risk evaluation
  • Transparency and recourse mechanisms
  • Recommendations for mitigation

AIIA process workflow

Figure 4 that follows illustrates a generic AIIA workflow that includes initiating, scoping, assessing impact, planning mitigation, and documenting the outcome to evaluate how an AI system can affect individuals, groups, and society. Organizations can tailor this process to the AI system context, business objectives, and compliance requirements for their use case.

Figure 4: Sample prescriptive process with key phases on conducting an AIIA

Figure 4: Sample prescriptive process with key phases on conducting an AIIA

AIIA outcome

AIIA reports should capture the core purpose of the exercise: to evaluate how an AI system might affect individuals, communities, and society at large and to make sure that potential risks are addressed through appropriate mitigation strategies. While formats might vary across industries, an AIIA outcome typically includes key sections such as summary of system purpose, a mapping of affected stakeholders, a contextual analysis of legal and social factors, an evaluation of likely impacts (including fairness, bias, and autonomy risks) and a plan for a mitigation, oversight, and monitoring. Governance details such as sign off responsibility and reassessment triggers should also be included.

Whether you’re starting from scratch or adapting an existing template, these foundational elements will help make sure that your documentation supports transparency, accountability, and ethical AI deployment.

Templates:

Mapping AI lifecycle risks to ISO/IEC 42001 controls

After you have identified risks through techniques such as threat modeling and impact assessments, the next step is to make sure that they’re mitigated through the appropriate ISO/IEC 42001 controls. Using the lifecycle stages defined in ISO/IEC 22989:2022, you can map AI risks identified during the threat hunting process to the corresponding ISO/IEC 42001:2023 clauses and Annex A controls. This mapping helps you align your AI development and governance efforts with a standards-based risk framework.

AI lifecycle stage Identified risk Relevant ISO/IEC 42001 clauses Risk mitigation – Annex A controls
Inception Spoofing: Impersonation Clause 4, Clause 5 A.6.1 (Governance roles), A.5.1
Design and development Tampering: Unauthorized changes Clause 6.1, Clause 8.2 A.8.2, A.9.1
Verification and validation Repudiation: No traceability Clause 8.2 A.8.5, A.7.1
Deployment Elevation of privilege: Unauthorized model tweaks Clause 8.2, Clause 9.1 A.10.2, A.6.1
Operation and monitoring Denial of service: System overload Clause 9.1, Clause 10.1 A.8.3, A.10.3
Re-evaluation Drift and new threat vectors Clause 9.3, Clause 10.2 A.10.2, A.6.4
Retirement Information disclosure: Residual risks Clause 8.3, Clause 10.2 A.9.4, A.5.2

Maintaining AI governance

Like most technology risk and governance programs, AI management must be continuously monitored and maintained. ISO 42001 requires an organization to have leadership support and sufficient resources to operate effectively over time. This means that AI governance should be built into every process in the AI development and maintenance journey. AIIAs and threat modeling should be conducted at least annually on existing systems, and prior to the deployment of any new AI function. Policies should be reviewed at least annually and after major change to the AI system. Internal audits should review and monitor compliance with controls continuously, and organizations seeking ISO certification will require annual external audits. Progress toward governance goals and metrics on the status of known AI risks should be reported to the highest level of leadership in a live dashboard, and incidents of negative outcomes related to AI use should be tracked and analyzed to improve the AI system.

Conclusion

Managing AI risk effectively means aligning technical, organizational, and ethical considerations throughout the AI system lifecycle. ISO/IEC 42001 provides structure and accountability. Threat modeling techniques such as STRIDE, MITRE ATLAS, and OWASP for LLM surface deep technical risks. AWS services and features such as SageMaker Model Cards, SageMaker Clarify, and Amazon Bedrock Guardrails help embed governance into layers of AI development.

By combining technical tools, structured assessments, and standards-driven controls, you can build AI systems that are trustworthy, resilient, and aligned with societal expectations.

For additional guidance on achieving, maintaining, and automating compliance in the cloud, contact AWS Security Assurance Services (AWS SAS) or their account team. AWS SAS is a PCI QSAC and HITRUST Assessor Firm that can help by tying together applicable audit standards to AWS service specific features and functionality. They help you build on frameworks such as ISO 42001, PCI DSS, HITRUST CSF, NIST-CSF and Privacy Framework, SOC 2, HIPAA, ISO 27001 and 27701, and more. In addition, AWS Professional Services can also help you plan and map your compliance journey.

Disclaimer: The risk strategies and threat modeling guidance shared in this blog are intended to provide general direction and practical insight into implementing AI risk management under ISO/IEC 42001:2023. However, organizations are responsible for conducting their own context-specific risk assessments, as mandated by the standard. This blog should not be interpreted as an exhaustive approach to or guarantee of compliance with ISO/IEC 42001.

If you have feedback about this post, submit comments in the Comments section below.

Abdul Javid

Abdul Javid

Abdul is a Senior Security Assurance Consultant and a PECB ISO 42001 Lead Auditor and IAPP Certified AI Governance Professional. He draws on his extensive experience to guide AWS customers on compliance matters. He holds an M.S. in Computer Science from IIT Chicago and numerous certifications from IAPP, AWS, ISO, HITRUST, ISACA, PMI, PCI DSS, and ISC2.

Amber Welch

Amber Welch

Amber is a Senior Privacy Consultant with AWS Security Assurance Services and a PECB-certified ISO 42001 Lead Auditor. With extensive security and privacy management experience across industries, she advises AWS customers on compliance and risk management. She holds an M.A. in English – Technical Communication, CIPM and CIPP-E certifications, and is a thought leader in AI privacy, contributing to the AWS Privacy Reference Architecture.

Security Week 2025: in review

Post Syndicated from Kim Blight original https://blog.cloudflare.com/security-week-2025-wrap-up/

Thank you for following along with another Security Week at Cloudflare. We’re extremely proud of the work our team does to make the Internet safer and to help meet the challenge of emerging threats. As our CISO Grant Bourzikas outlined in his kickoff post this week, security teams are facing a landscape of rapidly increasing complexity introduced by vendor sprawl, an “AI Boom”, and an ever-growing surface area to protect.

As we continuously work to meet new challenges, Innovation Weeks like Security Week give us an invaluable opportunity to share our point of view and engage with the wider Internet community. Cloudflare’s mission is to help build a better Internet. We want to help safeguard the Internet from the arrival of quantum supercomputers, help protect the livelihood of content creators from unauthorized AI scraping, help raise awareness of the latest Internet threats, and help find new ways to help reduce the reuse of compromised passwords. Solving these challenges will take a village. We’re grateful to everyone who has engaged with us on these issues via social media, contributed to our open source repositories, and reached out through our technology partner program to work with us on the issues most important to them. For us, that’s the best part.

Here’s a recap of this week’s announcements:

Helping make the Internet safer

Title

Excerpt

Conventional cryptography is under threat. Upgrade to post-quantum cryptography with Cloudflare Zero Trust

We’re thrilled to announce that organizations can now protect their sensitive corporate network traffic against quantum threats by tunneling it through Cloudflare’s Zero Trust platform.

How Cloudflare is using automation to tackle phishing head on

How Cloudflare is using threat intelligence and our Developer Platform products to automate phishing abuse reports.

Advancing account security as part of Cloudflare’s commitment to CISA’s Secure by Design pledge

Cloudflare has made significant progress in boosting multi-factor authentication (MFA) adoption. With the addition of Apple and Google social logins, we’ve made secure access easier for our users.

Email Security now available for free for political parties and campaigns through Cloudflare for Campaigns

We’re excited to announce that Cloudflare for Campaigns now includes Email Security, adding an extra layer of protection to email systems that power political campaigns.

Enhanced security and simplified controls with automated botnet protection, cipher suite selection, and URL Scanner updates

Enhanced security, simplified control! This Security Week, Cloudflare unveils automated botnet protection, flexible cipher suites, and an upgraded URL Scanner.

Password reuse is rampant: nearly half of user logins are compromised

Nearly half of login attempts across websites protected by Cloudflare involved leaked credentials. The pervasive issue of password reuse is enabling automated bot attacks on a massive scale.

Threat research from the network that sees the most threats 

Title

Excerpt

Unleashing improved context for threat actor activity with our Cloudforce One threat events platform

Gain real-time insights with our new threat events platform. This tool empowers your cybersecurity defense with actionable intelligence to stay ahead of attacks and protect your critical assets.

One platform to manage your company’s predictive security posture with Cloudflare

Cloudflare introduces a single platform for unified security posture management, helping protect SaaS and web applications deployed across various environments.

Cloudflare enables native monitoring and forensics with Log Explorer and custom dashboards

We are excited to announce support for Zero Trust datasets, and custom dashboards where customers can monitor critical metrics for suspicious or unusual activity

Introducing new Turnstile Analytics: Gain insight into your visitor traffic, bot behavior patterns, traffic anomalies, and attack attributes.

Introducing new Turnstile Analytics: gain insight into your visitor traffic, bot behavior patterns, traffic anomalies, and attack attributes.

Extending Cloudflare Radar’s security insights with new DDoS, leaked credentials, and bots datasets

For Security Week 2025, we are adding several new DDoS-focused graphs, new insights into leaked credential trends, and a new Bots page to Cloudflare Radar.

Securing models and guarding against AI threats 

Title

Excerpt

Cloudflare for AI: supporting AI adoption at scale with a security-first approach

With Cloudflare for AI, developers, security teams, and content creators can leverage Cloudflare’s network and portfolio of tools to secure, observe, and make AI applications resilient and safe to use.

How we train AI to uncover malicious JavaScript intent and make web surfing safer

Learn more about how Cloudflare developed an AI model to uncover malicious JavaScript intent using a Graph Neural Network, from pre-processing data to inferencing at scale.

An early look at cryptographic watermarks for AI-generated content

It’s hard to tell the difference between web content produced by humans and web content produced by AI. We’re taking a new approach to making AI content distinguishable without impacting performance.

How Cloudflare uses generative AI to slow down, confuse, and waste the resources of AI Crawlers and other bots that don’t respect “no crawl” directives.

How Cloudflare uses generative AI to slow down, confuse, and waste the resources of AI Crawlers and other bots that don’t respect “no crawl” directives.

Take control of public AI application security with Cloudflare’s Firewall for AI

Firewall for AI discovers and protects your public LLM-powered applications, and is seamlessly integrated with Cloudflare WAF. Join the beta now and take control of your generative AI security

Improved Bot Management flexibility and visibility with new high-precision heuristics

By building and integrating a new heuristics framework into the Cloudflare Ruleset Engine, we now have a more flexible system to write rules and deploy new releases rapidly

Simplifying security

Title

Excerpt

Introducing Cloudy, Cloudflare’s AI agent for simplifying complex configurations

Cloudflare’s first AI agent, Cloudy, helps make complicated configurations easy to understand for Cloudflare administrators.

Making Application Security simple with a new unified dashboard experience

We’re introducing a new Application Security experience in the Cloudflare dashboard, with a reworked UI organized by use cases, making it easier for customers to navigate and secure their accounts

Improved support for private applications and reusable access policies with Cloudflare Access

We are excited to introduce support for private hostname and IP address-defined applications as well as reusable access policies.

Simplify allowlist management and lock down origin access with Cloudflare Aegis

Cloudflare Aegis provides dedicated egress IPs for Zero Trust origin access strategies, now supporting BYOIP and customer-facing configurability, with observability of Aegis IP address utilization coming soon.

HTTPS-only for Cloudflare APIs: shutting the door on cleartext traffic

We are closing the cleartext HTTP ports entirely for Cloudflare API traffic. This prevents the risk of clients unintentionally leaking their secret API keys in cleartext during the initial request, before we can reject the connection at the server side.

Cloudflare named a leader in Web Application Firewall Solutions in 2025 Forrester report

Forrester Research has recognized Cloudflare as a Leader in its The Forrester Wave™: Web Application Firewall Solutions, Q1 2025 report.

Data security everywhere, all the time 

Title

Excerpt

Detecting sensitive data and misconfigurations in AWS and GCP with Cloudflare One

Using Cloudflare’s CASB, integrate, scan, and detect sensitive data and misconfigurations in your cloud storage accounts.

RDP without the risk: Cloudflare’s browser-based solution for secure third-party access

Cloudflare now provides clientless, browser-based support for the Remote Desktop Protocol (RDP). It natively enables secure, remote Windows server access without VPNs or RDP clients, to support third-party access and BYOD security.

Improving Data Loss Prevention accuracy with AI-powered context analysis

Cloudflare’s Data Loss Prevention is reducing false positives by using a self-improving AI-powered algorithm, built on Cloudflare’s Developer Platform, to improve detection accuracy through AI context analysis.

Enhance data protection in Microsoft Outlook with Cloudflare One’s new DLP Assist

Customers can now easily safeguard sensitive data in Microsoft Outlook with our new DLP Assist feature.

Prepping for post-quantum: a beginner’s guide to lattice cryptography

This post is a beginner’s guide to lattices, the math at the heart of the transition to post-quantum (PQ) cryptography. It explains how to do lattice-based encryption and authentication from scratch.

Cloudflare is now IRAP assessed at the PROTECTED level, furthering our commitment to the global public sector

Cloudflare is now assessed at the IRAP PROTECTED level, bringing our products and services to the Australian Public Sector.

Tune in to the latest on Cloudflare TV

For a deeper dive on many of the great announcements from Security Week, check out our CFTV segments where our team shares even more details on our latest updates. 

See you for our next Innovation Week

We appreciate everyone who’s taken the time to read Cloudflare’s Security Week blog posts or engage with us on these topics via social media. Our next innovation week, Developer Week, is right around the corner in April. We look forward to seeing you then!

Cloudflare named a leader in Web Application Firewall Solutions in 2025 Forrester report

Post Syndicated from Daniele Molteni original https://blog.cloudflare.com/cloudflare-named-leader-waf-forrester-2025/

Forrester Research has recognized Cloudflare as a Leader in it’s The Forrester Wave™: Web Application Firewall Solutions, Q1 2025 report. This market analysis helps security and risk professionals select the right solution for their needs. According to Forrester: 

“Cloudflare is a strong option for customers that want to manage an easy-to-use, unified web application protection platform that will continue to innovate.”

In this evaluation, Forrester assessed 10 Web Application Firewall (WAF) vendors across 22 criteria, including product security and vision. We believe this recognition is due to our continued investment in our product offering. Get a complimentary copy of the report here.

Since introducing our first WAF in 2013, Cloudflare has transformed it into a robust, enterprise-grade Application Security platform. Our fully integrated suite includes WAF, bot mitigation, API security, client-side protection, and DDoS mitigation, all built on our expansive global network. By leveraging AI and machine learning, we deliver industry-leading security while enhancing application performance through our content delivery and optimization solutions.

According to the Forrester report, “Cloudflare stands out with features that help customers work more efficiently.” Unlike other solutions in the market, Cloudflare’s WAF, API Security, bot detection, client-side security, and DDoS protection are natively integrated within a single platform, running on a unified engine. Our integrated solution empowers a seamless user experience and enables advanced threat detection across multiple vectors to meet the most demanding security requirements.

Cloudflare: a standout in Application Security

Forrester’s evaluation of Web Application Firewall solutions is one of the most comprehensive assessments in the industry. We believe this report highlights Cloudflare’s integrated global cloud platform and our ability to deliver enterprise-grade security without added complexity. We don’t just offer a WAF — we provide a flexible, customizable security toolkit designed to address your unique application security challenges.

Cloudflare continuously leads the WAF market through our strategic vision and the breadth of our capabilities. We center our approach on relentless innovation, delivering industry-leading security features, and ensuring a seamless management experience with enterprise processes and tools such as Infrastructure as Code (IaC) and DevOps. Our predictable cadence of major feature releases, powered by annual initiatives like Security Week and Birthday Week, ensures that customers always have access to the latest security advancements.

We believe Forrester also highlighted Cloudflare’s extensive security capabilities, with particular recognition of the significant improvements in our API security offerings.

Cloudflare’s top-ranked criteria

In the report, Cloudflare received the highest possible scores in 15 out of 22 criteria, reinforcing, in our opinion, our commitment to delivering the most advanced, flexible and easy-to-use web application protection in the industry. Some of the key criteria include:

  • Detection models: Advanced AI and machine learning models that continuously evolve to detect new threats.

  • Layer 7 DDoS protection: Industry-leading mitigation of sophisticated application-layer attacks.

  • Rule creation and modification: Simple, easy to use rule creation experience, propagating within seconds globally.

  • Management UI: An intuitive and efficient user interface that simplifies security management.

  • Product security: A robust architecture that ensures enterprise-grade security.

  • Infrastructure-as-code support: Seamless integration with DevOps workflows for automated security policy enforcement.

  • Innovation: A forward-thinking approach to security, consistently pushing the boundaries of what’s possible.

What sets Cloudflare apart?

First, Cloudflare’s WAF goes beyond traditional rule-based protections, offering a comprehensive suite of detection mechanisms to identify attacks and vulnerabilities across web and API traffic while also safeguarding client environments. We leverage AI and machine learning to detect threats such as attacks, automated traffic, anomalies, and compromised JavaScript, among others. Our industry-leading application-layer DDoS protection makes volumetric attacks a thing of the past.

Second, Cloudflare has also made significant strides in API security. Our WAF can be supercharged with features such as: API discovery, schema validation & sequence mitigation, volumetric detection, and JWT authentication. 

Third, Cloudflare simplifies security management with an intuitive dashboard that is easy to use while still offering powerful configurations for advanced practitioners. All features are Terraform-supported, allowing teams to manage the entire Cloudflare platform as code. With Security Analytics, customers gain a comprehensive view of all traffic, whether mitigated or not, and can run what-if scenarios to test new rules before deployment. This analytic capability ensures that businesses can dynamically adapt their security posture while maintaining high performance. To make security management even more seamless, our AI agent, powered by Natural Language Processing (NLP), helps users craft and refine custom rules and create powerful visualizations within our analytics engine.

Cloudflare: the clear choice for modern security

We are confident that Forrester’s report validates what our customers already know: Cloudflare is a leading WAF vendor, offering unmatched security, innovation, and ease of use. As threats continue to evolve, we remain committed to pushing the boundaries of web security to protect organizations worldwide.

If you’re looking for a powerful, scalable, and easy-to-manage web application firewall, Cloudflare is the best choice for securing your applications, APIs, and infrastructure.

Ready to enhance your security?

Learn more about Cloudflare WAF by creating an account today and see why Forrester has recognized us as a leader in the market. 

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. For more information, read about Forrester’s objectivity here .

Making Application Security simple with a new unified dashboard experience

Post Syndicated from Michael Tremante original https://blog.cloudflare.com/new-application-security-experience/

Over the years, we have framed our Application Security features against market-defined product groupings such as Web Application Firewall (WAF), DDoS Mitigation, Bot Management, API Security (API Shield), Client Side Security (Page Shield), and so forth. This has led to unnecessary artificial separation of what is, under the hood, a well-integrated single platform.

This separation, which has sometimes guided implementation decisions that have led to different systems being built for the same purpose, makes it harder for our users to adopt our features and implement a simple effective security posture for their environment.

Today, following user feedback and our drive to constantly innovate and simplify, we are going back to our roots by breaking these artificial product boundaries and revising our dashboard, so it highlights our strengths. The ultimate goal remains: to make it shockingly easy to secure your web assets.

Introducing a new unified Application Security experience.

If you are a Cloudflare Application Security user, log in to the dashboard today and try out the updated dashboard interface. To make the transition easier, you can toggle between old and new interfaces.


Security, simplified

Modern applications are built using a variety of technologies. Your app might include a web interface and a mobile version, both powered by an API, each with its own unique security requirements. As these technologies increasingly overlap, traditional security categories like Web, API, client-side, and bot protection start to feel artificial and disconnected when applied to real-world application security.

Consider scenarios where you want to secure your API endpoints with proper authentication, or prevent vulnerability scanners from probing for weaknesses. These tasks often require switching between multiple dashboards, creating different policies, and managing disjointed configurations. This fragmented approach not only complicates workflows but also increases the risk of overlooking a critical vulnerability. The result? A security posture that is harder to manage and potentially less effective.

When you zoom out, a pattern emerges. Whether it’s managing bots, securing APIs, or filtering web traffic, these solutions ultimately analyze incoming traffic looking for specific patterns, and the resulting signal is used to perform actions. The primary difference between these tools is the type of signal they generate, such as identifying bots, enforcing authorization, or flagging suspicious requests. 

At Cloudflare, we saw an opportunity to address this complexity by unifying our application security tools into a single platform with one cohesive UI. A unified approach means security practitioners no longer have to navigate multiple interfaces or piece together different security controls. With a single UI, you can configure policies more efficiently, detect threats faster, and maintain consistent protection across all aspects of your application. This simplicity doesn’t just save time, it ensures that your applications remain secure, even as threats evolve.

At the end of the day, attackers won’t care which product you’re using. But by unifying application security, we ensure they’ll have a much harder time finding a way in.

Many products, one common approach

To redefine the experience across Application Security products, we can start by defining three concepts that commonly apply:

  • Web traffic (HTTP/S), which can be generalised even further as “data”

  • Signals and detections, which provide intelligence about the traffic. Can be generalised as “metadata”

  • Security rules that let you combine any signal or detection (metadata), to block, challenge or otherwise perform an action on the web traffic (data)

We can diagram the above as follows:


Using these concepts, all the product groupings that we offer can be converted to different types of signals or detections. All else remains the same. And if we are able to run and generate our signals on all traffic separately from the rule system, therefore generating all the metadata, we get what we call always-on detections, another vital benefit of a single platform approach. Also note that the order in which we generate the signals becomes irrelevant.

In diagram form:


The benefits are twofold. First, problem spaces (such as account takeover or web attacks) become signal groupings, and therefore metadata that can be queried to answer questions about your environment.

For example, let’s take our Bot Management signal, the bot score, and our WAF Attack Score signal, the attack score. These already run as always-on detections at Cloudflare. By combining these two signals and filtering your traffic against them, you can gain powerful insights on who is accessing your application*:


Second, as everything is just a signal, the mitigation layer, driven by the optional rules, becomes detection agnostic. By providing the same signals as fields in a unified rule system, writing high level policies becomes a breeze. And as we said earlier, given the detection is always-on and fully separated from the mitigation rule system, exploring the data can be thought of as a powerful rule match preview engine. No need to deploy a rule in LOG mode to see what it matches!

We can now design a unified user experience that reflects Application Security as a single product.

* note: the example here is simplistic, and the use cases become a lot more powerful once you expand to the full set of potential signals that the platform can generate. Take, for example, our ability to detect file uploads. If you run a job application site, you may want to let crawlers access your site, but you may *not* want crawlers to submit applications on behalf of applicants. By combining the bot score signal with the file upload signal, you can ensure that rule is enforced.

Introducing a unified Application Security experience

As signals are always-on, the user journey can now start from our new overview page where we highlight security suggestions based on your traffic profile and configurations. Alternatively, you can jump straight into analytics where you can investigate your traffic using a combination of all available signals.

When a specific traffic pattern seems malicious, you can jump into the rule system to implement a security policy. As part of our new design, given the simplicity of the navigation, we also took advantage of the opportunity to introduce a new web assets page, where we highlight discovery and attack surface management details.

Of course, reaching the final design required multiple iterations and feedback sessions. To best understand the balance of maintaining flexibility in the UI whilst reducing complexity, we focused on customer tasks to be done and documenting their processes while trying to achieve their intended actions in the dashboard. Reducing navigation items and using clear naming was one element, but we quickly learned that the changes needed to support ease of use for tasks across the platform.

Here is the end result:


To recap, our new dashboard now includes:

  • One overview page where misconfigurations, risks, and suggestions are aggregated

  • Simplified and redesigned security analytics that surfaces security signals from all Application Security capabilities, so you can easily identify and act on any suspicious activity

  • A new web assets page, where you can manage your attack surfaces, helping improve detection relevance

  • A single Security Rules page that provides a unified interface to manage, prioritise, and customise all mitigation rules in your zone, significantly streamlining your security configuration

  • A new settings page where advanced control is based on security needs, not individual products

Let’s dive into each one.

Overview

With the unified security approach, the new overview page aggregates and prioritizes security suggestions across all your web assets, helping you maintain a healthy security posture. The suggestions span from detected (ongoing) attacks if there are any, to risks and misconfigurations to further solidify your protection. This becomes the daily starting point to manage your security posture.


Analytics

Security Analytics and Events have been redesigned to make it easier to analyze your traffic. Suspicious activity detected by Cloudflare is surfaced at the top of the page, allowing you to easily filter and review related traffic. From the Traffic Analytics Sampled Log view, further below in the page, new workflows enable you to take quick action to craft a custom rule or review related security events in context.


Web assets

Web assets is a new concept introduced to bridge your business goals with threat detection capabilities. A web asset is any endpoint, file, document, or other related entity that we normally would act on from a security perspective. Within our new web asset page, you will be able to explore all relevant discovered assets by our system.

With our unified security platform, we are able to rapidly build new use-case driven threat detections. For example, to block automated actions across your e-commerce website, you can instruct Cloudflare’s system to block any fraudulent signup attempts, while allowing verified crawlers to index your product pages. This is made possible by labelling your web assets, which, where possible, is automated by Cloudflare, and then using those labels to power threat detections to protect your assets.


Security rules

The unified Security rules interface brings all mitigation rule types — including WAF custom rules, rate limiting rules, API sequence rules, and client side rules — together in one centralized location, eliminating the need to navigate multiple dashboards.

The new page gives you visibility into how Cloudflare mitigates both incoming traffic and blocks potentially malicious client side resources from loading, making it easier to understand your security posture at a glance. The page allows you to create customised mitigation rules by combining any detection signals, such as Bot Score, Attack Score, or signals from Leaked Credential Checks, enabling precise control over how Cloudflare responds to potential threats.


Settings

Balancing guidance and flexibility was the key driver for designing the new Settings page. As much as Cloudflare guides you towards the optimal security posture through recommendations and alerts, customers that want the flexibility to proactively adjust these settings can find all of them here.


Experience it today

This is the first of many enhancements we plan to make to the Application Security experience in the coming months. To check out the new navigation, log in to the Cloudflare dashboard, click on “Security” and choose “Check it out” when you see the message below. You will still have the option of opting out, if you so prefer.

Let us know what you think either by sharing feedback in our community forum or by providing feedback directly in the dashboard (you will be prompted if you revert to the old design).

Watch on Cloudflare TV

Improved Bot Management flexibility and visibility with new high-precision heuristics

Post Syndicated from Curtis Lowder original https://blog.cloudflare.com/bots-heuristics/

Within the Cloudflare Application Security team, every machine learning model we use is underpinned by a rich set of static rules that serve as a ground truth and a baseline comparison for how our models are performing. These are called heuristics. Our Bot Management heuristics engine has served as an important part of eight global machine learning (ML) models, but we needed a more expressive engine to increase our accuracy. In this post, we’ll review how we solved this by moving our heuristics to the Cloudflare Ruleset Engine. Not only did this provide the platform we needed to write more nuanced rules, it made our platform simpler and safer, and provided Bot Management customers more flexibility and visibility into their bot traffic.   

Bot detection via simple heuristics

In Cloudflare’s bot detection, we build heuristics from attributes like software library fingerprints, HTTP request characteristics, and internal threat intelligence. Heuristics serve three separate purposes for bot detection: 

  1. Bot identification: If traffic matches a heuristic, we can identify the traffic as definitely automated traffic (with a bot score of 1) without the need of a machine learning model. 

  2. Train ML models: When traffic matches our heuristics, we create labelled datasets of bot traffic to train new models. We’ll use many different sources of labelled bot traffic to train a new model, but our heuristics datasets are one of the highest confidence datasets available to us.   

  3. Validate models: We benchmark any new model candidate’s performance against our heuristic detections (among many other checks) to make sure it meets a required level of accuracy.

While the existing heuristics engine has worked very well for us, as bots evolved we needed the flexibility to write increasingly complex rules. Unfortunately, such rules were not easily supported in the old engine. Customers have also been asking for more details about which specific heuristic caught a request, and for the flexibility to enforce different policies per heuristic ID.  We found that by building a new heuristics framework integrated into the Cloudflare Ruleset Engine, we could build a more flexible system to write rules and give Bot Management customers the granular explainability and control they were asking for. 

The need for more efficient, precise rules

In our previous heuristics engine, we wrote rules in Lua as part of our openresty-based reverse proxy. The Lua-based engine was limited to a very small number of characteristics in a rule because of the high engineering cost we observed with adding more complexity.

With Lua, we would write fairly simple logic to match on specific characteristics of a request (i.e. user agent). Creating new heuristics of an existing class was fairly straight forward. All we’d need to do is define another instance of the existing class in our database. However, if we observed malicious traffic that required more than two characteristics (as a simple example, user-agent and ASN) to identify, we’d need to create bespoke logic for detections. Because our Lua heuristics engine was bundled with the code that ran ML models and other important logic, all changes had to go through the same review and release process. If we identified malicious traffic that needed a new heuristic class, and we were also blocked by pending changes in the codebase, we’d be forced to either wait or rollback the changes. If we’re writing a new rule for an “under attack” scenario, every extra minute it takes to deploy a new rule can mean an unacceptable impact to our customer’s business. 

More critical than time to deploy is the complexity that the heuristics engine supports. The old heuristics engine only supported using specific request attributes when creating a new rule. As bots became more sophisticated, we found we had to reject an increasing number of new heuristic candidates because we weren’t able to write precise enough rules. For example, we found a Golang TLS fingerprint frequently used by bots and by a small number of corporate VPNs. We couldn’t block the bots without also stopping the legitimate VPN usage as well, because the old heuristics platform lacked the flexibility to quickly compile sufficiently nuanced rules. Luckily, we already had the perfect solution with Cloudflare Ruleset Engine. 

Our new heuristics engine

The Ruleset Engine is familiar to anyone who has written a WAF rule, Load Balancing rule, or Transform rule, just to name a few. For Bot Management, the Wireshark-inspired syntax allows us to quickly write heuristics with much greater flexibility to vastly improve accuracy. We can write a rule in YAML that includes arbitrary sub-conditions and inherit the same framework the WAF team uses to both ensure any new rule undergoes a rigorous testing process with the ability to rapidly release new rules to stop attacks in real-time. 

Writing heuristics on the Cloudflare Ruleset Engine allows our engineers and analysts to write new rules in an easy to understand YAML syntax. This is critical to supporting a rapid response in under attack scenarios, especially as we support greater rule complexity. Here’s a simple rule using the new engine, to detect empty user-agents restricted to a specific JA4 fingerprint (right), compared to the empty user-agent detection in the old Lua based system (left): 

Old

New

local _M = {}

local EmptyUserAgentHeuristic = {

   heuristic = {},

}

EmptyUserAgentHeuristic.__index = EmptyUserAgentHeuristic

--- Creates and returns empty user agent heuristic

-- @param params table contains parameters injected into EmptyUserAgentHeuristic

-- @return EmptyUserAgentHeuristic table

function _M.new(params)

   return setmetatable(params, EmptyUserAgentHeuristic)

end

--- Adds heuristic to be used for inference in `detect` method

-- @param heuristic schema.Heuristic table

function EmptyUserAgentHeuristic:add(heuristic)

   self.heuristic = heuristic

end

--- Detect runs empty user agent heuristic detection

-- @param ctx context of request

-- @return schema.Heuristic table on successful detection or nil otherwise

function EmptyUserAgentHeuristic:detect(ctx)

   local ua = ctx.user_agent

   if not ua or ua == '' then

      return self.heuristic

   end

end

return _M

ref: empty-user-agent

      description: Empty or missing

User-Agent header

      action: add_bot_detection

      action_parameters:

        active_mode: false

      expression: http.user_agent eq

"" and cf.bot_management.ja4 = "t13d1516h2_8daaf6152771_b186095e22b6"

The Golang heuristic that captured corporate proxy traffic as well (mentioned above) was one of the first to migrate to the new Ruleset engine. Before the migration, traffic matching on this heuristic had a false positive rate of 0.01%. While that sounds like a very small number, this means for every million bots we block, 100 real users saw a Cloudflare challenge page unnecessarily. At Cloudflare scale, even small issues can have real, negative impact.

When we analyzed the traffic caught by this heuristic rule in depth, we saw the vast majority of attack traffic came from a small number of abusive networks. After narrowing the definition of the heuristic to flag the Golang fingerprint only when it’s sourced by the abusive networks, the rule now has a false positive rate of 0.0001% (One out of 1 million).  Updating the heuristic to include the network context improved our accuracy, while still blocking millions of bots every week and giving us plenty of training data for our bot detection models. Because this heuristic is now more accurate, newer ML models make more accurate decisions on what’s a bot and what isn’t.

New visibility and flexibility for Bot Management customers 

While the new heuristics engine provides more accurate detections for all customers and a better experience for our analysts, moving to the Cloudflare Ruleset Engine also allows us to deliver new functionality for Enterprise Bot Management customers, specifically by offering more visibility. This new visibility is via a new field for Bot Management customers called Bot Detection IDs. Every heuristic we use includes a unique Bot Detection ID. These are visible to Bot Management customers in analytics, logs, and firewall events, and they can be used in the firewall to write precise rules for individual bots. 



Detections also include a specific tag describing the class of heuristic. Customers see these plotted over time in their analytics.


To illustrate how this data can help give customers visibility into why we blocked a request, here’s an example request flagged by Bot Management (with the IP address, ASN, and country changed):


Before, just seeing that our heuristics gave the request a score of 1 was not very helpful in understanding why it was flagged as a bot. Adding our Detection IDs to Firewall Events helps to paint a better picture for customers that we’ve identified this request as a bot because that traffic used an empty user-agent.


In addition to Analytics and Firewall Events, Bot Detection IDs are now available for Bot Management customers to use in Custom Rules, Rate Limiting Rules, Transform Rules, and Workers. 

Account takeover detection IDs

One way we’re focused on improving Bot Management for our customers is by surfacing more attack-specific detections. During Birthday Week, we launched Leaked Credentials Check for all customers so that security teams could help prevent account takeover (ATO) attacks by identifying accounts at risk due to leaked credentials. We’ve now added two more detections that can help Bot Management enterprise customers identify suspicious login activity via specific detection IDs that monitor login attempts and failures on the zone. These detection IDs are not currently affecting the bot score, but will begin to later in 2025. Already, they can help many customers detect more account takeover events now.

Detection ID 201326592 monitors traffic on a customer website and looks for an anomalous rise in login failures (usually associated with brute force attacks), and ID 201326593 looks for an anomalous rise in login attempts (usually associated with credential stuffing). 


Protect your applications

If you are a Bot Management customer, log in and head over to the Cloudflare dashboard and take a look in Security Analytics for bot detection IDs 201326592 and 201326593.

These will highlight ATO attempts targeting your site. If you spot anything suspicious, or would like to be protected against future attacks, create a rule that uses these detections to keep your application safe.

One platform to manage your company’s predictive security posture with Cloudflare

Post Syndicated from Zhiyuan Zheng original https://blog.cloudflare.com/cloudflare-security-posture-management/

In today’s fast-paced digital landscape, companies are managing an increasingly complex mix of environments — from SaaS applications and public cloud platforms to on-prem data centers and hybrid setups. This diverse infrastructure offers flexibility and scalability, but also opens up new attack surfaces.

To support both business continuity and security needs, “security must evolve from being reactive to predictive”. Maintaining a healthy security posture entails monitoring and strengthening your security defenses to identify risks, ensure compliance, and protect against evolving threats. With our newest capabilities, you can now use Cloudflare to achieve a healthy posture across your SaaS and web applications. This addresses any security team’s ultimate (daily) question: How well are our assets and documents protected?

A predictive security posture relies on the following key components:

  • Real-time discovery and inventory of all your assets and documents

  • Continuous asset-aware threat detection and risk assessment

  • Prioritised remediation suggestions to increase your protection

Today, we are sharing how we have built these key components across SaaS and web applications, and how you can use them to manage your business’s security posture.

Your security posture at a glance

Regardless of the applications you have connected to Cloudflare’s global network, Cloudflare actively scans for risks and misconfigurations associated with each one of them on a regular cadence. Identified risks and misconfigurations are surfaced in the dashboard under Security Center as insights.

Insights are grouped by their severity, type of risks, and corresponding Cloudflare solution, providing various angles for you to zoom in to what you want to focus on. When applicable, a one-click resolution is provided for selected insight types, such as setting minimum TLS version to 1.2 which is recommended by PCI DSS. This simplicity is highly appreciated by customers that are managing a growing set of assets being deployed across the organization.

To help shorten the time to resolution even further, we have recently added role-based access control (RBAC) to Security Insights in the Cloudflare dashboard. Now for individual security practitioners, they have access to a distilled view of the insights that are relevant for their role. A user with an administrator role (a CSO, for example) has access to, and visibility into, all insights.


In addition to account-wide Security Insights, we also provide posture overviews that are closer to the corresponding security configurations of your SaaS and web applications. Let’s dive into each of them.

Securing your SaaS applications

Without centralized posture management, SaaS applications can feel like the security wild west. They contain a wealth of sensitive information – files, databases, workspaces, designs, invoices, or anything your company needs to operate, but control is limited to the vendor’s settings, leaving you with less visibility and fewer customization options. Moreover, team members are constantly creating, updating, and deleting content that can cause configuration drift and data exposure, such as sharing files publicly, adding PII to non-compliant databases, or giving access to third party integrations. With Cloudflare, you have visibility across your SaaS application fleet in one dashboard.

Posture findings across your SaaS fleet

From the account-wide Security Insights, you can review insights for potential SaaS security issues:


You can choose to dig further with Cloud Access Security Broker (CASB) for a thorough review of the misconfigurations, risks, and failures to meet best practices across your SaaS fleet. You can identify a wealth of security information including, but not limited to:

  • Publicly available or externally shared files

  • Third-party applications with read or edit access

  • Unknown or anonymous user access

  • Databases with exposed credentials

  • Users without two-factor authentication

  • Inactive user accounts

You can also explore the Posture Findings page, which provides easy searching and navigation across documents that are stored within the SaaS applications.


Additionally, you can create policies to prevent configuration drift in your environment. Prevention-based policies help maintain a secure configuration and compliance standards, while reducing alert fatigue for Security Operations teams, and these policies can prevent the inappropriate movement or exfiltration of sensitive data. Unifying controls and visibility across environments makes it easier to lock down regulated data classes, maintain detailed audit trails via logs, and improve your security posture to reduce the risk of breaches.

How it works: new, real-time SaaS documents discovery

Delivering SaaS security posture information to our customers requires collecting vast amounts of data from a wide range of platforms. In order to ensure that all the documents living in your SaaS apps (files, designs, etc.) are secure, we need to collect information about their configuration — are they publicly shared, do third-party apps have access, is multi-factor authentication (MFA) enabled? 

We previously did this with crawlers, which would pull data from the SaaS APIs. However, we were plagued with rate limits from the SaaS vendors when working with larger datasets. This forced us to work in batches and ramp scanning up and down as the vendors permitted. This led to stale findings and would make remediation cumbersome and unclear – for example, Cloudflare would be reporting that a file is still shared publicly for a short period after the permissions were removed, leading to customer confusion.

To fix this, we upgraded our data collection pipeline to be dynamic and real-time, reacting to changes in your environment as they occur, whether it’s a new security finding, an updated asset, or a critical alert from a vendor. We started with our Microsoft asset discovery and posture findings, providing you real-time insight into your Microsoft Admin Center, OneDrive, Outlook, and SharePoint configurations. We will be rapidly expanding support to additional SaaS vendors going forward.

Listening for update events from Cloudflare Workers

Cloudflare Workers serve as the entry point for vendor webhooks, handling asset change notifications from external services. The workflow unfolds as follows:

  • Webhook listener: An initial Worker acts as the webhook listener, receiving asset change messages from vendors.

  • Data storage & queuing: Upon receiving a message, the Worker uploads the raw payload of the change notification to Cloudflare R2 for persistence, and publishes it to a Cloudflare Queue dedicated to raw asset changes.

  • Transformation Worker: A second Worker, bound as a consumer to the raw asset change queue, processes the incoming messages. This Worker transforms the raw vendor-specific data into a generic format suitable for CASB. The transformed data is then:

    • Stored in Cloudflare R2 for future reference.

    • Published on another Cloudflare Queue, designated for transformed messages.

CASB Processing: Consumers & Crawlers

Once the transformed messages reach the CASB layer, they undergo further processing:

  • Polling consumer: CASB has a consumer that polls the transformed message queue. Upon receiving a message, it determines the relevant handler required for processing.

  • Crawler execution: The handler then maps the message to an appropriate crawler, which interacts with the vendor API to fetch the most up-to-date asset details.

  • Data storage: The retrieved asset data is stored in the CASB database, ensuring it is accessible for security and compliance checks.

With this improvement, we are now processing 10 to 20 Microsoft updates per second, or 864,000 to 1.72 million updates daily, giving customers incredibly fast visibility into their environment. Look out for expansion to other SaaS vendors in the coming months. 

Securing your web applications

A unique challenge of securing web applications is that no one size fits all. An asset-aware posture management bridges the gap between a universal security solution and unique business needs, offering tailored recommendations for security teams to protect what matters.

Posture overview from attacks to threats and risks

Starting today, all Cloudflare customers have access to Security Overview, a new landing page customized for each of your onboarded domains. This page aggregates and prioritizes security suggestions across all your web applications:

  1. Any (ongoing) attacks detected that require immediate attention

  2. Disposition (mitigated, served by Cloudflare, served by origin) of all proxied traffic over the last 7 days

  3. Summary of currently active security modules that are detecting threats

  4. Suggestions of how to improve your security posture with a step-by-step guide

  5. And a glimpse of your most active and lately updated security rules


These tailored security suggestions are surfaced based on your traffic profile and business needs, which is made possible by discovering your proxied web assets.

Discovery of web assets

Many web applications, regardless of their industry or use case, require similar functionality: user identification, accepting payment information, etc. By discovering the assets serving this functionality, we can build and run targeted threat detection to protect them in depth.

As an example, bot traffic towards marketing pages versus login pages have different business impacts. Content scraping may be happening targeting your marketing materials, which you may or may not want to allow, while credential stuffing on your login page deserves immediate attention.

Web assets are described by a list of endpoints; and labelling each of them defines their business goals. A simple example can be POST requests to path /portal/login, which likely describes an API for user authentication. While the GET requests to path /portal/login denote the actual login webpage.

To describe business goals of endpoints, labels come into play. POST requests to the /portal/login endpoint serving end users and to the /api/admin/login endpoint used by employees can both can be labelled using the same cf-log-in managed label, letting Cloudflare know that usernames and passwords would be expected to be sent to these endpoints.


API Shield customers can already make use of endpoint labelling. In early Q2 2025, we are adding label discovery and suggestion capabilities, starting with three labels, cf-log-in, cf-sign-up, and cf-rss-feed. All other customers can manually add these labels to the saved endpoints. One example, explained below, is preventing disposable emails from being used during sign-ups. 

Always-on threat detection and risk assessment

Use-case driven threat detection

Customers told us that, with the growing excitement around generative AI, they need support to secure this new technology while not hindering innovation. Being able to discover LLM-powered services allows fine-tuning security controls that are relevant for this particular technology, such as inspecting prompts, limit prompting rates based on token usage, etc. In a separate Security Week blog post, we will share how we build Cloudflare Firewall for AI, and how you can easily protect your generative AI workloads.

Account fraud detection, which encompasses multiple attack vectors, is another key area that we are focusing on in 2025.

On many login and signup pages, a CAPTCHA solution is commonly used to only allow human beings through, assuming only bots perform undesirable actions. Put aside that most visual CAPTCHA puzzles can be easily solved by AI nowadays, such an approach cannot effectively solve the root cause of most account fraud vectors. For example, human beings using disposable emails to sign up single-use accounts to take advantage of signup promotions.

To solve this fraudulent sign up issue, a security rule currently under development could be deployed as below to block all attempts that use disposable emails as a user identifier, regardless of whether the requester was automated or not. All existing or future cf-log-in and cf-sign-up labelled endpoints are protected by this single rule, as they both require user identification.


Our fast expanding use-case driven threat detections are all running by default, from the first moment you onboarded your traffic to Cloudflare. The instant available detection results can be reviewed through security analytics, helping you make swift informed decisions.

API endpoint risk assessment

APIs have their own set of risks and vulnerabilities, and today Cloudflare is delivering seven new risk scans through API Posture Management. This new capability of API Shield helps reduce risk by identifying security issues and fixing them early, before APIs are attacked. Because APIs are typically made up of many different backend services, security teams need to pinpoint which backend service is vulnerable so that development teams may remediate the identified issues.

Our new API posture management risk scans do exactly that: users can quickly identify which API endpoints are at risk to a number of vulnerabilities, including sensitive data exposure, authentication status, Broken Object Level Authorization (BOLA) attacks, and more.

Authentication Posture is one risk scan you’ll see in the new system. We focused on it to start with because sensitive data is at risk when API authentication is assumed to be enforced but is actually broken. Authentication Posture helps customers identify authentication misconfigurations for APIs and alerts of their presence. This is achieved by scanning for successful requests against the API and noting their authentication status. API Shield scans traffic daily and labels API endpoints that have missing and mixed authentication for further review.

For customers that have configured session IDs in API Shield, you can find the new risk scan labels and authentication details per endpoint in API Shield. Security teams can take this detail to their development teams to fix the broken authentication.


We’re launching today with scans for authentication posture, sensitive data, underprotected APIs, BOLA attacks, and anomaly scanning for API performance across errors, latency, and response size.

Simplify maintaining a good security posture with Cloudflare

Achieving a good security posture in a fast-moving environment requires innovative solutions that can transform complexity into simplicity. Bringing together the ability to continuously assess threats and risks across both public and private IT environments through a single platform is our first step in supporting our customers’ efforts to maintain a healthy security posture.

To further enhance the relevance of security insights and suggestions provided and help you better prioritize your actions, we are looking into integrating Cloudflare’s global view of threat landscapes. With this, you gain additional perspectives, such as what the biggest threats to your industry are, and what attackers are targeting at the current moment. Stay tuned for more updates later this year.

If you haven’t done so yet, onboard your SaaS and web applications to Cloudflare today to gain instant insights into how to improve your business’s security posture.

Grinch Bots strike again: defending your holidays from cyber threats

Post Syndicated from Avi Jaisinghani original https://blog.cloudflare.com/grinch-bot-2024/

Grinch Bots are still stealing Christmas

Back in 2021, we covered the antics of Grinch Bots and how the combination of proposed regulation and technology could prevent these malicious programs from stealing holiday cheer.

Fast-forward to 2024 — the Stop Grinch Bots Act of 2021 has not passed, and bots are more active and powerful than ever, leaving businesses to fend off increasingly sophisticated attacks on their own. During Black Friday 2024, Cloudflare observed:

  • 29% of all traffic on Black Friday was Grinch Bots. Humans still accounted for the majority of all traffic, but bot traffic was up 4x from three years ago in absolute terms. 

  • 1% of traffic on Black Friday came from AI bots. The majority of it came from Claude, Meta, and Amazon. 71% of this traffic was given the green light to access the content requested. 

  • 63% of login attempts across our network on Black Friday were from bots. While this number is high, it was down a few percentage points compared to a month prior, indicating that more humans accessed their accounts and holiday deals. 

  • Human logins on e-commerce sites increased 7-8% compared to the previous month. 

These days, holiday shopping doesn’t start on Black Friday and stop on Cyber Monday. Instead, it stretches through Cyber Week and beyond, including flash sales, pre-orders, and various other promotions. While this provides consumers more opportunities to shop, it also creates more openings for Grinch Bots to wreak havoc.

Black Friday – Cyber Monday by the numbers

Black Friday and Cyber Monday in 2024 brought record-breaking shopping — and grinching. In addition to looking across our entire network, we also analyzed traffic patterns specifically on a cohort of e-commerce sites. 

Legitimate shoppers flocked to e-commerce sites, with requests reaching an astounding 405 billion on Black Friday, accounting for 81% of the day’s total traffic to e-commerce sites. Retailers reaped the rewards of their deals and advertising, seeing a 50% surge in shoppers week-over-week and a 61% increase compared to the previous month.

Unfortunately, Grinch Bots were equally active. Total e-commerce bot activity surged to 103 billion requests, representing up to 19% of all traffic to e-commerce sites. Nearly one in every five requests to an online store was not a real customer. That’s a lot of resources to waste on bogus traffic. Cyber Week was a battleground, with bots hoarding inventory, exploiting deals, and disrupting genuine shopping experiences.


The upside, if there is one, is that there was more human activity on e-commerce sites (81%) than observed on our network more broadly (71%). 

The Grinch Bot’s Modus Operandi

Cloudflare saw 4x more bot requests than what we observed in 2021. Being able to observe and score all this traffic at scale means we can help customers keep the grinches away. We also got to see patterns that help us better identify the concentration of these attacks: 

  • 19% of traffic on e-commerce sites was Grinch Bots

  • 1% of traffic to e-commerce sites was from AI Bots. 

  • 63% of login attempt requests across our network were from bots 

  • 22% of bot activity originated from residential proxy networks


What are all of these bots up to? 

AI bots

This year marked a breakthrough for AI-driven bots, agents, and models, with their impact spilling into Black Friday. AI bots went from zero to one, now making up 1% of all bot traffic on e-commerce sites. 

AI-driven bots generated 29 billion requests on Black Friday alone, with Meta-external, Claudebot, and Amazonbot leading the pack. Based on their owners, these bots are meant to crawl to augment training data sets for Llama, Claude, and Alexa respectively. 


We looked at e-commerce sites specifically to find out if these bots were treating all content equally. While Meta-External and Amazonbot were still in the Top 3 of AI bots reaching e-commerce sites, Bytedance’s Bytespider crawled the most shopping sites.


Account Takeover (ATO) bots

In addition to scraping, crawling, and shopping, bots also targeted customer accounts on Black Friday. We saw 14.1 billion requests from bots to /login endpoints, accounting for 63% of that day’s login attempts. 

While this number seems high, intuitively it makes sense, given that humans don’t log in to accounts every day, but bots definitely try to crack accounts every day. Interestingly, while humans only accounted for 36% of traffic to login pages on Black Friday, this number was up 7-8% compared to the prior month. This suggests that more shoppers logged in to capitalize on deals and discounts on Black Friday than in preceding weeks. Human logins peaked at around 40% of all traffic to login sites on the Monday before Thanksgiving, and again on Cyber Monday.  

Separately, we also saw a 37% increase in leaked passwords used in login requests compared to the prior month. During Birthday Week, we shared how 65% of internet users are at risk of ATO due to re-use of leaked passwords. This surge, coinciding with heightened human and bot traffic, underscores a troubling pattern: both humans and bots continue to depend on common and compromised passwords, amplifying security risks.


Proxy bots: Regardless of whether they’re crawling your content or hoarding your wares, 22% of bot traffic originated from residential proxy networks. This obfuscation makes these requests look like legitimate customers browsing from their homes rather than large cloud networks. The large pool of IP addresses and the diversity of networks poses a challenge to traditional bot defense mechanisms that rely on IP reputation and rate limiting. 

Moreover, the diversity of IP addresses enables the attackers to rotate through them indefinitely. This shrinks the window of opportunity for bot detection systems to effectively detect and stop the attacks. The use of residential proxies is a trend we have been tracking for months now and Black Friday traffic was within the range we’ve seen throughout this year.


If you’re using Cloudflare’s Bot Management, your site is already protected from these bots since we update our bot score based on these types of network fingerprints. In May 2024, we introduced our latest model optimized for detecting residential proxies. Early results show promising declines in this type of activity, indicating that bot operators may be reducing their reliance on residential proxies. 

The Christmas “Yule” log: how customers can protect themselves

35% of all traffic on Black Friday was Grinch Bots. To keep Grinch Bots at bay, businesses need year-round bot protection and proactive strategies tailored to the unique challenges of holiday shopping.

Here are 4 yules (aka “rules”) for the season:

(1) Block bots: 22% of bot traffic originated from residential proxy networks. Our bot management score automatically adjusts based on these network signals. Use our Bot Score in rules to challenge sensitive actions. 


(2) Monitor potential Account Takeover (ATO) attacks: Bots often test stolen credentials in the months leading up to Cyber Week to refine their strategies. Re-use of stolen credentials makes businesses even more vulnerable. Our account abuse detections help customers monitor login paths for leaked credentials and traffic anomalies.


Check out more examples of related rules you can create.

(3) Rate limit account and purchase paths: Apply rate-limiting best practices on critical application paths. These include limiting new account access/creation from previously seen IP addresses, and leveraging other network fingerprints, to help prevent promo code abuse and inventory hoarding, as well as identifying account takeover attempts through the application of detection IDs and leaked credential checks.

(4) Block AI bots abusing shopping features to maintain fair access for human users. If you’re using Cloudflare, you can quickly block all AI bots by enabling our automatic AI bot blocking feature.  


What to expect in 2025? 

Over the next year, e-commerce sites should expect to see more humans shopping for longer periods. As sale periods lengthen (like they did in 2024) we expect more peaks in human activity on e-commerce sites across November and December. This is great for consumers and great for merchants.

More AI bots and agents will be integrated into e-commerce journeys in 2025. AI bots will not only be crawling sites for training data, but will also integrate into the shopping experience. AI bots did not exist in 2021, but now make up 1% of all bot traffic. This is only the tip of the iceberg and their growth will explode in the next year. We expect this to pose new risks as bots mimic and act on behalf of humans.

More sophisticated automation through network, device, and cookie cycling will also become a bigger threat. Bot operators will continue to employ advanced evasion tactics like rotating devices, IP addresses, and cookies to bypass detection.

Grinch Bots are evolving, and regulation may be slowing, but businesses don’t have to face them alone. We remain resolute in our mission to help build a better Internet … and holiday shopping experience.

Even though the holiday season is closing out soon, bots are never on vacation. It’s never too late or too early to start protecting your customers and your business from grinches that work all year round.

Wishing you all happy holidays and a bot-free new year!


AWS Network Firewall Geographic IP Filtering launch

Post Syndicated from Prasanjit Tiwari original https://aws.amazon.com/blogs/security/aws-network-firewall-geographic-ip-filtering-launch/

AWS Network Firewall is a managed service that provides a convenient way to deploy essential network protections for your virtual private clouds (VPCs). In this blog post, we discuss Geographic IP Filtering, a new feature of Network Firewall that you can use to filter traffic based on geographic location and meet compliance requirements.

Customers with internet-facing applications are constantly in need of advanced security features to protect their applications from threat actors. This includes restricting traffic to and from their workloads in Amazon Web Services (AWS) to certain geographies because of security risk. Customers operating in highly regulated industries—such as banking, public sector, or insurance—might have specific security requirements that can be addressed by Geographic IP Filtering.

Previously, customers had to rely on third-party tools for retrieving an IP address list of specific countries and updating their firewall rules on a regular basis to meet applicable requirements. Now, with Geographic IP Filtering on Network Firewall, you can protect your application workloads based on the geolocation of the IP address. As new IP addresses are assigned by the Internet Assigned Numbers Authority (IANA), the Geographic IP database underneath Network Firewall is automatically updated so that the service can consistently filter inbound and outbound traffic from specific countries based on country codes. It supports IPv4 and IPv6 traffic.

Geographic IP Filtering is supported in all AWS Regions where Network Firewall is available today, including the AWS GovCloud (US) Regions.

Set up Geographic IP Filtering in Network Firewall

You can use Network Firewall to inspect network traffic and protect your VPCs using layer 3–7 rules (network layer to application layer of the OSI model). When traffic reaches Network Firewall, it will identify the location of the source and destination IP address from the Geographic IP database and block traffic if you have a firewall rule to block that location. You can choose to pass, drop, reject, or create an alert for traffic coming from or going to specific countries.

Before setting up Geographic IP Filtering rules, you need to deploy Network Firewall and attach a firewall policy. You can learn more about these steps in the Network Firewall Getting Started guide. You can configure Network Firewall Geographic IP Filtering in minutes using the AWS Management Console, AWS Command Line Interface (AWS CLI), AWS SDK, or the Network Firewall API.

To configure Geographic IP Filtering rules using the console:

  1. Sign in to the AWS Management Console and open the Amazon VPC console.
  2. In the navigation pane, under Network Firewall, choose Network Firewall rule groups.
  3. Choose Create rule group.
  4. In the Create rule group page, for the Rule group type, select Stateful rule group.
  5. For the Rule group format, select Standard stateful rule.
  6. For Rule evaluation order, select either Strict order (recommended) or Action order.
  7. Enter a name for the stateful rule group.
  8. For Capacity, enter the maximum capacity you want to allow for the stateful rule group.
  9. Under Standard stateful rules, for Geographic IP Filtering, select whether you want to Disable Geographic IP filtering, Match only selected countries, or Match all but selected countries.
  10. If you opt for Geographic IP Filtering, then select the Geographic IP traffic direction and Country codes that you want to filter the traffic for.
  11. Enter the appropriate values for Protocol, Source, Source port, Destination, and Destination port.
  12. For Action, select the action that you want Network Firewall to take when a packet matches the rule settings.

    Figure 1: Standard stateful rule

    Figure 1: Standard stateful rule

  13. Click Add rule and then review the rule to create the rule group.

    Figure 2: Geographic IP Filtering rules

    Figure 2: Geographic IP Filtering rules

Suricata compatibility

You can also use Geographic IP filtering with Suricata-compatible rule strings using the geoip keyword.

To create a Suricata compatible rule string:

  1. Follow steps 1 through 4 of the previous procedure.
  2. For the Rule group format, select Suricata compatible rule string.
  3. For Rule evaluation order, select either Strict order (recommended) or Action order.
  4. Enter a name for the stateful rule group.
  5. For Capacity, enter the maximum capacity you want to allow for the stateful rule group.
  6. Under Suricata compatible rule string, enter an appropriate string based on your source and destination along with the country code to filter traffic for. To use a Geographic IP filter, provide the geoip keyword, the filter type, and the country codes for the countries that you want to filter for.
  7. Suricata supports filtering for source and destination IPs. You can filter on either of these types by itself, by specifying dst or src. You can filter on the two types together with AND or OR logic, by specifying both or any.

For example, the following sample Suricata rule string drops traffic originating from Japan:

drop ip any any -> any any (msg:"Geographic IP from JP,Japan"; geoip:src,JP; sid:55555555; rev:1;)

Note that Suricata determines the location of requests using MaxMind GeoIP databases. MaxMind reports very high accuracy of their data at the country level, although accuracy varies according to factors such as country and type of IP. For more information about MaxMind, see MaxMind IP Geolocation.

If you think any of the Geographic IP data is incorrect, you can submit a correction request to MaxMind at MaxMind Correct GeoIP Data.

Logging Geographic IP Filtering

You can configure Network Firewall logging for your firewall’s stateful engine to get detailed information about the packet and any stateful rule action taken against the packet. There are no changes to the logging and monitoring mechanism with the introduction of the Geographic IP Filtering feature. However, by explicitly specifying the msg and metadata keywords, you can see additional geographic information in the alert logs that can help with troubleshooting. If these keywords aren’t specified in the Suricata rule string, the log event will not show any geographic information.

Suricata rule examples

In this section, you will find examples of Suricata rule strings to pass, block, reject, and alert on traffic to or from a specific country.

Example 1: To pass ingress traffic from a specific country

The following example passes ingress traffic from India.

Note: The rule evaluation order should be set to Strict for alert logs to be generated in this example. If the rule evaluation order is set to Action, then although the traffic will pass, alert logs will not be generated.

alert ip $EXTERNAL_NET any -> $HOME_NET any (msg:"Ingress traffic from IN allowed"; flow:to_server; geoip:src,IN; metadata:geo IN; sid:202409301;)
pass ip $EXTERNAL_NET any -> $HOME_NET any (msg:"Ingress traffic from IN allowed"; flow:to_server; geoip:src,IN; metadata:geo IN; sid:202409302;)

The following are the alert and flow logs for Example 1.

Alert logs:

{
    "firewall_name": "Test-NFW",
    "availability_zone": "eu-north-1a",
    "event_timestamp": "1731102856",
    "event": {
        "src_ip": "13.127.20.X",
        "src_port": 56630,
        "event_type": "alert",
        "alert": {
            "severity": 3,
            "signature_id": 202409301,
            "rev": 0,
            "metadata": {
                "geo": ["IN"]
            },
            "signature": "Ingress traffic from IN allowed",
            "action": "allowed",
            "category": ""
        },
        "flow_id": 234143298308779,
        "dest_ip": "172.31.2.4",
        "proto": "TCP",
        "verdict": {
            "action": "pass"
        },
        "dest_port": 80,
        "pkt_src": "geneve encapsulation",
        "timestamp": "2024-11-08T21:54:16.972019+0000",
        "direction": "to_server"
    }
}

Flow logs from source to destination:

{
    "firewall_name": "Test-NFW",
    "availability_zone": "eu-north-1a",
    "event_timestamp": "1731102918",
    "event": {
        "tcp": {
            "tcp_flags": "13",
            "syn": true,
            "fin": true,
            "ack": true
        },
        "app_proto": "unknown",
        "src_ip": "13.127.20.X",
        "src_port": 56630,
        "netflow": {
            "pkts": 4,
            "bytes": 216,
            "start": "2024-11-08T21:54:16.972019+0000",
            "end": "2024-11-08T21:54:17.263030+0000",
            "age": 1,
            "min_ttl": 112,
            "max_ttl": 112
        },
        "event_type": "netflow",
        "flow_id": 234143298308779,
        "dest_ip": "172.31.2.4",
        "proto": "TCP",
        "dest_port": 80,
        "timestamp": "2024-11-08T21:55:18.257416+0000"
    }
}

Flow logs from destination to source:

{
    "firewall_name": "Test-NFW",
    "availability_zone": "eu-north-1a",
    "event_timestamp": "1731102918",
    "event": {
        "tcp": {
            "tcp_flags": "13",
            "syn": true,
            "fin": true,
            "ack": true
        },
        "app_proto": "unknown",
        "src_ip": "172.31.2.4",
        "src_port": 80,
        "netflow": {
            "pkts": 2,
            "bytes": 112,
            "start": "2024-11-08T21:54:16.972019+0000",
            "end": "2024-11-08T21:54:17.263030+0000",
            "age": 1,
            "min_ttl": 126,
            "max_ttl": 126
        },
        "event_type": "netflow",
        "flow_id": 234143298308779,
        "dest_ip": "13.127.20.X",
        "proto": "TCP",
        "dest_port": 56630,
        "timestamp": "2024-11-08T21:55:18.257449+0000"
    }
}

Example 2: To block ingress traffic from a specific country

The following example blocks ingress traffic from Japan.

drop ip $EXTERNAL_NET any -> $HOME_NET any (msg:"Ingress traffic from JP blocked"; flow:to_server; geoip:any,JP; metadata:geo JP; sid:202409303;)

Example 3: To block ingress SSH traffic from a specific country

The following example blocks ingress SSH traffic from Russia.

drop ssh $EXTERNAL_NET any -> $HOME_NET any (msg:"Ingress SSH traffic from RU blocked"; flow:to_server; geoip:src,RU; metadata:geo RU; sid:202409304;)

Example 4: To reject egress TCP traffic to a specific country:

The following example rejects egress TCP traffic to Iran.

reject tcp $HOME_NET any -> $EXTERNAL_NET any (msg:"Egress traffic to IR rejected"; flow:to_server; geoip:dst,IR; metadata:geo IR; sid:202409305;)

Example 5: To alert on traffic originating from or destined to specific country

The following example alerts on traffic that originates from Venezuela.

alert ip any any -> any any (msg:"Geographic IP is from VE, Venezuela"; geoip:any,VE; sid: 202409306;)

Conclusion

You can use the new Geographic IP Filtering feature in AWS Network Firewall to enhance your security posture by controlling traffic based on geographic locations. In this post, you learned about the key concepts, configuration steps, and examples for implementing the Geographic IP Filtering feature in Network Firewall. By using this feature, businesses can protect their networks from potentially harmful traffic and control which geographic locations can interact with their infrastructure. As cyber threats continue to evolve, the Geographic IP Filtering feature serves as a vital tool for strengthening network security.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.
 

Prasanjit Tiwari
Prasanjit Tiwari

Prasanjit is a Cloud Support Engineer II based out of Virginia, USA. He has a Master of Science in Telecommunications Engineering from the University of Maryland. He is a WAF and Route 53 subject matter expert and enjoys working on networking and perimeter security services. He is enthusiastic about using innovative solutions to address customer challenges.
Dhiren Patel
Dhiren Patel

Dhiren is a Cloud Support Engineer-II based out of Virginia, USA. He has a Master of Science in Electrical and Computer Engineering from New York University. As a WAF and Route 53 subject matter expert, he specializes in AWS networking and security services. He’s passionate about helping customers solve their AWS issues and get the best cloud experience possible through AWS.

Threat modeling your generative AI workload to evaluate security risk

Post Syndicated from Danny Cortegaca original https://aws.amazon.com/blogs/security/threat-modeling-your-generative-ai-workload-to-evaluate-security-risk/

As generative AI models become increasingly integrated into business applications, it’s crucial to evaluate the potential security risks they introduce. At AWS re:Invent 2023, we presented on this topic, helping hundreds of customers maintain high-velocity decision-making for adopting new technologies securely. Customers who attended this session were able to better understand our recommended approach for qualifying security risk and maintaining a high security bar for the applications they build. In this blog post, we’ll revisit the key steps for conducting effective threat modeling on generative AI workloads, along with additional best practices and examples, including some typical deliverables and outcomes you should look for across each stage. Throughout this post we will link to specific examples that we created with the AWS Threat Composer tool. Threat Composer is an open source AWS tool you can use to document your threat model, available at no additional cost.

This post covers a practical approach for threat modeling a generative AI workload and assumes you know the basics of threat modeling. If you want to get an overview on threat modeling, we recommend that you check out this blog post. In addition, this post is part of a larger series on the security and compliance considerations of generative AI.

Why use threat modeling for generative AI?

Each new technology comes with its own learning curve when it comes to identifying and mitigating the unique security risks it presents. The adoption of generative AI into workloads is no different. These workloads, specifically the use of large language models (LLMs), introduce new security challenges because they can generate highly customized and non-deterministic outputs based on user prompts, which introduces the possibility for potential misuse or abuse. In addition, relies on access to large and customized data sets, often internal data sources which might contain sensitive information.

Although working with LLMs is a relatively new practice and has some unique and nuanced security risks and impacts, it’s crucial to remember that LLMs are only one portion of a larger workload. It’s important to apply the threat modeling approach to parts of the system, taking into account well-known threats such as injections or the compromise of credentials. Part 1 of the Securing generative AI AWS blog series, An introduction to the Generative AI Security Scoping Matrix, provides a great overview of what those nuances are, and how the risks differ depending on how you make use of LLMs in your organization.

The four stages of threat modeling for generative AI

As a quick refresher, threat modeling is a structured approach to identifying, understanding, addressing, and communicating the security risks in a given system or application. It is a fundamental element of the design phase that allows you to identify and implement appropriate mitigations and make fundamental security decisions as early as possible.

At AWS, threat modeling is a required input to initiating our Application Security (AppSec) process for the builder teams at AWS, and our builder teams get support from a Security Guardian to build threat models for their features or services.

A useful way of structuring the approach to threat modeling, created by expert Adam Shostack, involves answering four key questions. We’ll look into each one and how to apply them to your generative AI workload.

  1. What are we working on?
  2. What can go wrong?
  3. What are we going to do about it?
  4. Did we do a good enough job?

What are we working on?

This question aims to get a detailed understanding of your business context and application architecture. The detail that you’re looking for should already be captured as part of the comprehensive system documentation created by the builders of your generative AI solution. By starting from this documentation, you can streamline the threat modeling process and focus on identifying potential threats and vulnerabilities, rather than on re-creating foundational system knowledge.

Example outcomes or deliverables

At a minimum, builders should capture the key components of the solution, including data flows, assumptions, and design decisions. This lays the groundwork for identifying potential threats. Key elements to document are the following:

  • Data flow diagrams (DFDs) that clearly illustrate the critical data flows of the application, from request to response, detailing what happens at each component or “hop”
  • Well-articulated assumptions about how users are expected to interact with and ask questions of the system, or how the model will interact with other parts of the system. For example, in a RAG scenario where the model needs to retrieve data that is stored in other systems, how it will authenticate and translate that data into an appropriate response for the user
  • Documentation of key design decisions made by the business, including the rationale behind these decisions
  • Detailed business context about the application, such as whether it is considered a critical system, what types of data it handles (for example, confidential, high-integrity, high-availability), and the primary business concerns for the application (for example, data confidentiality, data integrity, system availability)

Figure 1 shows how Threat Composer allows you to input information about the application in the Application Information, Architecture, Dataflow, and Assumptions sections.

Figure 1: Threat composer dataflow diagram view for a generative AI chatbot example

Figure 1: Threat composer dataflow diagram view for a generative AI chatbot example

What can go wrong?

For this question, you identify possible threats to your application using the context and information you gathered for the previous question. To help you identify possible threats, make use of existing repositories of knowledge, especially those related to the new technologies you are adopting. These often have tangible examples that you can apply to your application. Useful resources are the OWASP top 10 for LLMs, MITRE ATLAS framework, and the AI Risk Repository. You can also use a structured framework such as STRIDE to aid you in your thinking. Use the information you received from the “What are we building?” question and apply the most relevant STRIDE categories to your thinking. For example, if your application hosts critical data that the business has no risk appetite for losing, then you might think about the various Information Disclosure threats first.

You can write and document these possible threats to your application in the form of threat statements. Threat statements are a way to maintain consistency and conciseness when you document your threat. At AWS, we adhere to a threat grammar which follows the syntax:

A [threat source] with [prerequisites] can [threat action] which leads to [threat impact], negatively impacting [impacted assets].

This threat grammar structure helps you to maintain consistency and allows you to iteratively write useful threat statements. As shown in Figure 2, Threat Composer provides you with this structure for new threat statements and includes examples to assist you.

Figure 2: Threat composer threat statement builder

Figure 2: Threat composer threat statement builder

Once you go through the process of creating threat statements, you will have a summary of “what can go wrong.” You can then define attack steps, as an analysis of “how it can go wrong.” It’s not always necessary to define attack steps for each threat statement because there are many ways a threat might actually happen. Going through the exercise of identifying and documenting a few different threat mechanisms can help to get specific mitigations that you can associate with each attack step for a more effective defense-in-depth approach.

Threat Composer gives you the ability to add additional metadata to your threat statements. Customers who have adopted this option into their workflows most commonly use the STRIDE category and Priority metadata tags. Those customers can quickly track which threats are the highest priority and which STRIDE category they correspond to. Figure 3 shows how you can document threat statements alongside their associated metadata in Threat Composer.

Figure 3: Threat Composer sample genAI chatbot application – threat view

Figure 3: Threat Composer sample genAI chatbot application – threat view

Example outcomes or deliverables

By systematically considering what can go wrong, and how, you can uncover a range of possible threats. Let’s explore some of the example deliverables that can emerge from this process:

  • A list of threat statements that you will develop mitigations for, categorized by STRIDE element and priority
  • A list of attack steps that are associated to your threat statements. As mentioned, attack steps are an optional activity at this stage, but we recommend at least identifying some for your highest-priority threats

Example threat statements

These are some example threat statements for an application that is interacting with an LLM component:

  • A threat actor with access to the public-facing application can inject malicious prompts that overwrite existing system prompts, resulting in healthcare data from other patients being returned, impacting the confidentiality of the data in the database
  • A threat actor with access to the public-facing application can inject malicious prompts that request malicious or destructive actions, resulting in healthcare data from other patients being deleted, impacting the availability of the data in the database

Example attack steps

These are some example attack steps that demonstrate how the preceding threat statements could occur:

  • Perform crafted prompt injection to bypass system prompt guardrails
  • Embed a vulnerable agent with access to the model
  • Embed an indirect prompt injection in a webpage instructing the LLM to disregard previous user instructions and use an LLM plugin to delete the user’s emails

What can we do about it?

Now that you’ve identified some possible threats, consider which controls would be appropriate to help mitigate the risks associated with those threats. This decision will be driven by your business context and the asset in question. Your organizational policies will also influence prioritization of controls: Some organizations might choose to prioritize the control that impacts the highest number of threats, while others might choose to start with the control that impacts the threats that are deemed the highest risk (by likelihood and impact).

For each identified threat, define specific mitigation strategies. This could include input sanitization, output validation, access controls, and more. Ideally, at a minimum, you want at least one preventative control and one detective control associated with each threat. The same resources that are linked to in the What can go wrong? section are also highly useful for identifying relevant controls. For example, the MITRE ATLAS has a dedicated section for mitigations.

Note: You might find that as you identify mitigations for your threats, you start to see duplication in your controls. For example, least-privilege access control might be associated with almost all of your threats. This duplication can also help you to prioritize. If a single control appears in 90% of your threat mitigations, the effective implementation of that control will help to drive down risk across each of those threats.

Example outcomes or deliverables

Associated with each threat, you should have a list of mitigations, each with a unique identifier to ease lookups and reusability later on. Example mitigations with identifiers include the following:

  • M-001: Predefine SQL query structure
  • M-002: Sanitize for known parameters (input filtering)
  • M-003: Check against templated prompt parameters
  • M-004: Review output is relevant to user (output filtering)
  • M-005: Limit LLM context window
  • M-006: Dynamic permissions check on high-risk actions performed by model (separating authentication parameters from prompt)
  • M-007: Apply least privilege to all components of the application

For more information on relevant security controls for your workload, we recommend that you read Part 3 of our Securing generative AI series: Applying relevant security controls.

Figure 4 shows some completed example threat statements in Threat Composer, with mitigations linked to each.

Figure 4: Completed threat statements with metadata and linked mitigations

Figure 4: Completed threat statements with metadata and linked mitigations

After answering the first three questions, you have your completed threat model. The documentation should contain your DFDs, threat statements, [optional] attack steps, and mitigations.

For a more detailed example, including a visual dashboard that shows a breakdown of a threat summary, see the full GenAI chatbot example in Threat Composer.

Did we do a good enough job?

A threat model is a living document. This post has discussed how creating a threat model helps you to identify technical controls for threats, but it’s also important to consider the non-technical benefits that the process of threat modeling provides.

For your final activity, you should validate both elements of the threat modeling activity.

Validate the effectiveness of the identified mitigation: Some of the mitigations you identify might be new, and some you might already have had in place. Regardless, it’s important to continuously test and verify that your security measures are working as intended. This could involve penetration testing or automated security scans. At AWS, threat models serve as inputs to automated test cases to be embedded in the pipeline. The threats defined are also used to define the scope of the penetration testing, to confirm whether those threats have been mitigated sufficiently.

Validate the effectiveness of the process: Threat modeling is fundamentally a human activity. It requires interaction across your business, builder teams, and security functions. Those closest to the creation and operations of the application should own the threat model document and revisit it often, with support from their security team (or Security Guardian equivalent). How often this is done will depend on your organizational policies and the criticality of the workload, though it is important to define triggers that will initiate a review of the threat model. Example triggers can include threat intelligence updates, new features that significantly change data flows, or new features that impact security-related aspects of the system (such as authentication or authorization, or logging). Validating your process periodically is especially important when you adopt new technologies because the threat landscape for these evolves faster than usual.

Performing a retrospective on the threat modeling process is also a good way to work through and discuss what worked well, what didn’t work well, and what changes you will commit to the next time the threat model is revisited.

Example outputs

These are some example outputs for this step of the process:

  • Automated test case definitions based on mitigations
  • A defined scope for penetration testing, and test cases based on threats
  • A living document for the threat model that is stored alongside application documentation (including a data flow diagram)
  • A retrospective overview, including lessons learned and feedback from the threat modeling participants, and what will be done next time to improve

Conclusion

In this blog post, we explored a practical and proactive approach to threat modeling for generative AI workloads. The key steps we covered provide a structured framework for conducting effective threat modeling, from understanding the business context and application architecture to identifying potential threats, defining mitigation strategies, and validating the overall effectiveness of the process.

By following this approach, organizations can better equip themselves to maintain a high security bar as they adopt generative AI technologies. The threat modeling process not only helps to mitigate known risks, but also fosters a culture of security-mindedness that is crucial for organizations to adopt. This can help your organization to unlock the full potential of these powerful technologies while maintaining the security and privacy of your systems and data.

Want to look deeper into additional areas of generative AI security? Check out the other posts in the Securing Generative AI series:

 

Danny Cortegaca

Danny Cortegaca

Danny is a Security Specialist Solutions Architect and is the Telco lead for AWS Industries. He joined AWS in 2021 and partners with some of the largest organizations in the world to help them navigate complex security and regulatory environments. He loves talking about application security with customers and has helped many adopt threat modeling into their practices.

Ana Malhotra

Ana Malhotra

Ana previously worked as a Security Specialist Solutions Architect at AWS and was the Healthcare and Life Sciences (HCLS) Security Lead for AWS Industry. She is no longer with AWS. As a former AWS Application Security Engineer, Ana loved talking all things AppSec, including people, process, and technology. In her free time, she enjoys tapping into her creative side with music and dance.

Kareem Abdol-Hamid

Kareem Abdol-Hamid

Kareem is a Senior Accelerated Compute Specialist for Startups. As an Accelerated Compute specialist, Kareem experiences novel challenges every day involving generative AI, High Performance Compute, and massively scaled workloads. In his free time, he plays piano and competes in the video game Street Fighter.

How to build a Security Guardians program to distribute security ownership

Post Syndicated from Mitch Beaumont original https://aws.amazon.com/blogs/security/how-to-build-your-own-security-guardians-program/

Welcome to the second post in our series on Security Guardians, a mechanism to distribute security ownership at Amazon Web Services (AWS) that trains, develops, and empowers builder teams to make security decisions about the software that they create. In the previous post, you learned the importance of building a culture of security ownership to scale security within your organization, and how AWS achieves this using the Security Guardians program. Since then, many customers have asked how they can build their own, similar program.

In this post, you will learn the steps to build your own Security Guardians program for your organization, including how to:

  • Set the vision, mission, and goals of your program
  • Identify developer teams that can pilot your new program
  • Define the expected behaviors for those teams
  • Develop training and create opportunities for career development to keep your teams engaged in the program

The guidance in this post is based on what we learned at AWS. Because every organization is different, the final version of the program you build is likely to look different from the one at AWS. Your program needs to reflect the current state of your organization’s culture of security and be designed to cultivate the security-related behaviors that are most important to your organization.

Security Guardians program mechanism

As discussed in the previous post, mechanisms form a key part of our business at AWS. Figure 1 demonstrates how a mechanism is a complete process, or virtuous cycle, that reinforces and improves itself as it operates. It takes controllable inputs and transforms them into ongoing outputs to address a recurring business challenge. In this case, the business challenge AWS faced was that security findings were being identified late in the development lifecycle, making it more expensive—in terms of time, money and effort—to remediate them. This led to bottlenecks in our security review process. The culture of security at AWS, specifically our culture of ownership, provides support to solve this challenge, but we needed the Security Guardians mechanism to actually do it.

Figure 1: AWS mechanism cycle

Figure 1: AWS mechanism cycle

With most mechanisms, driving adoption is difficult, especially when the mechanism requires human participation to succeed. This is also true in the case of Security Guardians, and you can use our experience to help you avoid some of the challenges and growing pains of driving adoption.

Getting everyone aligned

“If I had an hour to solve a problem and my life depended on the solution, I would spend the first 55 minutes determining the proper question to ask, for once I know the proper question, I could solve the problem in less than five minutes.” – Albert Einstein

Getting alignment for the need to distribute security expertise starts with deeply understanding what problems need to be addressed. For example:

  • Is product delivery velocity being negatively impacted by delays in the security review process?
  • What business goal or metric are these delays negatively impacting?
  • Where in the security review process are those delays occurring?
  • What factors are contributing to those delays?
  • Is it a lack of time, people, or skills?

Thoroughly understanding the specific problems and their root causes, as identified by answering those questions, allows you to evaluate whether distributing security ownership is the appropriate solution. This in turn makes it easier to gain alignment and buy-in across the organization for the chosen approach.

A component of a culture of security

Building a strong culture of security requires support from executive leadership to set the direction for the rest of the organization. Executive support makes it easier for product leaders to secure the resources and finances needed for a Security Guardians program to be successful. To align with your organization’s leaders, you can reflect on the goals of your leaders and how the Security Guardians program can be built to meet those goals.

For example, if your business goal is to ship products 25 percent faster, understand how a particular resourcing effort from Security Guardians is going to help your organization meet that goal. AWS benefited from the program with a 26.9 percent reduction in the time to review a new service or feature when a Security Guardian was involved.

Our experience is that it’s challenging to establish a Security Guardians program without executive support. If you’re struggling to identify a business leader to sponsor the program and provide insight on the business problem, your AWS account team—including your account manager or solutions architect—can help. If you’re a business leader or executive reading this post, consider becoming that sponsor yourself.

One step at a time

A step-by-step approach to implementing the Security Guardians program helps overcome organizational challenges and avoid common pitfalls that could lead to failure. These steps, shown in Figure 2, are:

  1. Set the vision
  2. Choose innovators
  3. Define behaviors
  4. Maintain interest
  5. Measure success

These steps support the activities that make a mechanism successful: adoption, inspection, and tools.

Figure 2: Steps for implementing a Security Guardians program

Figure 2: Steps for implementing a Security Guardians program

Set the vision

Now that you’ve identified the business problem or business goal, set the vision for the Security Guardians program by working backwards from this problem or goal to define the purpose of your program. For example, the vision of the AWS Security Guardians is “To nourish security ownership that consistently delights our customers with security-by-design throughout the development lifecycle.”

Craft an ambitious vision for your Security Guardians program. Think beyond easy wins and focus on bold, forward-thinking security outcomes for your organization. Make sure that each element of your vision aligns with a business problem or goal. The following table is an example of how the vision of the program is aligned with business goals:

Business goals Security outcome Long-term goals
Develop products faster and more efficiently. To improve developer agility while reducing security risk. Increase the number of threat models performed by Security Guardians (instead of by application security engineers). Over time, this goal could change to “increase the quality of threat models.”.

Decrease the average monthly security issue rate.

Train three new Security Guardians each quarter.

Reduce long-term security spend. To identify and mitigate security risk as early as possible.
Increase customer trust. To exceed customer security expectations by raising the security bar.

The next step is to define a clear mission that is supported with measurable goals. The mission and goals must be achievable and help to move the needle towards the long-term vision.

The final part is to name your program. We chose Security Guardians, like Marvel’s Guardians of the Galaxy. We’ve also heard customers using Security Champions, Security Advocates, Security Innovators, and Security Drivers. Have fun with it and make sure the name resonates with as many participants as possible.

After you’ve defined the vision, future state, mission, measurable goals, and name of the program, review them with your security and business leaders. It’s beneficial to include your innovators or Security Guardians who will be early adopters of the program in this review. In the next section, you’ll learn how to identify these innovators.

Choosing innovators

Just as you develop for and iterate with early adopters of the products you’re building, you should identify individuals and teams who will pilot the program with you. Before the AWS Security Guardians program, our application security engineering teams built relationships with product teams through security reviews.

This meant that they already knew which individuals within those product teams had an interest in security. This is where AWS started, but the success of your program isn’t dependent on whether you already know who these individuals are. Development teams will self-identify and nominate Security Guardians from their own teams. Figure 4 shows examples to help you get started understanding which development teams will be good early adopters for your program.

Figure 3: Example product teams for early program adopters

Figure 3: Example product teams for early program adopters

The examples in Figure 3 include:

Candidate A: Quick wins team

Early adopters typically share key traits, including existing security measures and a designated security role or team members with security expertise. Essentially, they already prioritize security at the team level.

Candidate B: High impact team

This is the team most impacted by the disparity between product development teams and security teams; the agility and time-related benefits of the Security Guardians program will be the highest for this team. For example, this team might be facing long delays in launching products because of the current security review process at your organization.

Candidate C: High risk team

This team owns a product that has a high security risk because of the nature of the product. This team will benefit the most from additional security scrutiny and from raising the security bar at your organization. For example, this team might be building a product that’s considered a critical asset, hosts sensitive data, or performs critical processes.

After you’ve identified one or more teams that could be good early adopters of the program, you need to identify at least one individual from each team to serve as the Security Guardian. Keep the vision and goals of your program in mind when selecting your Security Guardian. Your early Security Guardians should have at least the following characteristics:

  • Ability to exercise well-informed and decisive judgement
  • Maintain and showcase their knowledge
  • Not afraid to have their work be independently validated
  • Advocate for their security needs in internal discussions
  • Hold a high security bar
  • Thoughtful and assertive to make customer security a top priority on their team

In terms of time commitment, our experience is that each Security Guardian spends an average of 3.5 hours each month on activities such as answering general security questions, identifying security stories needed for sprints, diving deep into security related tasks and supporting security related tasks. Each application security review takes approximately 4 hours of effort.

The first post of this series contains even more details on the characteristics that make a good Security Guardian.

Defining behaviors

It’s important to set expectations on what behaviors you want Security Guardians, developers, and security teams to exhibit within the context of the program. These behaviors typically relate directly to the goals of the program. For example, if one of the goals is to increase the number of threat models created, then create threat modeling will be one of the defined behaviors. The behaviors need to be measurable with some flexibility for change as you improve the program.

At AWS, our Security Guardians have access to a runbook that lists the activities each Guardian should take when engaged as part of a review. With each of these activities understood, the program team will then make sure appropriate training is provided so that the Security Guardians are able to complete each of the activities. For example, AWS Security Guardians are asked to help develop threat models. To support this, the program team has developed and released training material to teach Security Guardians how to create a threat model.

With the defined behaviors, understand how the Security Guardian and product development team will engage with the security team. Although we’re clearly defining behaviors, the behaviors aren’t typically done in a silo for the successful launch of a secure product. At AWS, the Security Guardians and product developers engage with the security teams in key partnership areas. If you’re unsure of where to start in defining the behaviors of your program, Figure 4 shows an example of how teams interact at AWS, beginning with the creation of an initial threat model and going through review, remediation, and testing. Consider creating your own version of the model to help define the behaviors and key partnership areas at your organization.

Figure 4: Example behaviors and partnership areas at AWS

Figure 4: Example behaviors and partnership areas at AWS

In the example of a threat model review, the Guardian and the central security team will jointly create and review the threat model. Specific activity examples include reviewing threats that have no documented mitigations and discussing additional threats that haven’t yet been considered.

As part of encouraging a culture of ownership, AWS recommends allowing Security Guardians to influence the role within a set of boundaries. An example of this is allowing the Security Guardians to be a part of recurring reviews of the program growth metrics, actively collecting their feedback, and encouraging them to host their own training sessions. Active Security Guardians are key to the success of the program and allowing them to influence the program will give them a sense of ownership and inclusion.

Maintaining interest

It’s important to not lose sight that a program like the AWS Security Guardians program is supported by volunteers. Most of your Security Guardians will be product developers who already have a full-time job developing products for your organization. The time and effort to find and onboard new Security Guardians will have a low return on investment if they stop engaging because the program owners didn’t keep them engaged. Keeping Security Guardians is just as important as finding them.

At AWS, we invest time to understand how to build trust with Security Guardians and provide value by working backwards from their wants and needs. Some Security Guardians joined the program to learn new skills and for career growth opportunities. AWS built training programs that were designed for Security Guardians and provide metrics that are used to document their impact to their managers and leaders.

AWS Security Guardians constantly tell us that they value recognition of their contributions by leadership. We work to build mechanisms to continuously surface the great work of our Security Guardians. We also recognize the contributions Security Guardians make through awards, gifts, and other incentives. For example, each quarter, the AWS Security Guardians team sends out a newsletter to senior leaders of the organization. This communication identifies the Guardians within their organization and highlights their contributions, including the number and impact of reviews they’ve completed.

Another way that AWS recognizes the contributions of our Security Guardians is through the Guardians Belt Program. The Guardians Belt Program is designed to recognize Security Guardians for their contributions and support them as they work to advance their security skills and expand their scope of impact. Security Guardians earn Black, Green, Yellow, and White belts with each belt corresponding to significant accomplishments that require consistent commitment to raising the security bar.

To make sure that Security Guardians value the program, your organization should provide and actively facilitate benefits. The benefits must be accessible without requiring additional time or effort from the Security Guardians, promoting immediate and direct gains. Consider the following examples of benefits to maintain Security Guardian interest and support:

  • Specialized training: Workshops, game days, challenges and contests.
  • Impact opportunities: Ability to impact multiple products by working with other teams in the organization, ability to help define patterns, best practices, and automation for the program.
  • Community: Collaborate, connect, share and learn from experts and individuals with similar interests.
  • Ownership opportunities: Ability to accelerate certain steps in the process.
  • Leadership opportunities: Active involvement in recurring program or business reviews.

The best ways to maintain interest are determined by the culture of your organization. What does your organization value the most, and how will the program provide that to your Security Guardians? Sometimes, the best way to answer these questions is to ask your early or potential Security Guardians.

Measuring success

The final step of building a successful Security Guardians program is to measure program success. Measuring success is equivalent to the inspection step from Figure 1. This verifies that your desired outcomes are being achieved and provides a jumping off point for iteration. Measuring success also gives you the opportunity to audit the output or results of the Security Guardians program and perform corrections and improvements.

Earlier in this post, we covered identifying the business problem and creating the vision and measurable goals for your Security Guardians program. Example metrics include:

  • Average time to release features
  • Average number of security issues per team
  • Average time spent by Security Guardians and builders doing security work
  • Percentage of Security Guardians who have taken required and non-required training

Measuring success includes steps to collect feedback and tune the program over time, shown in Figure 5.

Figure 5: Feedback and tuning steps for Security Guardians program.

Figure 5: Feedback and tuning steps for Security Guardians program.

The cycle to gather feedback and tune the program includes:

  1. Report on metrics
  2. Communicate wins
  3. Measure outcome and cycle time
  4. Identify trends
  5. Review goals

Gathering feedback from Security Guardians is as important as providing feedback to them. One of the ways AWS collects feedback from Security Guardians is through an annual survey that collects feedback on their experiences of program and tooling. To help both builders and Security Guardians improve over time, our security review tooling captures feedback from security engineers on the inputs from Security Guardians. Combined, the data gathered through these surveys helps our security ownership mechanism reinforce and improve itself over time.

Figure 6 summarizes the steps that you can take to develop your program.

Figure 6: Security Guardians program steps

Figure 6: Security Guardians program steps

The broad steps to develop a program include:

  • Set the vision: Set your vision for the program and metrics for success. Get sponsorship from leadership. Choose a name for your program.
  • Choose innovators: Identify innovators who have a passion for security and foster a community with continuous knowledge sharing.
  • Define behaviors: Redefine your RACI (responsible, accountable, consulted, informed) and be clear on expectations from your security advocates.
  • Maintain interest: Provide clear training and learning paths and opportunities for career advancement.
  • Measure success: Gather feedback and measure the program’s effectiveness.

Conclusion

This post and the previous post covered numerous concepts, considerations, and ideas, including:

  • The initial intention of the Security Guardians program is to focus on training developers in product teams. This improves early security-focused design thinking.
  • An alternative approach is to embed or align security engineers directly with product development teams. This can be more effective in organizations where reporting structures and accountability are key considerations.
  • Some organizations draw Security Guardians from all job types. The program can also be used to focus on uplifting developers and broad security culture.
  • You must regularly inspect the outcomes delivered by the Security Guardians program and use the information to make incremental improvements as the program matures.

For additional support building a Security Guardians program, contact your AWS account representative and they will get you in touch with a specialist who can help you develop your program.

 
If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.
 

Mitch Beaumont
Mitch Beaumont

Mitch is a Principal Solutions Architect for Amazon Web Services based in Sydney, Australia. Mitch works with some of Australia’s largest financial services customers, helping them to continually raise the security bar for the products and features that they build and ship. Outside of work, Mitch enjoys spending time with his family, photography, and surfing.
Ana Malhotra
Ana Malhotra

Ana previously worked as a Security Specialist Solutions Architect and was the Healthcare and Life Sciences (HCLS) Security Lead for AWS Industry, based in Seattle, Washington. As a former AWS Application Security Engineer, during her time with AWS Industry, Ana loved talking all things AppSec, including people, process, and technology. In her free time, she enjoys tapping into her creative side with music and dance.

How Cloudflare is helping domain owners with the upcoming Entrust CA distrust by Chrome and Mozilla

Post Syndicated from Dina Kozlov original https://blog.cloudflare.com/how-cloudflare-is-helping-domain-owners-with-the-upcoming-entrust-ca

Chrome and Mozilla announced that they will stop trusting Entrust’s public TLS certificates issued after November 12, 2024 and December 1, 2024, respectively. This decision stems from concerns related to Entrust’s ability to meet the CA/Browser Forum’s requirements for a publicly trusted certificate authority (CA). To prevent Entrust customers from being impacted by this change, Entrust has announced that they are partnering with SSL.com, a publicly trusted CA, and will be issuing certs from SSL.com’s roots to ensure that they can continue to provide their customers with certificates that are trusted by Chrome and Mozilla. 

We’re excited to announce that we’re going to be adding SSL.com as a certificate authority that Cloudflare customers can use. This means that Cloudflare customers that are currently relying on Entrust as a CA and uploading their certificate manually to Cloudflare will now be able to rely on Cloudflare’s certificate management pipeline for automatic issuance and renewal of SSL.com certificates. 

CA distrust: responsibilities, repercussions, and responses

With great power comes great responsibility
Every publicly trusted certificate authority (CA) is responsible for maintaining a high standard of security and compliance to ensure that the certificates they issue are trustworthy. The security of millions of websites and applications relies on a CA’s commitment to these standards, which are set by the CA/Browser Forum, the governing body that defines the baseline requirements for certificate authorities. These standards include rules regarding certificate issuance, validation, and revocation, all designed to secure the data transferred over the Internet. 

However, as with all complex software systems, it’s inevitable that bugs or issues may arise, leading to the mis-issuance of certificates. Improperly issued certificates pose a significant risk to Internet security, as they can be exploited by malicious actors to impersonate legitimate websites and intercept sensitive data. 

To mitigate such risk, publicly trusted CAs are required to communicate issues as soon as they are discovered, so that domain owners can replace the compromised certificates immediately. Once the issue is communicated, CAs must revoke the mis-issued certificates within 5 days to signal to browsers and clients that the compromised certificate should no longer be trusted. This level of transparency and urgency around the revocation process is essential for minimizing the risk posed by compromised certificates. 

Why Chrome and Mozilla are distrusting Entrust
The decision made by Chrome and Mozilla to distrust Entrust’s public TLS certificates stems from concerns regarding Entrust’s incident response and remediation process. In several instances, Entrust failed to report critical issues and did not revoke certificates in a timely manner. The pattern of delayed action has eroded the browsers’ confidence in Entrust’s ability to act quickly and transparently, which is crucial for maintaining trust as a CA. 

Google and Mozilla cited the ongoing lack of transparency and urgency in addressing mis-issuances as the primary reason for their distrust decision. Google specifically pointed out that over the past 6 years, Entrust has shown a “pattern of compliance failures” and failed to make the “tangible, measurable progress” necessary to restore trust. Mozilla echoed these concerns, emphasizing the importance of holding Entrust accountable to ensure the integrity and security of the public Internet. 

Entrust’s response to the distrust announcement 
In response to the distrust announcement from Chrome and Mozilla, Entrust has taken proactive steps to ensure continuity for their customers. To prevent service disruption, Entrust has announced that they are partnering with SSL.com, a CA that’s trusted by all major browsers, including Chrome and Mozilla, to issue certificates for their customers. By issuing certificates from SSL.com’s roots, Entrust aims to provide a seamless transition for their customers, ensuring that they can continue to obtain certificates that are recognized and trusted by the browsers their users rely on. 

In addition to their partnership with SSL.com, Entrust stated that they are working on a number of improvements, including changes to their organizational structure, revisions to their incident response process and policies, and a push towards automation to ensure compliant certificate issuances. 

How Cloudflare can help Entrust customers 

Now available: SSL.com as a certificate authority for Advanced Certificate Manager and SSL for SaaS certificates
We’re excited to announce that customers using Advanced Certificate Manager will now be able to select SSL.com as a certificate authority for Advanced certificates and Total TLS certificates. Once the certificate is issued, Cloudflare will handle all future renewals on your behalf. 

By default, Cloudflare will issue SSL.com certificates with a 90 day validity period. However, customers using Advanced Certificate Manager will have the option to set a custom validity period (14, 30, or 90 days) for their SSL.com certificates. In addition, Enterprise customers will have the option to obtain 1-year SSL.com certificates. Every SSL.com certificate order will include 1 RSA and 1 ECDSA certificate.

Note: We are gradually rolling this out and customers should see the CA become available to them through the end of September and into October. 

If you’re using Cloudflare as your DNS provider, there are no additional steps for you to take to get the certificate issued. Cloudflare will validate the ownership of the domain on your behalf to get your SSL.com certificate issued and renewed. 

If you’re using an external DNS provider and have wildcard hostnames on your certificates, DNS based validation will need to be used, which means that you’ll need to add TXT DCV tokens at your DNS provider in order to get the certificate issued. With SSL.com, two tokens are returned for every hostname on the certificate. This is because SSL.com uses different tokens for the RSA and ECDSA certificates. To reduce the overhead around certificate management, we recommend setting up DCV Delegation to allow Cloudflare to place domain control validation (DCV) tokens on your behalf. Once DCV Delegation is set up, Cloudflare will automatically issue, renew, and deploy all future certificates for you. 

Advanced Certificates: selecting SSL.com as a CA through the UI or API
Customers can select SSL.com as a CA through the UI or through the Advanced Certificate API endpoint by specifying “ssl_com” in the certificate_authority parameter. 

If you’d like to use SSL.com as a CA for an advanced certificate, you can select “SSL.com” as your CA when creating a new Advanced certificate order. 


If you’d like to use SSL.com as a CA for all of your certificates, we recommend setting your Total TLS CA to SSL.com. This will issue an individual certificate for each of your proxied hostname from the CA. 

Note: Total TLS is a feature that’s only available to customers that are using Cloudflare as their DNS provider. 


SSL for SaaS: selecting SSL.com as a CA through the UI or API
Enterprise customers can select SSL.com as a CA through the custom hostname creation UI or through the Custom Hostnames API endpoint by specifying “ssl_com” in the certificate_authority parameter. 

All custom hostname certificates issued from SSL.com will have a 90 day validity period. If you have wildcard support enabled for custom hostnames, we recommend using DCV Delegation to ensure that all certificate issuances and renewals are automatic.  

Our recommendation if you’re using Entrust as a certificate authority 

Cloudflare customers that use Entrust as their CA are required to manually handle all certificate issuances and renewals. Since Cloudflare does not directly integrate with Entrust, customers have to get their certificates issued directly from the CA and upload them to Cloudflare as custom certificates. Once these certificates come up for renewal, customers have to repeat this manual process and upload the renewed certificates to Cloudflare before the expiration date. 

Manually managing your certificate’s lifecycle is a time-consuming and error prone process. With certificate lifetimes decreasing from 1 year to 90 days, this cycle needs to be repeated more frequently by the domain owner. 

As Entrust transitions to issuing certificates from SSL.com roots, this manual management process will remain unless customers switch to Cloudflare’s managed certificate pipeline. By making this switch, you can continue to receive SSL.com certificates without the hassle of manual management — Cloudflare will handle all issuances and renewals for you!

In early October, we will be reaching out to customers who have uploaded Entrust certificates to Cloudflare to recommend migrating to our managed pipeline for SSL.com certificate issuances, simplifying your certificate management process. 

If you’re ready to make the transition today, simply go to the SSL/TLS tab in your Cloudflare dashboard, click “Order Advanced Certificate”, and select “SSL.com” as your certificate authority. Once your new SSL.com certificate is issued, you can either remove your Entrust certificate or simply let it expire. Cloudflare will seamlessly transition to serving the managed SSL.com certificate before the Entrust certificate expires, ensuring zero downtime during the switch. 

New whitepaper available: Building security from the ground up with Secure by Design

Post Syndicated from Bertram Dorn original https://aws.amazon.com/blogs/security/new-whitepaper-available-building-security-from-the-ground-up-with-secure-by-design/

Developing secure products and services is imperative for organizations that are looking to strengthen operational resilience and build customer trust. However, system design often prioritizes performance, functionality, and user experience over security. This approach can lead to vulnerabilities across the supply chain.

As security threats continue to evolve, the concept of Secure by Design (SbD) is gaining importance in the effort to mitigate vulnerabilities early, minimize risks, and recognize security as a core business requirement. We’re excited to share a whitepaper we recently authored with SANS Institute called Building Security from the Ground up with Secure by Design, which addresses SbD strategy and explores the effects of SbD implementations.

The whitepaper contains context and analysis that can help you take a proactive approach to product development that facilitates foundational security. Key considerations include the following:

  • Integrating SbD into the software development lifecycle (SDLC)
  • Supporting SbD with automation
  • Reinforcing defense-in-depth
  • Applying SbD to artificial intelligence (AI)
  • Identifying threats in the design phase with threat modeling
  • Using SbD to simplify compliance with requirements and standards
  • Planning for the short and long term
  • Establishing a culture of security

While the journey to a Secure by Design approach is an iterative process that is different for every organization, the whitepaper details five key action items that can help set you on the right path. We encourage you to download the whitepaper and gain insight into how you can build secure products with a multi-layered strategy that meaningfully improves your technical and business outcomes. We look forward to your feedback and to continuing the journey together.

Download Building Security from the Ground up with Secure by Design.

 
If you have feedback about this post, submit comments in the Comments section below.

Bertram Dorn
Bertram Dorn

Bertram is a Principal within the Office of the CISO at AWS, based in Munich, Germany. He helps internal and external AWS customers and partners navigate AWS security-related topics. He has over 30 years of experience in the technology industry, with a focus on security, networking, storage, and database technologies. When not helping customers, Bertram spends time working on his solo piano and multimedia performances.
Paul Vixie
Paul Vixie

Paul is a VP and Distinguished Engineer who joined AWS Security after a 29-year career as the founder and CEO of five startup companies covering the fields of DNS, anti-spam, internet exchange, internet carriage and hosting, and internet security. He earned his PhD in Computer Science from Keio University in 2011, and was inducted into the Internet Hall of Fame in 2014. Paul is also known as an author of open source software, including Cron. As a VP, Distinguished Engineer, and Deputy CISO at AWS, Paul and his team in the Office of the CISO use leadership and technical expertise to provide guidance and collaboration on the development and implementation of advanced security strategies and risk management.

Application Security report: 2024 update

Post Syndicated from Michael Tremante original https://blog.cloudflare.com/application-security-report-2024-update


Over the last twelve months, the Internet security landscape has changed dramatically. Geopolitical uncertainty, coupled with an active 2024 voting season in many countries across the world, has led to a substantial increase in malicious traffic activity across the Internet. In this report, we take a look at Cloudflare’s perspective on Internet application security.

This report is the fourth edition of our Application Security Report and is an official update to our Q2 2023 report. New in this report is a section focused on client-side security within the context of web applications.

Throughout the report we discuss various insights. From a global standpoint, mitigated traffic across the whole network now averages 7%, and WAF and Bot mitigations are the source of over half of that. While DDoS attacks remain the number one attack vector used against web applications, targeted CVE attacks are also worth keeping an eye on, as we have seen exploits as fast as 22 minutes after a proof of concept was released.

Focusing on bots, about a third of all traffic we observe is automated, and of that, the vast majority (93%) is not generated by bots in Cloudflare’s verified list and is potentially malicious.

API traffic is also still growing, now accounting for 60% of all traffic, and maybe more concerning, is that organizations have up to a quarter of their API endpoints not accounted for.

We also touch on client side security and the proliferation of third-party integrations in web applications. On average, enterprise sites integrate 47 third-party endpoints according to Page Shield data.

It is also worth mentioning that since the last report, our network, from which we gather the data and insights, is bigger and faster: we are now processing an average of 57 million HTTP requests/second (+23.9% YoY) and 77 million at peak (+22.2% YoY). From a DNS perspective, we are handling 35 million DNS queries per second (+40% YoY). This is the sum of authoritative and resolver requests served by our infrastructure.

Maybe even more noteworthy, is that, focusing on HTTP requests only, in Q1 2024 Cloudflare blocked an average of 209 billion cyber threats each day (+86.6% YoY). That is a substantial increase in relative terms compared to the same time last year.

As usual, before we dive in, we need to define our terms.

Definitions

Throughout this report, we will refer to the following terms:

  • Mitigated traffic: any eyeball HTTP* request that had a “terminating” action applied to it by the Cloudflare platform. These include the following actions: BLOCK, CHALLENGE, JS_CHALLENGE and MANAGED_CHALLENGE. This does not include requests that had the following actions applied: LOG, SKIP, ALLOW. They also accounted for a relatively small percentage of requests. Additionally, we improved our calculation regarding the CHALLENGE type actions to ensure that only unsolved challenges are counted as mitigated. A detailed description of actions can be found in our developer documentation. This has not changed from last year’s report.
  • Bot traffic/automated traffic: any HTTP* request identified by Cloudflare’s Bot Management system as being generated by a bot. This includes requests with a bot score between 1 and 29 inclusive. This has not changed from last year’s report.
  • API traffic: any HTTP* request with a response content type of XML or JSON. Where the response content type is not available, such as for mitigated requests, the equivalent Accept content type (specified by the user agent) is used instead. In this latter case, API traffic won’t be fully accounted for, but it still provides a good representation for the purposes of gaining insights. This has not changed from last year’s report.

Unless otherwise stated, the time frame evaluated in this post is the period from April 1, 2023, through March 31, 2024, inclusive.

Finally, please note that the data is calculated based only on traffic observed across the Cloudflare network and does not necessarily represent overall HTTP traffic patterns across the Internet.

*When referring to HTTP traffic we mean both HTTP and HTTPS.

Global traffic insights

Average mitigated daily traffic increases to nearly 7%

Compared to the prior 12-month period, Cloudflare mitigated a higher percentage of application layer traffic and layer 7 (L7) DDoS attacks between Q2 2023 and Q1 2024, growing from 6% to 6.8%.

Figure 1: Percent of mitigated HTTP traffic increasing over the last 12 months

During large global attack events, we can observe spikes of mitigated traffic approaching 12% of all HTTP traffic. These are much larger spikes than we have ever observed across our entire network.

WAF and Bot mitigations accounted for 53.9% of all mitigated traffic

As the Cloudflare platform continues to expose additional signals to identify potentially malicious traffic, customers have been actively using these signals in WAF Custom Rules to improve their security posture. Example signals include our WAF Attack Score, which identifies malicious payloads, and our Bot Score, which identifies automated traffic.

After WAF and Bot mitigations, HTTP DDoS rules are the second-largest contributor to mitigated traffic. IP reputation, that uses our IP threat score to block traffic, and access rules, which are simply IP and country blocks, follow in third and fourth place.

Figure 2: Mitigated traffic by Cloudflare product group

CVEs exploited as fast as 22 minutes after proof-of-concept published

Zero-day exploits (also called zero-day threats) are increasing, as is the speed of weaponization of disclosed CVEs. In 2023, 97 zero-days were exploited in the wild, and that’s along with a 15% increase of disclosed CVEs between 2022 and 2023.

Looking at CVE exploitation attempts against customers, Cloudflare mostly observed scanning activity, followed by command injections, and some exploitation attempts of vulnerabilities that had PoCs available online, including Apache CVE-2023-50164 and CVE-2022-33891, Coldfusion CVE-2023-29298 CVE-2023-38203 and CVE-2023-26360, and MobileIron CVE-2023-35082.

This trend in CVE exploitation attempt activity indicates that attackers are going for the easiest targets first, and likely having success in some instances given the continued activity around old vulnerabilities.

As just one example, Cloudflare observed exploitation attempts of CVE-2024-27198 (JetBrains TeamCity authentication bypass) at 19:45 UTC on March 4, just 22 minutes after proof-of-concept code was published.

Figure 3: JetBrains TeamCity authentication bypass timeline

The speed of exploitation of disclosed CVEs is often quicker than the speed at which humans can create WAF rules or create and deploy patches to mitigate attacks. This also applies to our own internal security analyst team that maintains the WAF Managed Ruleset, which has led us to combine the human written signatures with an ML-based approach to achieve the best balance between low false positives and speed of response.

CVE exploitation campaigns from specific threat actors are clearly visible when we focus on a subset of CVE categories. For example, if we filter on CVEs that result in remote code execution (RCE), we see clear attempts to exploit Apache and Adobe installations towards the end of 2023 and start of 2024 along with a notable campaign targeting Citrix in May of this year.

Figure 4: Worldwide daily number of requests for Code Execution CVEs

Similar views become clearly visible when focusing on other CVEs or specific attack categories.

DDoS attacks remain the most common attack against web applications

DDoS attacks remain the most common attack type against web applications, with DDoS comprising 37.1% of all mitigated application traffic over the time period considered.

Figure 5: Volume of HTTP DDoS attacks over time

We saw a large increase in volumetric attacks in February and March 2024. This was partly the result of improved detections deployed by our teams, in addition to increased attack activity. In the first quarter of 2024 alone, Cloudflare’s automated defenses mitigated 4.5 million unique DDoS attacks, an amount equivalent to 32% of all the DDoS attacks Cloudflare mitigated in 2023. Specifically, application layer HTTP DDoS attacks increased by 93% YoY and 51% quarter-over-quarter (QoQ).

Cloudflare correlates DDoS attack traffic and defines unique attacks by looking at event start and end times along with target destination.

Motives for launching DDoS attacks range from targeting specific organizations for financial gains (ransom), to testing the capacity of botnets, to targeting institutions and countries for political reasons. As an example, Cloudflare observed a 466% increase in DDoS attacks on Sweden after its acceptance to the NATO alliance on March 7, 2024. This mirrored the DDoS pattern observed during Finland’s NATO acceptance in 2023. The size of DDoS attacks themselves are also increasing.

In August 2023, Cloudflare mitigated a hyper-volumetric HTTP/2 Rapid Reset DDoS attack that peaked at 201 million requests per second (rps) – three times larger than any previously observed attack. In the attack, threat actors exploited a zero-day vulnerability in the HTTP/2 protocol that had the potential to incapacitate nearly any server or application supporting HTTP/2. This underscores how menacing DDoS vulnerabilities are for unprotected organizations.

Gaming and gambling became the most targeted sector by DDoS attacks, followed by Internet technology companies and cryptomining.

Figure 6: Largest HTTP DDoS attacks as seen by Cloudflare, by year

Bot traffic insights

Cloudflare has continued to invest heavily in our bot detection systems. In early July, we declared AIndependence to help preserve a safe Internet for content creators, offering a brand new “easy button” to block all AI bots. It’s available for all customers, including those on our free tier.

Major progress has also been made in other complementary systems such as our Turnstile offering, a user-friendly, privacy-preserving alternative to CAPTCHA.

All these systems and technologies help us better identify and differentiate human traffic from automated bot traffic.

On average, bots comprise one-third of all application traffic

31.2% of all application traffic processed by Cloudflare is bot traffic. This percentage has stayed relatively consistent (hovering at about 30%) over the past three years.

The term bot traffic may carry a negative connotation, but in reality bot traffic is not necessarily good or bad; it all depends on the purpose of the bots. Some are “good” and perform a needed service, such as customer service chatbots and authorized search engine crawlers. But some bots misuse an online product or service and need to be blocked.

Different application owners may have different criteria for what they deem a “bad” bot. For example, some organizations may want to block a content scraping bot that is being deployed by a competitor to undercut on prices, whereas an organization that does not sell products or services may not be as concerned with content scraping. Known, good bots are classified by Cloudflare as “verified bots.”

93% of bots we identified were unverified bots, and potentially malicious

Unverified bots are often created for disruptive and harmful purposes, such as hoarding inventory, launching DDoS attacks, or attempting to take over an account via brute force or credential stuffing. Verified bots are those that are known to be safe, such as search engine crawlers, and Cloudflare aims to verify all major legitimate bot operators. A list of all verified bots can be found in our documentation.

Attackers leveraging bots focus most on industries that could bring them large financial gains. For example, consumer goods websites are often the target of inventory hoarding, price scraping run by competition or automated applications aimed at exploiting some sort of arbitrage (for example, sneaker bots). This type of abuse can have a significant financial impact on the target organization.

Figure 8: Industries with the highest median daily share of bot traffic

API traffic insights

Consumers and end users expect dynamic web and mobile experiences powered by APIs. For businesses, APIs fuel competitive advantages, greater business intelligence, faster cloud deployments, integration of new AI capabilities, and more.

However, APIs introduce new risks by providing outside parties additional attack surfaces with which to access applications and databases which also need to be secured. As a consequence, numerous attacks we observe are not targeting API endpoints first rather than the traditional web interfaces.

The additional security concerns are of course not slowing down adoption of API first applications.

60% of dynamic (non cacheable) traffic is API-related

This is a two percentage point increase compared to last year’s report. Of this 60%, about 4% on average is mitigated by our security systems.

Figure 9: Share of mitigated API traffic

A substantial spike is visible around January 11-17 that accounts for almost a 10% increase in traffic share alone for that period. This was due to a specific customer zone receiving attack traffic that was mitigated by a WAF Custom Rule.

Digging into mitigation sources for API traffic, we see the WAF being the largest contributor, as standard malicious payloads are commonly applicable to both API endpoints and standard web applications.

Figure 10: API mitigated traffic broken down by product group

A quarter of APIs are “shadow APIs”

You cannot protect what you cannot see. And, many organizations lack accurate API inventories, even when they believe they can correctly identify API traffic.

Using our proprietary machine learning model that scans not just known API calls, but all HTTP requests (identifying API traffic that may be going unaccounted for), we found that organizations had 33% more public-facing API endpoints than they knew about. This number was the median, and it was calculated by comparing the number of API endpoints detected through machine learning based discovery vs. customer-provided session identifiers.

This suggests that nearly a quarter of APIs are “shadow APIs” and may not be properly inventoried and secured.

Client-side risks

Most organizations’ web apps rely on separate programs or pieces of code from third-party providers (usually coded in JavaScript). The use of third-party scripts accelerates modern web app development and allows organizations to ship features to market faster, without having to build all new app features in-house.

Using Cloudflare’s client side security product, Page Shield, we can get a view on the popularity of third party libraries used on the Internet and the risk they pose to organizations. This has become very relevant recently due to the Polyfill.io incident that affected more than one hundred thousand sites.

Enterprise applications use 47 third-party scripts on average

Cloudflare’s typical enterprise customer uses an average of 47 third-party scripts, and a median of 20 third-party scripts. The average is much higher than the median due to SaaS providers, who often have thousands of subdomains which may all use third-party scripts. Here are some of the top third-party script providers Cloudflare customers commonly use:

  • Google (Tag Manager, Analytics, Ads, Translate, reCAPTCHA, YouTube)
  • Meta (Facebook Pixel, Instagram)
  • Cloudflare (Web Analytics)
  • jsDelivr
  • New Relic
  • Appcues
  • Microsoft (Clarity, Bing, LinkedIn)
  • jQuery
  • WordPress (Web Analytics, hosted plugins)
  • Pinterest
  • UNPKG
  • TikTok
  • Hotjar

While useful, third-party software dependencies are often loaded directly by the end-user’s browser (i.e. they are loaded client-side) placing organizations and their customers at risk given that organizations have no direct control over third-party security measures. For example, in the retail sector, 18% of all data breaches originate from Magecart style attacks, according to Verizon’s 2024 Data Breach Investigations Report.

Enterprise applications connect to nearly 50 third-parties on average

Loading a third-party script into your website poses risks, even more so when that script “calls home” to submit data to perform the intended function. A typical example here is Google Analytics: whenever a user performs an action, the Google Analytics script will submit data back to the Google servers. We identify these as connections.

On average, each enterprise website connects to 50 separate third-party destinations, with a median of 15. Each of these connections also poses a potential client-side security risk as attackers will often use them to exfiltrate additional data going unnoticed.

Here are some of the top third-party connections Cloudflare customers commonly use:

  • Google (Analytics, Ads)
  • Microsoft (Clarity, Bing, LinkedIn)
  • Meta (Facebook Pixel)
  • Hotjar
  • Kaspersky
  • Sentry
  • Criteo
  • tawk.to
  • OneTrust
  • New Relic
  • PayPal

Looking forward

This application security report is also available in PDF format with additional recommendations on how to address many of the concerns raised, along with additional insights.

We also publish many of our reports with dynamic charts on Cloudflare Radar, making it an excellent resource to keep up to date with the state of the Internet.

Automatically replacing polyfill.io links with Cloudflare’s mirror for a safer Internet

Post Syndicated from Matthew Prince original https://blog.cloudflare.com/automatically-replacing-polyfill-io-links-with-cloudflares-mirror-for-a-safer-internet


polyfill.io, a popular JavaScript library service, can no longer be trusted and should be removed from websites.

Multiple reports, corroborated with data seen by our own client-side security system, Page Shield, have shown that the polyfill service was being used, and could be used again, to inject malicious JavaScript code into users’ browsers. This is a real threat to the Internet at large given the popularity of this library.

We have, over the last 24 hours, released an automatic JavaScript URL rewriting service that will rewrite any link to polyfill.io found in a website proxied by Cloudflare to a link to our mirror under cdnjs. This will avoid breaking site functionality while mitigating the risk of a supply chain attack.

Any website on the free plan has this feature automatically activated now. Websites on any paid plan can turn on this feature with a single click.

You can find this new feature under Security ⇒ Settings on any zone using Cloudflare.

Contrary to what is stated on the polyfill.io website, Cloudflare has never recommended the polyfill.io service or authorized their use of Cloudflare’s name on their website. We have asked them to remove the false statement and they have, so far, ignored our requests. This is yet another warning sign that they cannot be trusted.

If you are not using Cloudflare today, we still highly recommend that you remove any use of polyfill.io and/or find an alternative solution. And, while the automatic replacement function will handle most cases, the best practice is to remove polyfill.io from your projects and replace it with a secure alternative mirror like Cloudflare’s even if you are a customer.

You can do this by searching your code repositories for instances of polyfill.io and replacing it with cdnjs.cloudflare.com/polyfill/ (Cloudflare’s mirror). This is a non-breaking change as the two URLs will serve the same polyfill content. All website owners, regardless of the website using Cloudflare, should do this now.

How we came to this decision

Back in February, the domain polyfill.io, which hosts a popular JavaScript library, was sold to a new owner: Funnull, a relatively unknown company. At the time, we were concerned that this created a supply chain risk. This led us to spin up our own mirror of the polyfill.io code hosted under cdnjs, a JavaScript library repository sponsored by Cloudflare.

The new owner was unknown in the industry and did not have a track record of trust to administer a project such as polyfill.io. The concern, highlighted even by the original author, was that if they were to abuse polyfill.io by injecting additional code to the library, it could cause far reaching security problems on the Internet affecting several hundreds of thousands websites. Or it could be used to perform a targeted supply-chain attack against specific websites.

Unfortunately, that worry came true on June 25, 2024 as the polyfill.io service was being used to inject nefarious code that, under certain circumstances, redirected users to other websites.

We have taken the exceptional step of using our ability to modify HTML on the fly to replace references to the polyfill.io CDN in our customers’ websites with links to our own, safe, mirror created back in February.

In the meantime, additional threat feed providers have also taken the decision to flag the domain as malicious. We have not outright blocked the domain through any of the mechanisms we have because we are concerned it could cause widespread web outages given how broadly polyfill.io is used with some estimates indicating usage on nearly 4% of all websites.

Corroborating data with Page Shield

The original report indicates that malicious code was injected that, under certain circumstances, would redirect users to betting sites. It was doing this by loading additional JavaScript that would perform the redirect, under a set of additional domains which can be considered Indicators of Compromise (IoCs):

https://www.googie-anaiytics.com/analytics.js
https://www.googie-anaiytics.com/html/checkcachehw.js
https://www.googie-anaiytics.com/gtags.js
https://www.googie-anaiytics.com/keywords/vn-keyword.json
https://www.googie-anaiytics.com/webs-1.0.1.js
https://www.googie-anaiytics.com/analytics.js
https://www.googie-anaiytics.com/webs-1.0.2.js
https://www.googie-anaiytics.com/ga.js
https://www.googie-anaiytics.com/web-1.0.1.js
https://www.googie-anaiytics.com/web.js
https://www.googie-anaiytics.com/collect.js
https://kuurza.com/redirect?from=bitget

(note the intentional misspelling of Google Analytics)

Page Shield, our client side security solution, is available on all paid plans. When turned on, it collects information about JavaScript files loaded by end user browsers accessing your website.

By looking at the database of detected JavaScript files, we immediately found matches with the IoCs provided above starting as far back as 2024-06-08 15:23:51 (first seen timestamp on Page Shield detected JavaScript file). This was a clear indication that malicious activity was active and associated with polyfill.io.

Replacing insecure JavaScript links to polyfill.io

To achieve performant HTML rewriting, we need to make blazing-fast HTML alterations as responses stream through Cloudflare’s network. This has been made possible by leveraging ROFL (Response Overseer for FL). ROFL powers various Cloudflare products that need to alter HTML as it streams, such as Cloudflare Fonts, Email Obfuscation and Rocket Loader

ROFL is developed entirely in Rust. The memory-safety features of Rust are indispensable for ensuring protection against memory leaks while processing a staggering volume of requests, measuring in the millions per second. Rust’s compiled nature allows us to finely optimize our code for specific hardware configurations, delivering performance gains compared to interpreted languages.

The performance of ROFL allows us to rewrite HTML on-the-fly and modify the polyfill.io links quickly, safely, and efficiently. This speed helps us reduce any additional latency added by processing the HTML file.

If the feature is turned on, for any HTTP response with an HTML Content-Type, we parse all JavaScript script tag source attributes. If any are found linking to polyfill.io, we rewrite the src attribute to link to our mirror instead. We map to the correct version of the polyfill service while the query string is left untouched.

The logic will not activate if a Content Security Policy (CSP) header is found in the response. This ensures we don’t replace the link while breaking the CSP policy and therefore potentially breaking the website.

Default on for free customers, optional for everyone else

Cloudflare proxies millions of websites, and a large portion of these sites are on our free plan. Free plan customers tend to have simpler applications while not having the resources to update and react quickly to security concerns. We therefore decided to turn on the feature by default for sites on our free plan, as the likelihood of causing issues is reduced while also helping keep safe a very large portion of applications using polyfill.io.

Paid plan customers, on the other hand, have more complex applications and react quicker to security notices. We are confident that most paid customers using polyfill.io and Cloudflare will appreciate the ability to virtually patch the issue with a single click, while controlling when to do so.

All customers can turn off the feature at any time.

This isn’t the first time we’ve decided a security problem was so widespread and serious that we’d enable protection for all customers regardless of whether they were a paying customer or not. Back in 2014, we enabled Shellshock protection for everyone. In 2021, when the log4j vulnerability was disclosed we rolled out protection for all customers.

Do not use polyfill.io

If you are using Cloudflare, you can remove polyfill.io with a single click on the Cloudflare dashboard by heading over to your zone ⇒ Security ⇒ Settings. If you are a free customer, the rewrite is automatically active. This feature, we hope, will help you quickly patch the issue.

Nonetheless, you should ultimately search your code repositories for instances of polyfill.io and replace them with an alternative provider, such as Cloudflare’s secure mirror under cdnjs (https://cdnjs.cloudflare.com/polyfill/). Website owners who are not using Cloudflare should also perform these steps.

The underlying bundle links you should use are:

For minified: https://cdnjs.cloudflare.com/polyfill/v3/polyfill.min.js
For unminified: https://cdnjs.cloudflare.com/polyfill/v3/polyfill.js

Doing this ensures your website is no longer relying on polyfill.io.

Application Security at re:Inforce 2024

Post Syndicated from Daniel Begimher original https://aws.amazon.com/blogs/security/application-security-at-reinforce-2024/

Join us in Philadelphia, Pennsylvania, on June 10–12, 2024, for AWS re:Inforce, a security learning conference where you can enhance your skills and confidence in cloud security, compliance, identity, and privacy. As an attendee, you will have access to hundreds of technical and non-technical sessions, an Expo featuring Amazon Web Services (AWS) experts and AWS Security Competency Partners, and keynote sessions led by industry leaders. AWS re:Inforce offers a comprehensive focus on six key areas, including Application Security.

The Application Security track helps you understand and implement best practices for securing your applications throughout the development lifecycle. This year, we are focusing on several key themes:

  • Building a culture of security – Learn how to define and influence organizational behavior to speed up application development, while reducing overall security risk through implementing best practices, training your internal teams, and defining ownership.
  • Security of the pipeline – Discover how to embed governance and guardrails to allow developer agility, while maintaining security across your continuous integration and delivery (CI/CD) pipelines.
  • Security in the pipeline – Explore tooling and automation to reduce the mean time of security reviews and embed continuous security into each stage of the development pipeline.
  • Supply chain security – Gain improved awareness of how risks are introduced by extension, track dependencies, and identify vulnerabilities used in your software.

Additionally, this year the Application Security track will have sessions focused on generative AI (gen AI), covering how to secure gen AI applications and use gen AI for development. Join these sessions to deepen your knowledge and up-level your skills, so that you can build modern applications that are robust, resilient, and secure.

Breakout sessions, chalk talks, lightning talks, and code talks

APS201 | Breakout session | Accelerate securely: The Generative AI Security Scoping Matrix
As generative AI ignites business innovation, cybersecurity teams need to keep up with the accelerating domain. Security leaders are seeking tools and answers to help drive requirements around governance, compliance, legal, privacy, threat mitigations, resiliency, and more. This session introduces you to the Generative AI Security Scoping Matrix, which is designed to provide a common language and thought model for approaching generative AI security. Leave the session with a framework, techniques, and best practices that you can use to support responsible adoption of generative AI solutions designed to help your business move at an ever-increasing pace.

APS301 | Breakout session | Enhance AppSec: Generative AI integration in AWS testing
This session presents an in-depth look at the AWS Security Testing program, emphasizing its scaling efforts to help ensure new products and services meet a high security bar pre-launch. With a focus on integrating generative AI into its testing framework, the program showcases how AWS anticipates and mitigates complex security threats to maintain cloud security. Learn about AWS’s proactive approaches to collaboration across teams and mitigating vulnerabilities, enriched by case studies that highlight the program’s flexibility and dedication to security excellence. Ideal for security experts and cloud architects, this session offers valuable insights into safeguarding cloud computing technologies.

APS302 | Breakout session | Building a secure MLOps pipeline, featuring PathAI
DevOps and MLOps are both software development strategies that focus on collaboration between developers, operations, and data science teams. In this session, learn how to build modern, secure MLOps using AWS services and tools for infrastructure and network isolation, data protection, authentication and authorization, detective controls, and compliance. Discover how AWS customer PathAI, a leading digital pathology and AI company, uses seamless DevOps and MLOps strategies to run their AISight intelligent image management system and embedded AI products to support anatomic pathology labs and bio-pharma partners globally.

APS401 | Breakout session | Keeping your code secure
Join this session to dive deep into how AWS implemented generative AI tooling in our developer workflows. Learn about the AWS approach to creating the underlying code scanning and remediation engines that AWS uses internally. Also, explore how AWS integrated these tools into the services we offer through reactive and proactive security features. Leave this session with a better understanding of how you can use AWS to secure code and how the code offered to you through AWS generative AI services is designed to be secure.

APS402 | Breakout session | Verifying code using automated reasoning
In this session, AWS principal applied scientists discuss how they use automated reasoning to certify bug-free code mathematically and help secure underlying infrastructure. Explore how to use Kani, an AWS created open source engine that analyzes, verifies, and detects errors in safe and unsafe Rust code. Hear how AWS built and implemented Kani internally with examples taken from real-world AWS open source code. Leave this session with the tools you need to get started using this Rust verification engine for your own workloads.

APS232 | Chalk talk | Successful security team patterns
It’s more common to hear what a security team does than to hear how the security team does it, or with whom the security team works rather than how it was designed to work. Organizational design is often demoted to a secondary consideration behind the goals of a security team, despite intentional design generally being what empowers, or hinders, security teams from achieving their goals. Security must work across the organization, not in isolation. This chalk talk focuses on designing effective security teams for organizations moving to the cloud, which necessitates outlining both what the security team works on and how it achieves that work.

APS331 | Chalk talk | Verifiable and auditable security inside the pipeline
In this chalk talk, explore platform engineering best practices at AWS. AWS deploys more than 150 million times per year while maintaining 143 different compliance framework attestations and certifications. Internally, AWS has learned how to make security easier for builder teams. Learn key risks associated with operating pipelines at scale and Amazonian mechanisms to make security controls inside the pipeline verifiable and auditable so that you can shift compliance and auditing left into the pipeline.

APS233 | Chalk talk | Threat modeling your generative AI workload to evaluate security risk
As the capabilities and possibilities of machine learning continue to expand with advances in generative AI, understanding the security risks introduced by these advances is essential for protecting your valuable AWS workloads. This chalk talk guides you through a practical threat modeling approach, empowering you to create a threat model for your own generative AI applications. Gain confidence to build your next generative AI workload securely on AWS with the help of threat modeling and leave with actionable steps you can take to get started.

APS321 | Lightning talk | Using generative AI to create more secure applications
Generative AI revolutionizes application development by enhancing security and efficiency. This lightning talk explores how Amazon Q, your generative AI assistant, empowers you to build, troubleshoot, and transform applications securely. Discover how its capabilities streamline the process, allowing you to focus on innovation while ensuring robust security measures. Unlock the power of generative AI for helping build secure, cutting-edge applications.

APS341 | Code talk | Shifting left, securing right: Container supply chain security
Supply chain security for containers helps ensure you can detect software security risks in third-party packages and remediate them during the container image build process. This prevents container images with vulnerabilities from being pushed to your container registry and causing potential harm to your production systems. In this code talk, learn how you can apply a shift-left approach to container image security testing in your deployment pipelines.

Hands-on sessions

APS373 | Workshop | Build a more secure generative AI chatbot with security guardrails
Generative AI is an emerging technology that is disrupting multiple industries. An early generative AI use case is interactive chat in customer service applications. As users interact with generative AI chatbots, there are security risks, such as prompt injection and jailbreaking resulting from specially crafted inputs sent to large language models. In this workshop, learn how to build an AI chatbot using Amazon Bedrock and protect it using Guardrails for Amazon Bedrock. You must bring your laptop to participate.

APS351 | Builders’ session | Implement controls for the OWASP Top 10 for LLM applications
In this builders’ session, learn how to implement security controls that address the OWASP Top 10 for LLM applications on AWS. Experts guide you through the use of AWS security tooling to provide practical insights and solutions to mitigate the most critical security risks outlined by OWASP. Discover technical options and choices you can make in cloud infrastructure and large-scale enterprise environments augmented by AWS generative AI technology. You must bring your laptop to participate.

APS271 | Workshop | Threat modeling for builders
In this workshop, learn threat modeling core concepts and how to apply them through a series of group exercises. Key topics include threat modeling personas, key phases, data flow diagrams, STRIDE, and risk response strategies as well as the introduction of a “threat grammar rule” with an associated tool. In exercises, identify threats and mitigations through the lens of each threat modeling persona. Assemble in groups and walk through a case study, with AWS threat modeling experts on hand to guide you and provide feedback. You must bring your laptop to participate.

APS371 | Workshop | Integrating open source security tools with AWS code services
AWS, open source, and partner tooling work together to accelerate your software development lifecycle. In this workshop, learn how to use the Automated Security Helper (ASH), an open source application security tool, to quickly integrate various security testing tools into your software build and deployment flows. AWS experts guide you through the process of security testing locally on your machines and within the AWS CodeCommit, AWS CodeBuild, and AWS CodePipeline services. In addition, discover how to identify potential security issues in your applications through static analysis, software composition analysis, and infrastructure-as-code testing. You must bring your laptop to participate.

This blog post highlighted some of the unique sessions in the Application Security track at the upcoming re:Inforce 2024 conference in Philadelphia. If these sessions pique your interest, register for re:Inforce 2024 to attend them, along with the numerous other Application Security sessions offered at the conference. For a comprehensive overview of sessions across all tracks, explore the AWS re:Inforce catalog preview.

 
If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

Daniel Begimher

Daniel Begimher
Daniel is a Senior Security Engineer specializing in cloud security and incident response solutions. He holds all AWS certifications and authored the open-source code scanning tool, Automated Security Helper. In his free time, Daniel enjoys gadgets, video games, and traveling.

Ipolitas Dunaravich

Ipolitas Dunaravich
Ipolitas is a technical marketing leader for networking and security services at AWS. With over 15 years of marketing experience and more than 4 years at AWS, Ipolitas is the Head of Marketing for AppSec services and curates the security content for re:Inforce and re:Invent.

The art of possible: Three themes from RSA Conference 2024

Post Syndicated from Anne Grahn original https://aws.amazon.com/blogs/security/the-art-of-possible-three-themes-from-rsa-conference-2024/

San Francisco skyline with Oakland Bay Bridge at sunset, California, USA

RSA Conference 2024 drew 650 speakers, 600 exhibitors, and thousands of security practitioners from across the globe to the Moscone Center in San Francisco, California from May 6 through 9.

The keynote lineup was diverse, with 33 presentations featuring speakers ranging from WarGames actor Matthew Broderick, to public and private-sector luminaries such as Cybersecurity and Infrastructure Security Agency (CISA) Director Jen Easterly, U.S. Secretary of State Antony Blinken, security technologist Bruce Schneier, and cryptography experts Tal Rabin, Whitfield Diffie, and Adi Shamir.

Topics aligned with this year’s conference theme, “The art of possible,” and focused on actions we can take to revolutionize technology through innovation, while fortifying our defenses against an evolving threat landscape.

This post highlights three themes that caught our attention: artificial intelligence (AI) security, the Secure by Design approach to building products and services, and Chief Information Security Officer (CISO) collaboration.

AI security

Organizations in all industries have started building generative AI applications using large language models (LLMs) and other foundation models (FMs) to enhance customer experiences, transform operations, improve employee productivity, and create new revenue channels. So it’s not surprising that AI dominated conversations. Over 100 sessions touched on the topic, and the desire of attendees to understand AI technology and learn how to balance its risks and opportunities was clear.

“Discussions of artificial intelligence often swirl with mysticism regarding how an AI system functions. The reality is far more simple: AI is a type of software system.” — CISA

FMs and the applications built around them are often used with highly sensitive business data such as personal data, compliance data, operational data, and financial information to optimize the model’s output. As we explore the advantages of generative AI, protecting highly sensitive data and investments is a top priority. However, many organizations aren’t paying enough attention to security.

A joint generative AI security report released by Amazon Web Services (AWS) and the IBM Institute for Business Value during the conference found that 82% of business leaders view secure and trustworthy AI as essential for their operations, but only 24% are actively securing generative AI models and embedding security processes in AI development. In fact, nearly 70% say innovation takes precedence over security, despite concerns over threats and vulnerabilities (detailed in Figure 1).

Figure 1: Generative AI adoption concerns

Figure 1: Generative AI adoption concerns, Source: IBM Security

Because data and model weights—the numerical values models learn and adjust as they train—are incredibly valuable, organizations need them to stay protected, secure, and private, whether that means restricting access from an organization’s own administrators, customers, or cloud service provider, or protecting data from vulnerabilities in software running in the organization’s own environment.

There is no silver AI-security bullet, but as the report points out, there are proactive steps you can take to start protecting your organization and leveraging AI technology to improve your security posture:

  1. Establish a governance, risk, and compliance (GRC) foundation. Trust in gen AI starts with new security governance models (Figure 2) that integrate and embed GRC capabilities into your AI initiatives, and include policies, processes, and controls that are aligned with your business objectives.

    Figure 2: Updating governance, risk, and compliance models

    Figure 2: Updating governance, risk, and compliance models, Source: IBM Security

    In the RSA Conference session AI: Law, Policy, and Common Sense Suggestions to Stay Out of Trouble, digital commerce and gaming attorney Behnam Dayanim highlighted ethical, policy, and legal considerations—including AI-specific regulations—as well as governance structures such as the National Institute of Standards and Technology (NIST) AI Risk Management Framework (AI RMF 1.0) that can help maximize a successful implementation and minimize potential risk.

  2. Strengthen your security culture. When we think of securing AI, it’s natural to focus on technical measures that can help protect the business. But organizations are made up of people—not technology. Educating employees at all levels of the organization can help avoid preventable harms such as prompt-based risks and unapproved tool use, and foster a resilient culture of cybersecurity that supports effective risk mitigation, incident detection and response, and continuous collaboration.

    “You’ve got to understand early on that security can’t be effective if you’re running it like a project or a program. You really have to run it as an operational imperative—a core function of the business. That’s when magic can happen.” — Hart Rossman, Global Services Security Vice President at AWS
  3. Engage with partners. Developing and securing AI solutions requires resources and skills that many organizations lack. Partners can provide you with comprehensive security support—whether that’s informing and advising you about generative AI, or augmenting your delivery and support capabilities. This can help make your engineers and your security controls more effective.

    While many organizations purchase security products or solutions with embedded generative AI capabilities, nearly two-thirds, as detailed in Figure 3, report that their generative AI security capabilities come through some type of partner.

    Figure 3: More than 90% of security gen AI capabilities are coming from third-party products or partners

    Figure 3: Most security gen AI capabilities are coming from third-party products or partners, Source: IBM Security

    Tens of thousands of customers are using AWS, for example, to experiment and move transformative generative AI applications into production. AWS provides AI-powered tools and services, a Generative AI Innovation Center program, and an extensive network of AWS partners that have demonstrated expertise delivering machine learning (ML) and generative AI solutions. These resources can support your teams with hands-on help developing solutions mapped to your requirements, and a broader collection of knowledge they can use to help you make the nuanced decisions required for effective security.

View the joint report and AWS generative AI security resources for additional guidance.

Secure by Design

Building secure software was a popular and related focus at the conference. Insecure design is ranked as the number four critical web application security concern on the Open Web Application Security Project (OWASP) Top 10.

The concept known as Secure by Design is gaining importance in the effort to mitigate vulnerabilities early, minimize risks, and recognize security as a core business requirement. Secure by Design builds off of security models such as Zero Trust, and aims to reduce the burden of cybersecurity and break the cycle of constantly creating and applying updates by developing products that are foundationally secure.

More than 60 technology companies—including AWS—signed CISA’s Secure by Design Pledge during RSA Conference as part of a collaborative push to put security first when designing products and services.

The pledge demonstrates a commitment to making measurable progress towards seven goals within a year:

  • Broaden the use of multi-factor authentication (MFA)
  • Reduce default passwords
  • Enable a significant reduction in the prevalence of one or more vulnerability classes
  • Increase the installation of security patches by customers
  • Publish a vulnerability disclosure policy (VDP)
  • Demonstrate transparency in vulnerability reporting
  • Strengthen the ability of customers to gather evidence of cybersecurity intrusions affecting products

“From day one, we have pioneered secure by design and secure by default practices in the cloud, so AWS is designed to be the most secure place for customers to run their workloads. We are committed to continuing to help organizations around the world elevate their security posture, and we look forward to collaborating with CISA and other stakeholders to further grow and promote security by design and default practices.” — Chris Betz, CISO at AWS

The need for security by design applies to AI like any other software system. To protect users and data, we need to build security into ML and AI with a Secure by Design approach that considers these technologies to be part of a larger software system, and weaves security into the AI pipeline.

Since models tend to have very high privileges and access to data, integrating an AI bill of materials (AI/ML BOM) and Cryptography Bill of Materials (CBOM) into BOM processes can help you catalog security-relevant information, and gain visibility into model components and data sources. Additionally, frameworks and standards such as the AI RMF 1.0, the HITRUST AI Assurance Program, and ISO/IEC 42001 can facilitate the incorporation of trustworthiness considerations into the design, development, and use of AI systems.

CISO collaboration

In the RSA Conference keynote session CISO Confidential: What Separates The Best From The Rest, Trellix CEO Bryan Palma and CISO Harold Rivas noted that there are approximately 32,000 global CISOs today—4 times more than 10 years ago. The challenges they face include staffing shortages, liability concerns, and a rapidly evolving threat landscape. According to research conducted by the Information Systems Security Association (ISSA), nearly half of organizations (46%) report that their cybersecurity team is understaffed, and more than 80% of CISOs recently surveyed by Trellix have experienced an increase in cybersecurity threats over the past six months. When asked what would most improve their organizations’ abilities to defend against these threats, their top answer was industry peers sharing insights and best practices.

Building trusted relationships with peers and technology partners can help you gain the knowledge you need to effectively communicate the story of risk to your board of directors, keep up with technology, and build success as a CISO.

AWS CISO Circles provide a forum for cybersecurity executives from organizations of all sizes and industries to share their challenges, insights, and best practices. CISOs come together in locations around the world to discuss the biggest security topics of the moment. With NDAs in place and the Chatham House Rule in effect, security leaders can feel free to speak their minds, ask questions, and get feedback from peers through candid conversations facilitated by AWS Security leaders.

“When it comes to security, community unlocks possibilities. CISO Circles give us an opportunity to deeply lean into CISOs’ concerns, and the topics that resonate with them. Chatham House Rule gives security leaders the confidence they need to speak openly and honestly with each other, and build a global community of knowledge-sharing and support.” — Clarke Rodgers, Director of Enterprise Strategy at AWS

At RSA Conference, CISO Circle attendees discussed the challenges of adopting generative AI. When asked whether CISOs or the business own generative AI risk for the organization, the consensus was that security can help with policies and recommendations, but the business should own the risk and decisions about how and when to use the technology. Some attendees noted that they took initial responsibility for generative AI risk, before transitioning ownership to an advisory board or committee comprised of leaders from their HR, legal, IT, finance, privacy, and compliance and ethics teams over time. Several CISOs expressed the belief that quickly taking ownership of generative AI risk before shepherding it to the right owner gave them a valuable opportunity to earn trust with their boards and executive peers, and to demonstrate business leadership during a time of uncertainty.

Embrace the art of possible

There are many more RSA Conference highlights on a wide range of additional topics, including post-quantum cryptography developments, identity and access management, data perimeters, threat modeling, cybersecurity budgets, and cyber insurance trends. If there’s one key takeaway, it’s that we should never underestimate what is possible from threat actors or defenders. By harnessing AI’s potential while addressing its risks, building foundationally secure products and services, and developing meaningful collaboration, we can collectively strengthen security and establish cyber resilience.

Join us to learn more about cloud security in the age of generative AI at AWS re:Inforce 2024 June 10–12 in Pennsylvania. Register today with the code SECBLOfnakb to receive a limited time $150 USD discount, while supplies last.

 
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Anne Grahn

Anne Grahn

Anne is a Senior Worldwide Security GTM Specialist at AWS, based in Chicago. She has more than a decade of experience in the security industry, and focuses on effectively communicating cybersecurity risk. She maintains a Certified Information Systems Security Professional (CISSP) certification.

Danielle Ruderman

Danielle Ruderman

Danielle is a Senior Manager for the AWS Worldwide Security Specialist Organization, where she leads a team that enables global CISOs and security leaders to better secure their cloud environments. Danielle is passionate about improving security by building company security culture that starts with employee engagement.