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How to prioritize security risks using AWS Security Hub exposure findings

Post Syndicated from Shahna Campbell original https://aws.amazon.com/blogs/security/how-to-prioritize-security-risks-using-aws-security-hub-exposure-findings/

At re:Inforce 2025, AWS unveiled an enhanced AWS Security Hub that transforms how organizations prioritize their most critical security issues and respond at scale to protect their cloud environments. In this blog post, we discuss how you can use Security Hub to prioritize these issues with exposure findings. The enhanced Security Hub now uses advanced analytics to automatically correlate, enrich, and prioritize security signals across your cloud environment. Security Hub seamlessly integrates with Amazon GuardDuty, Amazon Inspector, Amazon Macie, and AWS Security Hub Cloud Security Posture Management (CSPM), formerly known as AWS Security Hub. Through these integrations, it provides comprehensive threat detection and vulnerability assessment. This intelligent integration helps organizations quickly identify critical security issues, from potential credential compromises to unintended resource exposures, enabling security teams to focus on what matters most.

What is Security Hub?

Security Hub delivers three key security capabilities to help you strengthen your cloud security posture through a unified cloud security solution:

  • Provides visibility across your organization through centralized management and continuous monitoring.
  • Enriches security signals from services such as Amazon Inspector and AWS Security Hub CSPM to surface active risks specific to your environment, so you can prioritize with confidence and streamline response.
  • Delivers integrated risk analysis by correlating findings from Amazon Inspector, AWS Security Hub CSPM, Amazon Macie, and other AWS services to help identify potential attack paths, surface exploitable vulnerabilities and misconfigurations, and provide actionable remediation guidance.

A top concern for customers is: How do I know where to prioritize response first? Managing large volumes of findings across multiple accounts and regions becomes more challenging when security findings are viewed in isolation, making it difficult to determine true priority and impact. Security Hub solves this by providing context-driven analysis. It surfaces the most critical risks by correlating related vulnerabilities, threats, and misconfigurations to reveal exploitable paths. This can help you make informed decisions about which issues to address first.

With exposure findings, you can prioritize critical security issues and respond at scale. Exposures are based on an analysis of findings and traits from Security Hub CSPM, Amazon Inspector (which scans for vulnerabilities), and Amazon Macie (which discovers and protects sensitive data). They are defined as potential security issues, and they are generated by different exposure traits.

Without automated correlation and enriched signals, security teams can struggle to effectively prioritize issues. For example, a vulnerability that Amazon Inspector detects might become critically important when combined with misconfigurations that Security Hub CSPM identifies. However, manually analyzing relationships across thousands of signals is time-consuming and prone to missing critical security context. Teams often build custom solutions to achieve this, but this approach requires significant analyst time and maintenance, which can cause critical security relationships to be overlooked.

Security Hub reduces this complexity by providing native integration across these AWS services in a unified cloud security center, without the operational overhead of log collection and aggregation. For security teams, this means they can help identify and respond to their most critical exposures before the exposures can lead to business impact, rather than spending valuable time manually piecing together individual security signals. Automated correlation and enriched context can help you make faster, more informed decisions about where to focus your efforts. This ultimately helps protect your cloud environment more effectively.

Exposure findings identify security risks in your environment by providing a comprehensive view of your security posture. These findings enable you to understand and address potential risks. Through this consolidated approach, you can efficiently prioritize your remediation efforts by focusing on the most critical exposure findings first,.

Exposure findings are formatted in the Open Cybersecurity Schema Framework (OCSF) schema, an open-source standard that enables security tools to share data seamlessly. The adoption of OCSF by Security Hub has several advantages. As an open, standardized schema that is part of the Linux Foundation, OCSF enables interoperability across multiple security tools and services, both within and outside of the AWS environment. It provides enhanced data normalization with consistent field naming and categorization, making it more straightforward to integrate with third-party security tools.

Partners who already support or intend to support the OCSF schema to receive findings from Security Hub include companies such as Arctic Wolf; CrowdStrike; DataBee, a Comcast company; Datadog; DTEX Systems; Dynatrace; Fortinet; IBM; Netskope; Orca Security; Rapid7; Securonix; SentinelOne; Splunk, a Cisco Company; Sumo Logic; Tines; Trellix; and Wiz. Additionally, service partners such as Accenture, Caylent, Deloitte, IBM, and Optiv can help you adopt Security Hub and the OCSF schema.

Prioritizing security risks

When you navigate to Security Hub, you will see the summary dashboard, which includes an exposure summary widget, as shown in Figure 1. This widget shows your exposures by severity and frequency. Security Hub assigns each exposure finding a default severity of Critical, High, Medium, or Low. Exposure findings with a severity of Informational are not published.

Security Hub calculates exposure finding severity by analyzing and correlating multiple security traits across AWS services. Instead of evaluating these factors in isolation, Security Hub uses a contextual approach, assigning a severity rating based on how these factors are correlated. For example, a resource with an identified vulnerability might receive a higher severity rating if it’s exploitable from the internet or has access to sensitive data.

Security Hub uses several factors to determine the default severity of an exposure finding:

  • Ease of discovery – The availability of automated tools, such as port scans or internet searches to discover the resource at risk.
  • Ease of exploit – The ease with which a threat actor can exploit the risk. For example, if there are open network paths or misconfigured metadata, a threat actor can more quickly exploit the risk.
  • Likelihood of exploit – Security Hub uses both external signals, such as the Exploit Prediction Scoring System (EPSS)—a data-driven scoring system that estimates the probability of a vulnerability being exploited—and internal threat intelligence to determine the probability that the risk is exploited. This comprehensive approach applies to exposure findings for Amazon Elastic Compute Cloud (EC2) instances and AWS Lambda functions.
  • Awareness – The extent to which the risk is not merely theoretical but has publicly available or automated exploits. This factor applies to exposure findings for EC2 instances and Lambda functions.
  • Impact – The potential harm if the exploit is carried out. For example, an exposure could lead to loss of confidentiality from data exposure, loss of integrity from data corruption, loss of availability, or loss of accountability.

The list of risks in this widget is limited to the eight highest risks with the greatest number of critical findings. If two or more risks have an equal number of critical findings, the list automatically groups those findings behind more recent critical findings.

Figure 1 : Exposure summary widget

Figure 1 : Exposure summary widget

From the widget, you can pivot to the exposure dashboard to see to a pre-filtered view of your exposures for continued analysis of potential security issues. You can filter by severity by selecting the number associated with each severity, view a specific exposure by selecting from the list, or select View all exposure findings to see a dashboard of new exposures that are currently open, as shown in Figure 2.

Figure 2: Exposure dashboard

Figure 2: Exposure dashboard

The exposure console shows findings by their title and ranked by decreasing severity. It’s organized by the filter criteria and grouped by finding title. On the left-hand side, Quick filters provide a fast way to filter through exposures based on severity, the top 10 attributes based on the most common values across your findings, top 10 accounts, and top 10 resource types, as shown in Figure 2. In addition to using filters, you can use the Group by dropdown to group exposure findings by a specific attribute, such as AWS account ID, resource type, or product name.

To review the exposure, expand the findings, as shown in Figure 3 for the correlation of resources, status, attributes, and traits such as software vulnerabilities, misconfigurations, and reachability. These are also referred to as trait types. For a particular exposure finding, a trait can be associated with one or more signals, and a signal can contain one or more indicators.

Figure 3: Exposure findings

Figure 3: Exposure findings

As shown in Figure 3, the Potential Credential Stealing: Internet reachable EC2 instance with administrative instance profile has network-exploitable software vulnerabilities with a high likelihood of exploitation finding indicates that there are misconfigurations, vulnerabilities, and reachability (indication of an open network path to a resource) associated with the instance. To find out more about the signal, select anywhere in the line associated with the risk, and you will see an overview panel, as shown in Figure 4.

Figure 4: Exposure finding overview

Figure 4: Exposure finding overview

This example highlights a critical-severity finding for an internet-reachable EC2 instance with software vulnerabilities in the us-east-1 Region. This visualization is powerful because the Potential attack path diagram helps you see what matters by mapping out how potential threat actors could exploit these vulnerabilities to access your resources. The finding also includes critical metadata such as the resource identifier, creation time, reachability, vulnerability, and misconfigurations.

Using the finding, you can quickly understand complex security relationships, assess risk context, and determine remediation priorities, so you can better protect your workloads in the cloud and make more informed security decisions. To prioritize your security response efforts, you can also set finding severity levels and update status, and export findings in OCSF format.

To understand why an exposure is present, you can select the Traits tab, as shown in Figure 5. This will list traits such as Misconfiguration or Vulnerability. If you select By signal, in the Traits tab, you have a full list of the signals associated with the exposure finding. These signals are the underlying findings that were created from different services, such as Security Hub CSPM and Amazon Inspector, that were correlated together to determine the risk associated with the exposure finding.

Figure 5: Exposure finding traits

Figure 5: Exposure finding traits

If you select the Resources tab, you will see the resources associated with the exposure finding, as shown in Figure 6.

Figure 6: Exposure finding resources

Figure 6: Exposure finding resources

For this example, we have an EC2 instance, but you might have a combination of resources such as an EC2 instance, Amazon Simple Storage Service (Amazon S3) bucket, and AWS Identity and Access Management (IAM) role. This list of resources will help you determine what needs to be remediated in your environment to mitigate the risk attributed to this finding.

Finally, with the Create ticket option, Security Hub helps streamline the incident management process through its native integrations with popular ticketing systems such as Jira and ServiceNow. This integration minimizes the need for manual ticket creation and reduces the time between finding and fixing security issues. Organizations can use a Security Hub Automation Rule to automatically create and track tickets for security findings directly from the Security Hub console, helping to make sure that no critical security exposure goes unaddressed. Integration with these widely-used ticketing systems helps maintain a consistent workflow, enables better tracking of remediation efforts, and improves collaboration between security and operations teams. This can help you make your security operations more efficient by providing a streamlined path from detection to resolution.

Conclusion

The enhanced exposure findings capabilities in Security Hub represent a significant advancement in how organizations can secure their cloud environments. By automatically correlating and analyzing security signals across multiple AWS services, Security Hub helps you prioritize your most critical security issues confidently and respond at scale. The intuitive visualization of potential attack paths, combined with intelligent severity rankings and comprehensive trait analysis, enables security teams to make data-driven decisions about risk prioritization.

Security Hub exposure findings help organizations move from reactive to proactive security postures by:

  • Automatically discovering and evaluating publicly accessible resources
  • Providing clear visibility into security capabilities and configurations
  • Correlating multiple security signals to identify critical risks
  • Delivering actionable remediation guidance
  • Offering intuitive filtering and grouping options for efficient analysis

As cloud environments continue to grow in complexity, exposure findings provide the automation, intelligence, and context needed to stay ahead of potential security issues. This enables security teams to focus their valuable time on addressing the most critical risks first, ultimately helping organizations maintain a stronger security posture across their cloud environment.

Whether you’re managing a small deployment or a large enterprise environment, exposure findings in Security Hub provide the insights needed to effectively protect your AWS workloads and maintain a robust security position in an ever-evolving landscape.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on AWS Security, Identity, and Compliance re:Post or contact AWS Support.

Shahna Campbell

Shahna Campbell

Shahna is a solutions architect at AWS, working within the specialist organization with a focus on security. Previously, Shahna worked within the healthcare field clinically and as an application specialist. Shahna is passionate about cybersecurity and analytics. In her free time, she enjoys hiking, traveling, and spending time with family.

Author

Marshall Jones

Marshall is a Worldwide Security Specialist Solutions Architect at AWS. His background is in AWS consulting and security architecture and focused on a variety of security domains including edge, threat detection, and compliance. Today, he’s focused on helping enterprise AWS customers adopt and operationalize AWS security services to increase security effectiveness and reduce risk.

Kimberly Dickson

Kimberly is a Security Specialist Solutions Architect at AWS based in Singapore. She is passionate about working with customers on technical security solutions that help them build confidence and operate securely in the cloud.

AWS re:Inforce roundup 2025: top announcements

Post Syndicated from AWS News Blog Team original https://aws.amazon.com/blogs/aws/aws-reinforce-roundup-2025-top-announcements/

At AWS re:Inforce 2025 (June 16-18, Philadelphia), AWS Vice President and Chief Information Security Officer Amy Herzog delivered the keynote address, announcing new security innovations. Throughout the event, AWS announced additional security capabilities focused on simplifying security at scale and enabling organizations to build more resilient applications in the cloud. Below is a comprehensive roundup of the major security launches and updates announced at this year’s conference.

Verify internal access to critical AWS resources with new IAM Access Analyzer capabilities
A new capability in AWS Identity and Access Management Access Analyzer helps security teams verify which principals within their AWS organization have access to critical resources like S3 buckets, DynamoDB tables, and RDS snapshots by using automated reasoning to evaluate multiple policies and provide findings through a unified dashboard.

AWS IAM now enforces MFA for root users across all account types
The new Multi-Factor Authentication enforcement prevents over 99% of password-related attacks. You can use a range of supported IAM MFA methods, including FIDO-certified security keys to harden access to your AWS accounts. AWS supports FIDO2 passkeys for a user-friendly MFA implementation and allows you to register up to 8 MFA devices per root and IAM user.

Improve your security posture using Amazon threat intelligence on AWS Network Firewall
This new Network Firewall managed rule group offers protection against active threats relevant to workloads in AWS. The feature uses the Amazon threat intelligence system MadPot to continuously track attack infrastructure, including malware hosting URLs, botnet command and control servers, and crypto mining pools, identifying indicators of compromise (IOCs) for active threats.

AWS Certificate Manager introduces exportable public SSL/TLS certificates to use anywhere
You can now use AWS Certificate Manager to issue exportable public certificates for your AWS, hybrid, or multicloud workloads that require secure TLS traffic termination.

AWS WAF simplified console experience
The new AWS WAF console experience reduces security configuration steps by up to 80% through pre-configured protection packs. Security teams can quickly implement comprehensive protection for specific application types, with consolidated security metrics and customizable controls through an intuitive interface.

Amazon CloudFront simplifies web application delivery and security with new user-friendly interface
Try the simplified console experience with Amazon CloudFront to accelerate and secure web applications within a few clicks by automating TLS certificate provisioning, DNS configuration, and security settings through an integrated interface with AWS WAF’s enhanced Rule Packs.

New AWS Shield feature discovers network security issues before they can be exploited (Preview)
Shield network security posture management automatically discovers and analyzes network resources across AWS accounts, prioritizes security risks based on AWS best practices, and provides actionable remediation recommendations to protect applications against threats like SQL injections and DDoS attacks.

Unify your security with the new AWS Security Hub for risk prioritization and response at scale (Preview)
AWS Security Hub has been enhanced to transform security signals into actionable insights, helping security teams prioritize and respond to critical issues at scale. This unified solution provides comprehensive visibility across your cloud environment while reducing the complexity of managing multiple security tools.

Amazon GuardDuty expands Extended Threat Detection coverage to Amazon EKS clusters
Amazon GuardDuty Extended Threat Detection now supports Amazon EKS clusters, helping you detect sophisticated multistage attacks by correlating security signals across Kubernetes audit logs, runtime behaviors, and AWS API activities. This enhancement automatically identifies critical attack sequences that might otherwise go unnoticed, enabling faster response to threats.

New categories for the AWS MSSP Competency
The AWS MSSP Competency (previously AWS Level 1 MSSP Competency) now includes new categories covering infrastructure security, workload security, application security, data protection, identity and access management, incident response, and cyber recovery. Partners provide 24/7 monitoring and incident response through dedicated Security Operations Centers.

Secure your Express application APIs in minutes with Amazon Verified Permissions
Amazon Verified Permissions announced the release of the verified-permissions-express-toolkit, an open-source package that allows developers to implement authorization for Express web application APIs in minutes using Amazon Verified Permissions.

Beyond compute: Shifting vulnerability detection left with Amazon Inspector code security
Amazon Inspector code security capabilities are now generally available, helping you secure applications before production by rapidly identifying and prioritizing security vulnerabilities and misconfigurations across application source code, dependencies, and infrastructure as code (IaC).

AWS Backup adds new Multi-party approval for logically air-gapped vaults
Multi-party approval for AWS Backup logically air-gapped vaults enables you to recover your backup data even when your AWS account is compromised, by leveraging authorization from a designated approval team of trusted individuals who can enable vault sharing with a recovery account.

Amazon GuardDuty expands Extended Threat Detection coverage to Amazon EKS clusters

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/amazon-guardduty-expands-extended-threat-detection-coverage-to-amazon-eks-clusters/

Today, I’m happy to announce Amazon GuardDuty Extended Threat Detection with expanded coverage for Amazon Elastic Kubernetes Service (Amazon EKS), building upon the capabilities we introduced in our AWS re:Invent 2024 announcement of Amazon GuardDuty Extended Threat Detection: AI/ML attack sequence identification for enhanced cloud security.

Security teams managing Kubernetes workloads often struggle to detect sophisticated multistage attacks that target containerized applications. These attacks can involve container exploitation, privilege escalation, and unauthorized movement within Amazon EKS clusters. Traditional monitoring approaches might detect individual suspicious events, but often miss the broader attack pattern that spans across these different data sources and time periods.

GuardDuty Extended Threat Detection introduces a new critical severity finding type, which automatically correlates security signals across Amazon EKS audit logs, runtime behaviors of processes associated with EKS clusters, malware execution in EKS clusters, and AWS API activity to identify sophisticated attack patterns that might otherwise go unnoticed. For example, GuardDuty can now detect attack sequences in which a threat actor exploits a container application, obtains privileged service account tokens, and then uses these elevated privileges to access sensitive Kubernetes secrets or AWS resources.

This new capability uses GuardDuty correlation algorithms to observe and identify sequences of actions that indicate potential compromise. It evaluates findings across protection plans and other signal sources to identify common and emerging attack patterns. For each attack sequence detected, GuardDuty provides comprehensive details, including potentially impacted resources, timeline of events, actors involved, and indicators used to detect the sequence. The findings also map observed activities to MITRE ATT&CK® tactics and techniques and remediation recommendations based on AWS best practices, helping security teams understand the nature of the threat.

To enable Extended Threat Detection for EKS, you need at least one of these features enabled: EKS Protection or Runtime Monitoring. For maximum detection coverage, we recommend enabling both to enhance detection capabilities. EKS Protection monitors control plane activities through audit logs, and Runtime Monitoring observes behaviors within containers. Together, they create a complete view of your EKS clusters, enabling GuardDuty to detect complex attack patterns.

How it works
To use the new Amazon GuardDuty Extended Threat Detection for EKS clusters, go to the GuardDuty console to enable EKS Protection in your account. From the Region selector in the upper-right corner, select the Region where you want to enable EKS Protection. In the navigation pane, choose EKS Protection. On the EKS Protection page, review the current status and choose Enable. Select Confirm to save your selection.

After it’s enabled, GuardDuty immediately starts monitoring EKS audit logs from your EKS clusters without requiring any additional configuration. GuardDuty consumes these audit logs directly from the EKS control plane through an independent stream, which doesn’t affect any existing logging configurations. For multi-account environments, only the delegated GuardDuty administrator account can enable or disable EKS Protection for member accounts and configure auto-enable settings for new accounts joining the organization.

To enable Runtime Monitoring, choose Runtime Monitoring in the navigation pane. Under the Configuration tab, choose Enable to enable Runtime Monitoring for your account.

Now, you can view from the Summary dashboard the attack sequences and critical findings specifically related to Kubernetes cluster compromise. You can observe that GuardDuty identifies complex attack patterns in Kubernetes environments, such as credential compromise events and suspicious activities within EKS clusters. The visual representation of findings by severity, resource impact, and attack types gives you a holistic view of your Amazon EKS security posture. This means you can prioritize the most critical threats to your containerized workloads.

The Finding details page provides visibility into complex attack sequences targeting EKS clusters, helping you understand the full scope of potential compromises. GuardDuty correlates signals into a timeline, mapping observed behaviors to MITRE ATT&CK® tactics and techniques such as account manipulation, resource hijacking, and privilege escalation. This granular level of insight reveals exactly how attackers progress through your Amazon EKS environment. It identifies affected resources like EKS workloads and service accounts. The detailed breakdown of indicators, actors, and endpoints provides you with actionable context to understand attack patterns, determine impact, and prioritize remediation efforts. By consolidating these security insights into a cohesive view, you can quickly assess the severity of Amazon EKS security incidents, reduce investigation time, and implement targeted countermeasures to protect your containerized applications.

The Resources section of the Finding details page shows context about the specific assets affected during an attack sequence. This unified resource list provides you with visibility into the exact scope of the compromise—from the initial access to the targeted Kubernetes components. Because GuardDuty includes detailed attributes such as resource types, identifiers, creation dates, and namespace information, you can rapidly assess which components of your containerized infrastructure require immediate attention. This focused approach eliminates guesswork during incident response, so you can prioritize remediation efforts on the most critical affected resources and minimize the potential blast radius of Amazon EKS targeted attacks.

Now available
Amazon GuardDuty Extended Threat Detection with expanded coverage for Amazon EKS clusters provides comprehensive security monitoring across your Kubernetes environment. You can use this capability to detect sophisticated multistage attacks by correlating events across different data sources, identifying attack sequences that traditional monitoring might miss.

To start using this expanded coverage, enable EKS Protection in your GuardDuty settings and consider adding Runtime Monitoring for enhanced detection capabilities.

For more information about this new capability, refer to the Amazon GuardDuty Documentation.

— Esra

Unify your security with the new AWS Security Hub for risk prioritization and response at scale (Preview)

Post Syndicated from Donnie Prakoso original https://aws.amazon.com/blogs/aws/unify-your-security-with-the-new-aws-security-hub-for-risk-prioritization-and-response-at-scale-preview/

AWS Security Hub has been a central place for you to view and aggregate security alerts and compliance status across Amazon Web Services (AWS) accounts. Today, we are announcing the preview release of the new AWS Security Hub which offers additional correlation, contextualization, and visualization capabilities. This helps you prioritize critical security issues, respond at scale to reduce risks, improve team productivity, and better protect your cloud environment.

Here’s a quick look at the new AWS Security Hub.

With this new enhancement, AWS Security Hub integrates security capabilities like Amazon GuardDuty, Amazon Inspector, AWS Security Hub Cloud Security Posture Management (CSPM), Amazon Macie, and other AWS security capabilities to help you gain visibility across your cloud environment through centralized management in a unified cloud security solution. 

Getting started with the new AWS Security Hub
Let me walk you through how to get started with AWS Security Hub.

If you’re a new customer to AWS Security Hub, you need to navigate to the AWS Security Hub console to enable AWS security capabilities and capabilities and start assessing risk across your organization. You can learn more on the Documentation page.

After you have AWS Security Hub enabled, it will automatically consume data from supporting security capabilities you’ve enabled, such as Amazon GuardDuty, Amazon Inspector, Amazon Macie, and AWS Security Hub CSPM. You can navigate to the AWS Security Hub console to view these findings and benefit from insights created through correlation of findings across these capabilities.

As security risks are uncovered, they’re presented in a redesigned Security Hub summary dashboard. The new Security Hub summary dashboard provides a comprehensive, unified view of your AWS security posture. The dashboard organizes security findings into distinct categories, making it easier to identify and prioritize risks.

The new Exposure summary widget helps you identify and prioritize security exposures by analyzing resource relationships and signals from Amazon Inspector, AWS Security Hub CSPM, and Amazon Macie. These exposure findings are automatically generated and are a key part of the new solution, highlighting where your critical security exposures are located. You can learn more about exposure on the Documentation page.

AWS Security Hub now provides a Security coverage widget designed to help you identify potential coverage gaps. You can use this widget to identify where you’re missing coverage by the security capabilities that power Security Hub. This visibility helps you identify which capabilities, accounts, and features you need to address to improve your security coverage.

As you can see on the navigation menu, AWS Security Hub is organized into five key areas to streamline security management:

  • Exposure: Provides visibility into all exposure findings, a security vulnerability or misconfiguration that could potentially expose an AWS resource or system to unauthorized access or compromise, generated by Security Hub, helping you identify resources that might be accessible from outside your environment
  • Threats: Consolidates all threat findings generated by Amazon GuardDuty, showing potential malicious activities and intrusion attempts
  • Vulnerabilities: Displays all vulnerabilities detected by Amazon Inspector, highlighting software flaws and configuration issues
  • Posture management: Shows all posture management findings from AWS Security Hub Cloud Security Posture Management (CSPM), helping provide compliance with security best practices
  • Sensitive data: Presents all sensitive data findings identified by Amazon Macie, helping you track and protect your sensitive information

When you navigate to the Exposure page, you’ll see findings grouped by title, with severity levels clearly indicated to help you focus on critical issues first.

To explore specific exposures, you can select any finding to see affected resources. The panel includes key information about the implicated resource, account, Region, and when the issue was detected.

In this panel, you’ll also find an attack path visualization that is particularly useful for understanding complex security relationships. For network exposure paths, you can see all components involved in the path—including virtual private clouds (VPCs), subnets, security groups, network access control lists (ACLs), and load balancers—helping you identify exactly where to implement security controls. The visualization also highlights Identity and Access Management (IAM) relationships, showing how permission configurations might allow privilege escalation or data access. Resources with multiple contributing traits are clearly marked so you can quickly identify which components represent the greatest risk.

The Threats dashboard provides actionable insights into potential malicious activities detected by Amazon GuardDuty, organizing findings by severity so you can quickly identify critical issues like unusual API calls, suspicious network traffic, or potential credential compromises. The dashboard includes GuardDuty Extended Threat Detection findings, with all “Critical” severity threats representing these Extended Threat Detections that require immediate attention.

Similarly, the Vulnerabilities dashboard from Amazon Inspector provides a comprehensive view of software vulnerabilities and network exposure risks. The dashboard highlights vulnerabilities with known exploits, packages requiring urgent updates, and resources with the highest numbers of vulnerabilities.

Another valuable new feature is the Resources view, which provides an inventory of all resources deployed in your organization covered by AWS Security Hub. You can use this view to quickly identify which resources have findings against them and filter by resource type or finding severity. Selecting any resource provides detailed configuration information without needing to pivot to other consoles, streamlining your investigation workflow.

The new Security Hub also offers integration capabilities to help you comprehensively monitor your cloud environments and connect with third-party security solutions. This gives you the flexibility to create a unified security solution tailored to your organization’s specific needs.

For example, with integration capability, when viewing a security finding, you can select the Create ticket option and choose your preferred ticketing integration.

Additional things to know
Here are a couple of things to note:

  • Availability – During this preview period, the new AWS Security Hub is available in following AWS Regions: US East (N. Virginia, Ohio), US West (N. California, Oregon), Africa (Cape Town), Asia Pacific (Hong Kong, Jakarta, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Canada (Central), Europe (Frankfurt, Ireland, London, Milan, Paris, Stockholm), Middle East (Bahrain), and South America (São Paulo).
  • Pricing – The new AWS Security Hub is available at no additional charge during the preview period. However, you will still incur costs for the integrated capabilities including Amazon GuardDuty, Amazon Inspector, Amazon Macie, and AWS Security Hub CSPM.
  • Integration with existing AWS security capabilities – Security Hub integrates with Amazon GuardDuty, Amazon Inspector, AWS Security Hub CSPM, and Amazon Macie, providing a comprehensive security posture without additional operational overhead.
  • Enhanced data interoperability – The new Security Hub uses the Open Cybersecurity Schema Framework (OCSF), enabling seamless data exchange across your security capabilities with normalized data formats.

To learn more about the enhanced AWS Security Hub and join the preview, visit the AWS Security Hub product page.

Happy building!

— Donnie

AWS Backup adds new Multi-party approval for logically air-gapped vaults

Post Syndicated from Veliswa Boya original https://aws.amazon.com/blogs/aws/aws-backup-adds-new-multi-party-approval-for-logically-air-gapped-vaults/

Today, we’re announcing the general availability of a new capability that integrates AWS Backup logically air-gapped vaults with Multi-party approval to provide access to your backups even when your AWS account is inaccessible due to inadvertent or malicious events. AWS Backup is a fully managed service that centralizes and automates data protection across AWS services and hybrid workloads. It provides core data protection features, ransomware recovery capabilities, and compliance insights and analytics for data protection policies and operations.

As a backup administrator, you use AWS Backup logically air-gapped vaults to securely share backups across accounts and organizations, logically isolate your backup storage, and support direct restore to help reduce recovery time following an inadvertent or malicious event. However, if a bad or unintended actor gains root access to your backup account or the management account of your organization, your backups suddenly become inaccessible, even though they’re still safely stored in the logically air-gapped vault. While traditional account recovery involved working through support channels, AWS Backup with Multi-party approval delivers immediate access to recovery tools, empowering you with faster resolution times and greater control over your recovery timeline.

Multi-party approval for AWS Backup logically air-gapped vaults adds an additional layer of protection for you to recover your application data even when your AWS account becomes completely inaccessible. Using Multi-party approval, you can create approval teams which consist of highly trusted individuals in your organization, then associate them with your logically air-gapped vault. If you get locked out of your AWS accounts due to inadvertent or malicious actions, you can request your own approval team to authorize sharing of your vault from any account, even those outside your AWS Organizations account. Once approved, you gain authorized access to your backups and can begin your recovery process.

How it works
Multi-party approval for AWS Backup logically air-gapped vaults combines the security of logically air-gapped vaults with the governance of Multi-party approval to create a recovery mechanism that works even when your AWS account is compromised. Here’s how it works:

1. Approval team creation
First, you create an approval team in your AWS Organizations management account. If the management account is new, first create an AWS Identity and Access Management (IAM) Identity Center instance before creating the approval team. The approval team consists of trusted individuals (IAM Identity Center users) who will be authorized to approve vault sharing requests. Each approver receives an invitation to join the approval team through a new Approval portal.

2. Vault association
When your approval team is active, you share it with accounts that own logically air-gapped vaults using AWS Resource Access Manager (AWS RAM) to safeguard against requests for approval from arbitrary accounts. Backup administrators can then associate this approval team with new or existing logically air-gapped vaults.

3. Protection against compromise
If your AWS account becomes compromised or inaccessible, you can request access to your backups from a different account (a clean recovery account). This request includes the Amazon Resource Name (ARN) of the logically air-gapped vault in the format arn:aws:backup:<region>:<account>:backup-vault:<name> and an optional vault name and comment.

4. Multi-party approval
The request is sent to the approval team, who review it through the approval portal. When the minimum required number of approvers authorize the request, the vault is automatically shared with the requesting account. All requests and approvals are comprehensively logged in AWS CloudTrail.

5. Recovery process
With access granted, you can immediately start restoring or copying your data in the new recovery account without waiting for your compromised account to be remediated.

This approach provides an entirely separate authentication path to access and recover your backups, completely independent of your AWS account credentials. Even if the bad actor has root access to your account, they can’t prevent the approval team-based recovery process.

1. Create a new logically air-gapped vault
To create a new logically air-gapped vault, provide a name, tags (optional), and vault lock properties.

2. Assign an approval team
When the vault has been created, choose Assign approval team to assign it with an existing approval team.

Choose an existing approval team from the drop-down menu then select Submit to finalize the assignment.

Now your approval team is assigned to your logically air-gapped vault.

Good to know
It’s essential to test your recovery process before an actual emergency:

  1. From a different AWS account, use the AWS Backup console or API to request sharing of your logically air-gapped vault by providing the vault ID and ARN.
  2. Request approval of your request from the approval team.
  3. Once approved, verify that you can access and restore backups from the vault in your testing account.

As a best practice, monitor the health of your approval team regularly using AWS Backup Audit Manager to ensure they have sufficient active participants to meet your approval threshold.

Multi-party approval for enhanced cloud governance
Today, we’re also announcing the general availability of a new capability that AWS account administrators can use to add Multi-party approval to their product offerings. As highlighted in this post, AWS Backup is the first service to integrate this capability. With Multi-party approval, administrators can enable application owners to guard sensitive service operations with a distributed review process.

Good to know
Multi-party approval provides several significant security advantages:

  • Distributed decision-making, eliminating single points of failure
  • Full auditability through AWS CloudTrail integration
  • Protection against compromised credentials
  • Formal governance for compliance-sensitive operations
  • Consistent approval experience across integrated services

Now available

Multi-party approval is available today in all AWS Regions where AWS Organizations is available. Multi-party approval for AWS Backup logically air-gapped vaults is available in all AWS Regions where AWS Backup is available.

– Veliswa.

New AWS Shield feature discovers network security issues before they can be exploited (Preview)

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/new-aws-shield-feature-discovers-network-security-issues-before-they-can-be-exploited-preview/

Today, I’m happy to announce AWS Shield network security director (preview), a capability that simplifies identification of configuration issues related to threats such as SQL injections and distributed denial of service (DDoS) events, and proposes remediations. This feature identifies and analyzes network resources, connections, and configurations. It compares them against AWS best practices to create a network topology that highlights resources requiring protection.

Organizations today face significant challenges in maintaining a robust network security posture. Security teams often struggle to efficiently discover all resources in their environments, understand how these resources are interconnected, and identify which security services are currently configured. Additionally, they find determining how well resources are configured relative to AWS best practices requires considerable expertise and effort. Many teams find it difficult to identify which network security services and rule sets would best protect their applications from common and emerging threats.

AWS Shield network security director addresses these challenges through three key capabilities. First, it performs comprehensive analysis to discover resources across your AWS accounts, identify connectivity between resources, and determine which network security services and configurations are currently in place. Second, it prioritizes resources by severity level based on AWS network security best practices and threat intelligence. Finally, it provides specific remediation recommendations such as step-by-step instructions for implementing the right AWS security services, including AWS WAF, Amazon Virtual Private Cloud (Amazon VPC) security groups, and Amazon VPC network access control lists (ACLs) to protect your resources.

The service supports critical network security use cases, including protecting applications against internet-born threats and controlling human access to resources based on port, protocol, or IP address range. It provides network analysis to discover assets and delivers analysis that eliminates time-consuming manual processes for identifying resources that need protection. The service offers resource prioritization by assigning security findings a severity level based on network context and adherence to AWS best practices, helping you focus on what matters most. Additionally, it supplies actionable recommendations with specific guidance on which services and configurations will address each security gap. You can also get answers, in natural language, from AWS Shield network security director from within Amazon Q Developer in the AWS Management Console and chat applications.

Getting started with AWS Shield network security director
To use AWS Shield network security director, I need to initiate a network analysis of my AWS resources. I go to the AWS WAF & Shield console and choose Getting started under AWS Shield network security director in the navigation pane. I choose Get started, which takes me to the configuration page. On this page, I can choose how to perform my first network analysis: I can assess findings from across all supported Regions or from my current Region only. I select Start network analysis.

After the analysis is completed, the dashboard page shows a breakdown of resource types by severity level and the most common categories of network security findings associated with their resources. Resources are categorized by type and severity level (critical, high, medium, low, informational), making it easy to identify which areas need immediate attention.

Next, I explore the Resources section to understand the distribution of my assets and filter by severity level in my environment. I can use Resource overview to review a specific severity level, which will redirect me to the Resources under Network security director with the associated severity level filter. I choose the resources that have Medium severity level.

I choose a specific resource to view its network topology map showing how it connects to other resources and associated findings. This visualization helps me understand the potential impact of security configurations and identify exposed paths. I review detailed findings such as “Allows unrestricted inbound access (0.0.0.0/0) on all ports” with severity ratings.

Next, I go to Findings under Network security director, which shows common configuration issues. For each finding, I receive detailed information and recommended remediation steps. The service rates the severity of findings (high, medium, low) to help me prioritize my response. Critical-severity findings such as “CloudFront origin is also internet accessible without CloudFront protections” or high-severity findings such as “Allows unrestricted inbound access (0.0.0.0/0) on all ports” are presented first, followed by medium- and low-severity issues.

You can analyze your network security configurations, in natural language, with AWS Shield network security director within Amazon Q Developer in the AWS Management Console and chat applications. For example, you can say “Do I have any network security issues on my CloudFront distributions?” or “Are any of my resources vulnerable to bots and scrapers?” This integration helps security teams quickly understand their security posture and receive guidance on implementing best practices without having to navigate through extensive documentation.

To explore this capability, I ask “What are my most critical network security issues?” in the Explore with Amazon Q section. Amazon Q analyzes my network security configuration and generates a response based on the security assessment of my AWS environment.

With this comprehensive view of your network security, you can now make data-driven decisions to strengthen your defenses against emerging threats.

Join the preview
AWS Shield network security director is available in the US East (N. Virginia) and Europe (Stockholm) Regions. The Amazon Q Developer capability to analyze network security configurations is available in preview in US East (N. Virginia). To begin strengthening your network security, visit the AWS Shield network security director console and initiate your first network security analysis.

For more information, visit the AWS Shield product page.

— Esra

Amazon CloudFront simplifies web application delivery and security with new user-friendly interface

Post Syndicated from Micah Walter original https://aws.amazon.com/blogs/aws/amazon-cloudfront-simplifies-web-application-delivery-and-security-with-new-user-friendly-interface/

Today, we’re announcing a new simplified onboarding experience for Amazon CloudFront that developers can use to accelerate and secure their web applications in seconds. This new experience, along with improvements to the AWS WAF console experience, makes it easier than ever for developers to configure content delivery and security services without requiring deep technical expertise.

Setting up content delivery and security for web applications traditionally required navigating multiple Amazon Web Services (AWS) services and making numerous configuration decisions. With this new CloudFront onboarding experience, developers can now create a fully configured distribution with DNS and a TLS certificate in just a few clicks.

Amazon CloudFront offers compelling benefits for organizations of all sizes looking to deliver content and applications globally. As a content delivery network (CDN), CloudFront significantly improves application performance by serving content from edge locations closest to your users, reducing latency and improving user experience. Beyond performance, CloudFront provides built-in security features that protect your applications from distributed denial of service (DDoS) attacks and other threats at the edge, preventing malicious traffic from reaching your origin infrastructure. The service automatically scales with your traffic demands without requiring any manual intervention, handling both planned and unexpected traffic spikes with ease. Whether you’re running a small website or a large-scale application, the CloudFront integration with other AWS services and the new simplified console experience makes it easier than ever to implement these essential capabilities for your web applications.

Streamlined CloudFront configuration

The new CloudFront console experience guides developers through a simplified workflow that starts with the domain name they want to use for their distribution. When using Amazon Route 53, the experience automatically handles TLS certificate provisioning and DNS record configuration, while incorporating security best practices by default. This unified approach eliminates the need to switch between multiple services like AWS Certificate Manager, Route 53, and AWS WAF, and offers developers a faster time to production without the need to dive deep on the nuanced configuration options of each service.

For example, a developer can now create a secure CloudFront distribution for their applications fronted by a load balancer by entering their domain name and selecting their load balancer as the origin. The console automatically recommends optimal CDN and security configurations based on the application type and requirements, and developers can deploy with confidence knowing they’re following AWS best practices.

For developers who wish to host a static website on Amazon Simple Storage Service (Amazon S3), CloudFront provides several important benefits. First, it improves your website’s performance by caching content at edge locations closer to your users, reducing latency and improving page load times. Second, it helps protect your S3 bucket by acting as a security layer—CloudFront can be configured to be the only way to access your content, preventing direct access to your S3 bucket. The new experience automatically configures these security best practices for you.

Enhanced security integration with AWS WAF

Complementing the new CloudFront experience, we’re also introducing an improved AWS WAF console that features intelligent Rule Packs—curated sets of security rules based on application type and security requirements. These Rule Packs enable developers to implement comprehensive security controls without needing to be security experts.

When creating a CloudFront distribution, developers can now enable AWS WAF protection through an integrated experience that uses these new Rule Packs. The console provides clear recommendations for security configurations that developers can use to preview and validate their settings before deployment.

Web applications face numerous security threats today, including SQL injection attacks, cross-site scripting (XSS), and other OWASP Top 10 vulnerabilities. With the new AWS WAF integration, you automatically get protection against these common attack vectors. The recommended Rule Packs provide immediate protection against malicious bot traffic, common web exploits, and known bad actors while preventing direct-to-origin attacks that could overwhelm your infrastructure.

Let’s take a look

If you’ve ever created an Amazon CloudFront distribution, you’ll immediately notice that things have changed. The new experience is straightforward to follow and understand. For my example, I chose to create a distribution for a static website using Amazon S3 as my origin.

New onboarding experience for Amazon CloudFront

In Step 1, I give my distribution a name and select from Single website or app or the new Multi-tenant architecture option, which I can use to configure distributions that use multiple domains but share a common configuration. I choose Single website or app and enter an optional domain name. With the new experience, I can use the Check domain button to verify I have my domain as a Route 53 zone file.

Next, I select the origin for the distribution, which is where CloudFront will fetch the content to serve and cache. For my Origin type, I select Amazon S3. As the preceding screenshot shows, there are several additional options to choose from. Each of the options is designed to make configuration as straightforward as possible for the most popular use cases. Next, I select my S3 bucket, either by typing in the bucket name or using the Browse S3 button.

Next, I have several settings related to using Amazon S3 as my origin. The Grant CloudFront access to origin option is an important one. This option (selected by default) will update my S3 bucket policy to allow CloudFront to access my bucket and will configure my bucket for origin access control. This way, I can use a completely private bucket and know that assets in my bucket can only be accessed through CloudFront. This is a critical step to keeping my bucket and assets secure.

In the next step, I’m presented with the option to configure AWS WAF. With AWS WAF enabled, my web servers are better protected because it inspects each incoming request for potential threats before allowing them to make their way to my web servers. There is a cost to enabling AWS WAF, and as you can see in the following screenshot, there is a calculator to help estimate additional charges.

New onboarding experience for Amazon CloudFront

Now available

The new CloudFront onboarding experience and enhanced AWS WAF console are available today in all AWS Regions where these services are offered. You can start using these new features through the AWS Management Console. There are no additional charges for using these new experiences—you pay only for the CloudFront and AWS WAF resources you use, based on their respective pricing models.

To learn more about the new CloudFront onboarding experience and AWS WAF improvements, visit the Amazon CloudFront Documentation and AWS WAF Documentation. Start building faster, more secure web applications today with these simplified experiences.

AWS Certificate Manager introduces exportable public SSL/TLS certificates to use anywhere

Post Syndicated from Channy Yun (윤석찬) original https://aws.amazon.com/blogs/aws/aws-certificate-manager-introduces-exportable-public-ssl-tls-certificates-to-use-anywhere/

Today, we’re announcing exportable public SSL/TLS certificates from AWS Certificate Manager (ACM). Prior to this launch, you can issue your public certificates or import certificates issued by third-party certificate authorities (CAs) at no additional cost, and deploy them with integrated AWS services such as Elastic Load Balancing (ELB), Amazon CloudFront distribution, and Amazon API Gateway.

Now you can export public certificates from ACM, get access to the private keys, and use them on any workloads running on Amazon Elastic Compute Cloud (Amazon EC2) instances, containers, or on-premises hosts. The exportable public certificate are valid for 395 days. There is a charge at time of issuance, and again at time of renewal. Public certificates exported from ACM are issued by Amazon Trust Services and are widely trusted by commonly used platforms such as Apple and Microsoft and popular web browsers such as Google Chrome and Mozilla Firefox.

ACM exportable public certificates in action
To export a public certificate, you first request a new exportable public certificate. You cannot export previously created public certificates.

To get started, choose Request certificate in the ACM console and choose Enable export in the Allow export section. If you select Disable export, the private key for this certificate will be disallowed for exporting from ACM and this cannot be changed after certificate issuance.

You can also use the request-certificate command to request a public exportable certificate with Export=ENABLED option on the AWS Command Line Interface (AWS CLI).

aws acm request-certificate \
--domain-name mydomain.com \
--key-algorithm EC_Prime256v1 \
--validation-method DNS \
--idempotency-token <token> \
--options \
CertificateTransparencyLoggingPreference=DISABLED \
Export=ENABLED

After you request the public certificate, you must validate your domain name to prove that you own or control the domain for which you are requesting the certificate. The certificate is typically issued within seconds after successful domain validation.

When the certificate enters status Issued, you can export your issued public certificate by choosing Export.

Export your public certificate

Enter a passphrase for encrypting the private key. You will need the passphrase later to decrypt the private key. To get the public key, Choose Generate PEM Encoding.

You can copy the PEM encoded certificate, certificate chain, and private key or download each to a separate file.

Download PEM keys

You can use the export-certificate command to export a public certificate and private key. For added security, use a file editor to store your passphrase and output keys to a file to prevent being stored in the command history.

aws acm export-certificate \
     --certificate-arn arn:aws:acm:us-east-1:<accountID>:certificate/<certificateID> \
     --passphrase fileb://path-to-passphrase-file \
     | jq -r '"\(.Certificate)\(.CertificateChain)\(.PrivateKey)"' \
     > /tmp/export.txt

You can now use the exported public certificates for any workload that requires SSL/TLS communication such as Amazon EC2 instances. To learn more, visit Configure SSL/TLS on Amazon Linux in your EC2 instances.

Things to know
Here are a couple of things to know about exportable public certificates:

  • Key security – An administrator of your organization can set AWS IAM policies to authorize roles and users who can request exportable public certificates. ACM users who have current rights to issue a certificate will automatically get rights to issue an exportable certificate. ACM admins can also manage the certificates and take actions such as revoking or deleting the certificates. You should protect exported private keys using secure storage and access controls.
  • Revocation – You may need to revoke exportable public certificates to comply with your organization’s policies or mitigate key compromise. You can only revoke the certificates that were previously exported. The certificate revocation process is global and permanent. Once revoked, you can’t retrieve revoked certificates to reuse. To learn more, visit Revoke a public certificate in the AWS documentation.
  • Renewal – You can configure automatic renewal events for exportable public certificates by Amazon EventBridge to monitor certificate renewals and create automation to handle certificate deployment when renewals occur. To learn more, visit Using Amazon EventBridge in the AWS documentation. You can also renew these certificates on-demand. When you renew the certificates, you’re charged for a new certificate issuance. To learn more, visit Force certificate renewal in the AWS documentation.

Now available
You can now issue exportable public certificates from ACM and export the certificate with the private keys to use other compute workloads as well as ELB, Amazon CloudFront, and Amazon API Gateway.

You are subject to additional charges for an exportable public certificate when you create it with ACM. It costs $15 per fully qualified domain name and $149 per wildcard domain name. You only pay once during the lifetime of the certificate and will be charged again only when the certificate renews. To learn more, visit the AWS Certificate Manager Service Pricing page.

Give ACM exportable public certificates a try in the ACM console. To learn more, visit the ACM Documentation page and send feedback to AWS re:Post for ACM or through your usual AWS Support contacts.

— Channy

Verify internal access to critical AWS resources with new IAM Access Analyzer capabilities

Post Syndicated from Micah Walter original https://aws.amazon.com/blogs/aws/verify-internal-access-to-critical-aws-resources-with-new-iam-access-analyzer-capabilities/

Today, we’re announcing a new capability in AWS IAM Access Analyzer that helps security teams verify which AWS Identity and Access Management (IAM) roles and users have access to their critical AWS resources. This new feature provides comprehensive visibility into access granted from within your Amazon Web Services (AWS) organization, complementing the existing external access analysis.

Security teams in regulated industries, such as financial services and healthcare, need to verify access to sensitive data stores like Amazon Simple Storage Service (Amazon S3) buckets containing credit card information or healthcare records. Previously, teams had to invest considerable time and resources conducting manual reviews of AWS Identity and Access Management (IAM) policies or rely on pattern-matching tools to understand internal access patterns.

The new IAM Access Analyzer internal access findings identify who within your AWS organization has access to your critical AWS resources. It uses automated reasoning to collectively evaluate multiple policies, including service control policies (SCPs), resource control policies (RCPs), and identity-based policies, and generates findings when a user or role has access to your S3 buckets, Amazon DynamoDB tables, or Amazon Relational Database Service (Amazon RDS) snapshots. The findings are aggregated in a unified dashboard, simplifying access review and management. You can use Amazon EventBridge to automatically notify development teams of new findings to remove unintended access. Internal access findings provide security teams with the visibility to strengthen access controls on their critical resources and help compliance teams demonstrate access control audit requirements.

Let’s try it out

To begin using this new capability, you can enable IAM Access Analyzer to monitor specific resources using the AWS Management Console. Navigate to IAM and select Analyzer settings under the Access reports section of the left-hand navigation menu. From here, select Create analyzer.

Screenshot of creating an Analyzer in the AWS Console

From the Create analyzer page, select the option of Resource analysis – Internal access. Under Analyzer details, you can customize your analyzer’s name to whatever you prefer or use the automatically generated name. Next, you need to select your Zone of trust. If your account is the management account for an AWS organization, you can choose to monitor resources across all accounts within your organization or the current account you’re logged in to. If your account is a member account of an AWS organization or a standalone account, then you can monitor resources within your account.

The zone of trust also determines which IAM roles and users are considered in scope for analysis. An organization zone of trust analyzer evaluates all IAM roles and users in the organization for potential access to a resource, whereas an account zone of trust only evaluates the IAM roles and users in that account.

For this first example, we assume our account is the management account and create an analyzer with the organization as the zone of trust.

Screenshot of creating an Analyzer in the AWS Console

Next, we need to select the resources we wish to analyze. Selecting Add resources gives us three options. Let’s first examine how we can select resources by identifying the account and resource type for analysis.

Screenshot of creating an Analyzer in the AWS Console

You can use Add resources by account dialog to choose resource types through a new interface. Here, we select All supported resource types and select the accounts we wish to monitor. This will create an analyzer that monitors all supported resource types. You can either select accounts through the organization structure (shown in the following screenshot) or paste in account IDs using the Enter AWS account ID option.

Screenshot of creating an Analyzer in the AWS Console

You can also choose to use the Define specific resource types dialog, which you can use to pick from a list of supported resource types (as shown in the following screenshot). By creating an analyzer with this configuration, IAM Access Analyzer will continually monitor both existing and new resources of the selected type within the account, checking for internal access.

Screenshot of creating an Analyzer in the AWS Console

After you’ve completed your selections, choose Add resources.

Screenshot of creating an Analyzer in the AWS Console

Alternatively, you can use the Add resources by resource ARN option.

Screenshot of creating an Analyzer in the AWS Console

Or you can use the Add resources by uploading a CSV file option to configure monitoring a list of specific resources at scale.

Screenshot of creating an Analyzer in the AWS Console

After you’ve completed the creation of your analyzer, IAM Access Analyzer will analyze policies daily and generate findings that show access granted to IAM roles and users within your organization. The updated IAM Access Analyzer dashboard now provides a resource-centric view. The Active findings section summarizes access into three distinct categories: public access, external access outside of the organization (requires creation of a separate external access analyzer), and access within the organization. The Key resources section highlights the top resources with active findings across the three categories. You can see a list of all analyzed resources by selecting View all active findings or Resource analysis on the left-hand navigation menu.

Screenshot of Access Analyzer findings

On the Resource analysis page, you can filter the list of all analyzed resources for further analysis.

Screenshot of creating an Analyzer in the AWS Console

When you select a specific resource, any available external access and internal access findings are listed on the Resource details page. Use this feature to evaluate all possible access to your selected resource. For each finding, IAM Access Analyzer provides you with detailed information about allowed IAM actions and their conditions, including the impact of any applicable SCPs and RCPs. This means you can verify that access is appropriately restricted and meets least-privilege requirements.

Screenshot of creating an Analyzer in the AWS Console

Pricing and availability

This new IAM Access Analyzer capability is available today in all commercial Regions. Pricing is based on the number of critical AWS resources monitored per month. External access analysis remains available at no additional charge. Pricing for EventBridge applies separately.

To learn more about IAM Access Analyzer and get started with analyzing internal access to your critical resources, visit the IAM Access Analyzer documentation.

Building identity-first security: A guide to the Identity and Access Management track at AWS re:Inforce 2025

Post Syndicated from Rahul Sahni original https://aws.amazon.com/blogs/security/building-identity-first-security-a-guide-to-the-identity-and-access-management-track-at-aws-reinforce-2025/

AWS re:Inforce 2025: June 16-18 in Philadelphia, PA
Join us at AWS re:Inforce 2025 from June 16 to 18 as we dive deep into identity and access management, where we’ll explore how organizations are securing identities at scale. As the traditional security perimeter continues to dissolve in our hybrid and multi-cloud world, this year’s sessions showcase how AWS customers are building comprehensive identity-centric security strategies that span workforce and customer identities. From authenticating and authorizing human and machine identities to implementing least privilege access controls and securing identities that help drive AI adoption, you’ll discover practical approaches to modernizing your identity architecture.

Whether you’re managing enterprise workforce identities across complex organizational structures or building customer-facing applications that require seamless and secure authentication experiences, the Identity and Access Management track offers insights for every security professional. We’ve carefully curated sessions that address today’s most pressing identity challenges, including zero trust implementation patterns, unified workforce identity management across cloud and on-premises environments, and scalable customer identity and access management (CIAM) solutions. Through technical deep-dives, hands-on workshops, and customer case studies, you’ll learn how to use AWS Identity and Access Management (IAM), AWS IAM Identity Center, AWS Directory Services, Amazon Cognito, and other AWS services to build robust identity foundations that support both security and business agility.

In this post, we highlight some of the key sessions. With over 30 sessions dedicated to identity management, we feature valuable learnings for executives and practitioners alike. Let AWS experts and partners share practical challenges and solutions with you. Let’s explore what you can expect at this year’s conference.

Zero trust and principle of least privilege

IAM304 | Breakout session | Empowering developers to implement least-privilege IAM permissions
Wolters Kluwer, a global provider of professional information, software solutions, and services and GoTo Technologies (formerly LogMeIn Inc.), a U.S.-based software company that provides cloud-based remote work tools for collaboration and IT management use AWS IAM Access Analyzer to simplify and accelerate their journey to least privilege. Join this session to learn more about their use cases and their journey to empower their builders to refine IAM policies to remove excessive permissions. Gain insights into their strategies, best practices, and lessons learned for continuously monitoring unused permissions across their organization and building processes to streamline remediations.

IAM343 | Code talk | Scale Beyond RBAC: Transform App Access Control using AVP & Cedar
This session focuses on transforming an existing application from role-based access control (RBAC) to policy-based access control (PBAC) using Amazon Verified Permissions (AVP) and Cedar policy. The drive for least privilege has led to role explosion in RBAC model and necessitates a shift towards PBAC, augmenting RBAC with attribute-based access control (ABAC). You will learn how to move authorization logic out of application code and implementing a centralized PBAC model. Attendees will also learn to define permissions as policies using Cedar and seamlessly migrate from RBAC to PBAC with minimal application logic changes, enabling more granular and scalable access control.

Securing Identities in the AI era

IAM373 | Workshop | Identity without barriers: user-aware access for AWS analytics services
This hands-on workshop explores AWS IAM Identity Center’s Trusted Identity Propagation, teaching participants how to enable secure identity propagation across integrated applications. Through practical exercises, attendees will learn to configure identity propagation and use it with services such as Amazon Redshift, Amazon Athena, Amazon Q Business, and more. Participants will gain experience with cross-account scenarios, audit logging configuration, and troubleshooting common integration challenges. You must bring your laptop to participate.

IAM321 | Lightning talk | Building trust in Agentic AI through authentication and access control
AI agents execute tasks for humans, operating independently with or without human presence, while collaborating seamlessly across on-premise and multi-cloud environments. This dynamic setup poses unique challenges in human/agent authentication, identity propagation/delegation, and resource authorization. Leverage Amazon Cognito, Verified Permissions, and Bedrock to master effective Identity and Access Management (IAM) for your AI agents. Through real-world examples using OAuth2-based identity management, machine-to-machine authentication, and policy-based access control, you’ll unlock the ability to scale complex agent interactions securely, empowering you to build robust, scalable Agentic AI solutions.

IAM441 | Code Talk | The Right Way to Secure AI Agents with Code Examples
GenAI agents run tasks on behalf of human users with or without users being present, and often interact with each other across on-premise and different cloud providers. This brings new challenges in identity authentication, propagation, delegation, and resource authorization in the overall agentic AI solution. Learn how Amazon Cognito’s OAuth2-based identity management, machine-to-machine authentication, combined with Amazon Verified Permission’s fine-grained authorization can enable secure delegation patterns for AI agents, while preserving human identity and consent, agent machine identity, and other request context throughout the agent chain. We’ll walk through real-world examples with agents built on Amazon Bedrock or other frameworks.

Workforce identity management

IAM302 | Breakout session | Workforce identity for gen AI and analytics
Managing secure, consistent workforce access for generative AI and analytics is critical for unlocking innovation while protecting sensitive data. In this demo-filled session, you’ll see how centralized identity management and trusted identity propagation can deliver a user-centric data access experience. You’ll also learn how AWS IAM Identity Center simplifies access to AWS services such as Amazon Redshift, Amazon Athena, and AWS Lake Formation, while enabling fine-grained access to data based on user identity to help meet your security and compliance needs.

IAM341 | Code Talk | Visualizing Workforce Identity: Graph-Based Analysis for Access Rights
Discover how to gain deep insights into workforce identity relationships and resource access patterns by visualizing AWS IAM Identity Center data using graph databases. Learn how you can explore complex identity relationships, permission inheritance and resource access across your organization; get practical approaches to ingestion of identity data, creating graph queries for security analysis, and building visualization dashboards to help identify potential resource access risks. We’ll explore real-world scenarios for detecting excessive permissions, analyzing group memberships and resource access, and tracking resource access rights changes over time to strengthen your identity security posture.

Customer and Machine identity management

IAM332 | Chalk Talk | Securing and monitoring machine identities with Amazon Cognito
Unlock the power of secure machine-to-machine (M2M) authorization using Amazon Cognito’s OAuth2 client credentials flow. This session dives deep into implementing M2M authorization, featuring real-world optimization strategies for both security and cost. Learn essential security best practices, multi-tenant reference architectures, and monitoring techniques that ensure your M2M usage remains efficient and secure. Whether you’re building microservices, handling API authorization, or scaling your distributed systems, this session will equip you with actionable insights and patterns for successful M2M implementations. Bring your challenges and questions for an interactive discussion on Cognito-powered M2M authorization.

IAM372 | Workshop | Building CIAM Solutions with Amazon Cognito
Learn how to use Amazon Cognito for your solutions’ CIAM needs. Use hands on examples to build fully functional solutions and see some of the new features in action like the new Managed Login UI, Passwordless logins now supported natively and more.

AWS identity foundation

IAM305 | Breakout session | Establishing a data perimeter on AWS, featuring Block, Inc.
Organizations are storing an unprecedented and increasing amount of data on AWS for a range of use cases including data lakes, analytics, machine learning, and enterprise applications. They want to make sure that sensitive non-public data is protected from unintended access. In this session, dive deep into the controls that you can use to create a data perimeter to help ensure that only your trusted identities are accessing trusted resources from expected networks. Hear from Block, Inc. a leading fintech company about how they use data perimeter controls in their AWS environment to meet their security objectives.

IAM451 | Builders session | Securing GenAI Apps: Fine-Grained Access Control for Amazon Bedrock Agents
Want to secure GenAI applications accessing your organizational data? Learn how to implement intelligent access controls for Amazon Bedrock-powered applications accessing your organizational data. In this builder’s session, you’ll build a defense-in-depth approach that combines authentication using Amazon Cognito and fine-grained authorization with Amazon Verified Permissions to secure access for Bedrock AI Agents. Implement layered permissions that protect sensitive data without limiting your GenAI capabilities.

Conclusion

As organizations continue to navigate the complexities of modern identity architecture, implementing a robust IAM framework remains critical for maintaining security posture while enabling seamless access across hybrid environments. The disappearance of the identity perimeter and the shift towards identity-first security demands a more sophisticated approach to authentication and authorization workflows, making continuous validation and adaptive access policies paramount. The community at re:inforce, strives to provide you with solutions, tactics, and strategies that you can use to propel your business forward.

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

Rahul Sahni

Rahul Sahni

Rahul is a Senior Product Marketing Manager at AWS Security. An avid Amazonian, Rahul embodies the company’s principle of Learn and Be Curious in both his professional and personal life. With a passion for continuous learning, he thrives on new experiences and adventures. Outside of his professional work, he enjoys experimenting with new dishes from around the world.

Apruva More

Apruva More

Apurva is a part of the AWS Security, Identity, and Compliance team, with 14 years of experience in global product marketing across both startups and large enterprises. Known for her expertise in market positioning, competitive analysis, and customer insights, she has launched products that resonate with target audiences and drive revenue growth, while collaborating cross-functionally to align product vision with market needs and business goals.

Building secure foundations: A guide to network and infrastructure security at AWS re:Inforce 2025

Post Syndicated from Brandon Carroll original https://aws.amazon.com/blogs/security/building-secure-foundations-a-guide-to-network-and-infrastructure-security-at-aws-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.

Securing cloud infrastructure has never been more critical as organizations continue to expand their digital footprint and embrace modern architectures. At AWS re:Inforce 2025, the Network and Infrastructure Security track brings together security experts, practitioners, and industry leaders to share insights on building and maintaining secure, automated, and observable cloud foundations.This year’s track focuses on several key themes that are shaping the future of cloud security. Learn how to implement comprehensive defense-in-depth strategies through multiple layers of controls, from perimeter to workload protection. Discover the latest approaches to network visibility and inspection, including tools and architectures for deep packet inspection and enhanced traffic analysis across cloud environments.As organizations scale their cloud presence, automated policy management becomes crucial. This track showcases solutions and approaches for scaling security policy deployment, management, and compliance validation through automation and infrastructure as code (IaC). You’ll also dive deep into zero trust infrastructure implementations, exploring frameworks for identity-based network segmentation and access controls aligned with zero trust principles.With the growing complexity of distributed applications, protecting workloads across cloud, edge, and hybrid environments requires integrated security architectures. Sessions in this track demonstrate how to build comprehensive protection strategies that secure your entire infrastructure footprint while maintaining operational excellence.

Whether you’re just beginning your cloud security journey or leading mature enterprise security initiatives, the Network and Infrastructure Security track at re:Inforce 2025 will equip you with practical guidance and actionable insights to advance your organization’s security posture. Join in on the fun, and register for re:Inforce 2025!

Breakout sessions, chalk talks, and lightning talks

Breakout sessions are lecture-style, 1-hour sessions delivered by AWS experts, customers, and partners—perfect for deepening your knowledge on important topics, gaining actionable insights, and connecting with industry leaders.

Chalk talks are 1-hour long, highly interactive sessions with a small audience. This format is ideal for diving deep into specific topics, engaging directly with AWS experts, and getting your questions answered in real time.

Lightning talks are short (20 minutes) theater presentations dedicated to a specific customer story, service demo, or AWS Partner offering.

NIS301 | Breakout session | Egress control deployments made easy
Speakers: Sofía Aluma (AWS), Jesse Lepich (AWS)
Discover the latest AWS Network Firewall features that simplify implementation and enhance your security posture. In this hands-on workshop, learn how recent updates to AWS Network Firewall and Amazon Route 53 Resolver DNS Firewall streamline deployment, reduce threat exposure, and strengthen security policies. We’ll share practical recommendations for configuring firewall rules that match your specific use cases and help verify that your security controls meet intended objectives.

NIS302 | Breakout session | How Itaú Bank leverages AWS Shield Advanced to combat DDoS events
Speakers: Douglas Lopes (AWS), Guilherme Greco (AWS), Ricardo Donadel (Itaú Bank)
Learn how Itaú, Latin America’s largest bank, uses AWS Shield Advanced to protect their critical financial infrastructure from sophisticated DDoS events. In this session, Itaú’s security team shares how they architected their defense strategy by integrating Shield Advanced with existing security operations and collaborating with the AWS DDoS Response Team. Discover how they maintain robust protection while meeting financial regulatory requirements and examine the business value of their implementation. Whether you work in financial services or other regulated industries, you’ll gain actionable insights for enterprise-grade DDoS protection.

NIS303 | Breakout session | Thinking beyond traditional firewalling architectures
Speakers: Tom Adamski (AWS), Ankit Chadha (AWS)
In this session, we’ll discuss a brave new world where we think beyond traditional firewalling architectures. We’ll explore the use-cases that require firewalls including workload-to-workload, client-to-workload, and workload-to-internet traffic flows. After defining the use cases, we’ll discuss AWS services that allow customers to retain their desired security posture without inserting inline firewalls. We’ll wrap with specific considerations on when firewalling is a good option. For example, for scenarios when customers require AppId-like functionality, or for creating data loss prevention (DLP) deployments for egress traffic.

NIS304 | Breakout session | Integrate Zero Trust into your cloud network
Speakers: Dave DeRicco (AWS)
In this session, learn how to adopt Zero Trust alongside traditional network security functions such as firewalls and VPNs. Explore how services like Amazon VPC Lattice and AWS Verified Access complement your existing network security posture by leveraging identity and network controls to continuously authenticate and monitor access. and how these services can integrate into your existing network architecture. Learn about common adoption approaches and migration patterns and hear best practices for building Zero Trust mechanisms into a secure, modern network architecture.

NIS305 | Breakout session | Advanced network defense: From basics to global scale with AWS Cloud WAN
Speakers: Sidhartha Chauhan (AWS)
Starting with core security principles, this session demonstrates how to build robust network security architectures in AWS. Learn to establish effective network isolation boundaries using AWS Cloud WAN and AWS PrivateLink, followed by implementing traffic filtering through strategic firewall deployments. We’ll compare centralized versus distributed inspection architectures, culminating in how AWS Cloud WAN’s service insertion and policy-based approach enables global-scale centralized inspection flows. Through practical scenarios, attendees will master designing scalable network security architectures that maintain security posture across complex cloud environments. Ideal for security engineers and architects managing enterprise-scale AWS deployments.

DAP332 | Chalk talk | Executive perspective: Risk management for generative AI workloads
Speakers: Jason Garman (AWS) & Mark Ryland (AWS)
Don’t let the perceived complexity of responsible AI keep you from deploying generative AI applications on AWS. In this chalk talk, we will present a framework for breaking down AI safety and security risks, introduce AWS best practices for keeping enterprise data secure in generative AI applications using zero trust principles, and mitigate safety risks using technologies such as Amazon Bedrock Guardrails. Discover as a group with fellow security leaders how to identify safety and security risks relevant to your workload, implement appropriate mitigation strategies, and measure efficacy over time.

NIS306 | Breakout session | Securing AWS networks: Observability meets defense-in-depth
Speakers: Anandprasanna Gaitonde (AWS), Ankush Goyal (AWS), Amish Shah (AWS)
AWS customers use multiple security services to build strong network defenses, but visibility into threats, misconfigurations, and vulnerabilities across multi-VPC and multi-account environments can remain a challenge. This session covers AWS network security fundamentals – Security Groups, NACLs, AWS Network Firewall, DNS Firewall, and Gateway Load Balancer—for a layered defense strategy. We will also highlight observability tools like VPC Flow Logs, Reachability Analyzer, and Network Access Analyzer to detect security gaps and troubleshoot access issues. By integrating these tools, organizations can proactively enhance network security, detect vulnerabilities, and ensure secure, scalable architectures across AWS accounts and environments.

NIS231 | Chalk talk | High noon duel: Live events tamed by AWS WAF
Speakers: Tzoori Tamam (AWS), Harith Gaddamanugu (AWS)
In this thrilling session, we’ll build a robust protection setup using AWS WAF and Amazon CloudFront, demonstrating how to fend off increasingly sophisticated live events. Learn to leverage Amazon CloudFront, configure rate-based rules, implement AWS WAF Managed Rule groups, bot control, and create custom defenses. As we construct our digital fortress, our resident “black hat” will launch progressively complex events, showcasing how each layer of defense performs under pressure. Suitable for both newcomers and experienced AWS security professionals.

NIS331 | Chalk talk | Enhance your cloud security infrastructure using Zero Trust techniques
Speakers: Pablo Sánchez Carmona (AWS), Adam Palmer (AWS)
Traditional perimeter-based security and network segmentation often fall short in today’s dynamic microservices environments, creating operational overhead and potential security gaps. Join us in this session to discuss how to evolve beyond conventional security models by implementing Zero Trust architecture in AWS. We will cover different services and techniques such as AWS Verified Access in the human-to-application connectivity, Amazon VPC Lattice for service-to-service communication, and the use of AWS Verified Permissions for fine-grained application authorization. We’ll explore how these services can work together to enable continuous authentication.

NIS332 | Chalk talk | Build secure connectivity with Amazon VPC Lattice and AWS PrivateLink
Speakers: Alexandra Huides (AWS), Jordan Rojas Garcia (AWS)
In this chalk talk, we review the best practices and reference architectures for building secure connectivity with Amazon VPC Lattice and AWS PrivateLink. We focus on service and resource oriented connectivity as we dive into the new VPC Lattice capabilities, such as support for VPC Resources and service network endpoints, and cross-region support for AWS PrivateLink.

NIS333 | Chalk talk | Build defense-in-depth network designs to safeguard apps and data
Speakers: Raghavarao Sodabathina (AWS), Brian Soper (AWS)
Strong adherence to architecture best practices and proactive controls are the foundation of web application security. These techniques allow developers to build applications that are more resilient. In this chalk talk, learn how to build a layered network security approach to achieve defense-in-depth; to protect, detect, and respond to issues faster; and to accelerate your secure migrations to AWS. Discover key considerations, best practices, and reference architectures that include Amazon VPC, Amazon Route 53, Amazon CloudFront, AWS WAF, AWS Shield, Application Load Balancer, and AWS Elastic Disaster Recovery to achieve your defense-in-depth objectives.

NIS431 | Chalk talk | Cloud network defense: Advanced visibility and analysis on AWS
Speakers: Kyle Hanrahan (AWS), Anand Kumar Mandilwar (AWS)
Organizations struggle to maintain comprehensive network visibility in complex cloud environments. This session demonstrates how to implement advanced network monitoring and analysis using AWS’s native services. Learn to leverage VPC Flow Logs, AWS Network Firewall Logs, Route 53 Resolver Logs, AWS WAF Logs and other data sources for traffic analysis. Discover practical implementation of tools for enhanced security and real-time monitoring. Walk away with reference architectures and best practices for building robust network visibility solutions that scale across your AWS environment while maintaining performance. Perfect for security teams modernizing their network defense strategy.

NIS321 | Lightning talk | How Meta enabled secure egress patterns using AWS Network Firewall
Speakers: Syed Shareef (AWS), Robin Rodriguez (AWS)
Meta envisions 2025 as the breakthrough year for its leading AI assistant, aiming to reach over 1 billion people with highly intelligent and personalized interactions. Partnering with AWS, Meta has made substantial investments in AI infrastructure, providing its developers with specialized compute resources for AI training. To secure this ambitious initiative, Meta has had to evolve not just their cloud security but also culture and mindset to secure a growing AWS footprint/infrastructure. Meta leverages AWS Network Firewall (ANF) to centrally inspect and filter VPC traffic before reaching external destinations, using rule-based filtering to control domain access, block malicious IPs, and prevent data exfiltration.

NIS322 | Lightning talk | I didn’t know Network Firewall could do that!
Speakers: Brandon Carroll (AWS), Mary Kay Sondecker (AWS)
This lightning talk will uncover powerful yet often overlooked capabilities that can transform your network security game. In just 20 minutes, we’ll speed through eye-opening features including flow capture and flush operations, advanced Suricata rule capabilities, dynamic packet filtering tricks, and lesser-known integration patterns that even experienced practitioners might have missed. From stateful traffic manipulation to sophisticated protocol inspection and real-world architectural patterns, you’ll discover practical techniques to leverage AWS Network Firewall’s full potential. Whether you’re managing complex multi-account deployments or hunting for advanced threats, this rapid-fire session will equip you with new tools for your security arsenal.

NIS323 | Lightning talk | WAF logs to security gold: A 20-minute dashboard revolution
Speakers: Emmanuel Isimah (AWS), Victor Babasanmi (AWS)
Drowning in AWS WAF logs? Transform raw security data into actionable insights with Amazon CloudWatch dashboards. In this high-energy session, discover how to build powerful visualizations that expose threats in real-time. We’ll cut through the complexity to show you battle-tested patterns for threat detection and alerting that security teams love. Twenty minutes to level up your WAF monitoring game – no fluff, just results.

NIS421 | Lightning talk | VPN-less access to AWS private services with AWS Verified Access
Speakers: John Sol (AWS), Mike Cornstubble (AWS)
In hybrid environments where employees need to access a file server outside their corporate network, they typically use a VPN. This session demonstrates how to establish secure, VPN-free connectivity to an Amazon FSx for Windows File Server using the new TCP protocol support of AWS Verified Access (AVA). Learn how AVA provides fine-grained access controls using AWS.

Interactive sessions (builders’ sessions, code talks, and workshops)

Interact with small groups led by an AWS expert providing interactive learning about how to build on AWS. Each builders’ session begins with a short explanation or demonstration of what attendees are building, then it’s your turn to build! The expert guides you end-to-end through this hands-on experience. Or join code talks, our code-focused interactive sessions where AWS experts lead a discussion featuring live coding or code samples as they illuminate the why behind AWS solutions. Attendees are encouraged to ask questions and follow along.

Workshops are 2-hour interactive sessions where you collaborate in teams or work individually to solve real-world challenges by using AWS services, making them perfect for hands-on learning. Each workshop begins with a brief lecture, followed by dedicated time to work through the problem.

Note: Don’t forget to bring your laptop to build alongside AWS experts.

NIS251 | Builders’ session | Build dashboards to gain visibility into your network perimeter
Speakers: Victor Babasanmi (AWS), Tom Adamski (AWS), Todd Pula (AWS), Vamsi Manthapuram (AWS)
Effective network security requires comprehensive visibility into your security posture and traffic patterns. This hands-on session demonstrates how to build and customize Amazon CloudWatch dashboards for real-time insights into AWS Network Firewall operations. Learn to visualize critical metrics including dropped packets, traffic patterns, and potential threats. We’ll explore creating dynamic widgets to track stateful rule matches, analyze top talkers, and identify suspicious patterns. Through step-by-step guidance, discover how to monitor bandwidth utilization, track rule effectiveness, and create custom alarms. Leave with ready-to-implement templates for enhancing your security operations. You must bring your laptop to participate.

NIS252 | Builders’ session | Mastering Amazon VPC Block Public Access for secure cloud networks
Speakers: Ankush Goyal (AWS), Salman Ahmed (AWS), Kunj Thacker (AWS)>, Ravi Kumar (AWS)
Join this interactive workshop to explore Amazon VPC Block Public Access, a feature designed for secure, scalable cloud environments. Learn to block ingress and egress traffic, enforce compliance, and configure granular exclusions for public and private subnets, with a focus on both IPv4 and IPv6 traffic. Through practical labs, you’ll enable Block Public Access, create exclusions, and use Reachability Analyzer to test connectivity before and after enabling the feature. By the end, you’ll be equipped to secure VPCs effectively while maintaining flexibility for modern workloads. You must bring your laptop to participate.

NIS351 | Builders’ session | Streamlining DNS resource sharing across multiple VPCs and accounts
Speakers: Aanchal Agrawal (AWS), Anushree Shetty (AWS), Mike Torro (AWS), Tyler Pack (AWS)
Amazon Route 53 Profiles is an innovative feature of Route 53 that enables the effortless sharing of hosted zones, resolver rules, and DNS firewall rules across multiple VPCs. This builders’ session will guide you through the process of creating Route 53 profiles and demonstrate how to restrict access using various features tailored to your specific needs, such as different environments. You must bring your laptop to participate.

NIS352 | Builders’ session | Accessing private VPC resources using CloudFront VPC origin
Speakers: Anushree Shetty (AWS), Ramya Mikkilineni (AWS), Aanchal Agrawal (AWS), Anjana Krishnan (AWS)
You can now privately access Amazon VPC resources, including load balancers and Amazon Elastic Compute Cloude (Amazon EC2) instances, and restrict these resources to be only accessed via Amazon CloudFront distribution through a new feature in CloudFront. In this builders’ session, we will set up a website located in a private subnet and access it via a CloudFront distribution. You must bring your laptop to participate.

NIS353 | Builders’ session | Scaling threat prevention on AWS with Suricata
Speakers: Ivo Pinto (AWS), Jesse Lepich (AWS), Michael Leighty (AWS), Miguel Silva (AWS)
Suricata is an open-source network intrusion prevention system (IPS) that includes a standard rule-based language for stateful network traffic inspection. AWS Network Firewall lets you define rules to inspect and control traffic to and from your VPC using IP, port, protocol, domain names, and general pattern matches. Building rules, in this format, for your security needs can be challenging but rewarding. During this session you will learn how you can utilize Suricata-compatible rules in AWS Network Firewall and build rulesets for common use cases as well as complex scenarios. You must bring your laptop to participate.

NIS354 | Builders’ session | Use AWS PrivateLink to set up private access to Amazon Bedrock
Speakers: Akshay Karanth (AWS), Du’An Lightfoot (AWS), Mike Gillespie (AWS), Salman Ahmed (AWS)
When building generative AI applications using Large Language Models on Amazon Bedrock, customers want to generate responses without going over the public internet or without exposing your proprietary data. This builders’ session introduces the Amazon Bedrock VPC endpoint, powered by AWS PrivateLink, as a solution for establishing secure and private connections between customer VPCs and Amazon Bedrock services. You’ll learn how this technology enables communication without public IP addresses, mitigating potential threat vectors from internet exposure. We’ll cover security challenges in generative AI, the architecture of VPC endpoint solution, and hands-on labs for implementation. You must bring your laptop to participate.

NIS451 | Builders’ session | Troubleshooting real-world perimeter protection scenarios
Speakers: Tzoori Tamam (AWS), Manuel Pata (AWS), Kaustubh Phatak (AWS)
Suspicious of an activity spike? Seeing odd traffic patterns? Introduced a new AWS WAF rule and want to make sure it is operating as it should? Join this session for a walkthrough of a day in the life of a security engineer operating AWS WAF, reviewing dashboards, exploring data in the logs, and building new dashboard widgets to make your life easier. You must bring your laptop to participate.

NIS341 | Code talk | A deep dive into Amazon VPC Lattice granular security
Speakers: Pablo Sánchez Carmona (AWS), Cristobal Lopez Callejon (AWS)
Join us for a session exploring Amazon VPC Lattice’s security capabilities and fine-grained access controls. We’ll explore authentication mechanisms, authorization policies, and service-level permissions that enable precise control over network traffic between services. You’ll learn how to leverage authorization policies in VPC Lattice to create layered security controls, and see practical examples of implementing Zero Trust principles within your application network. The session will cover best practices for auditing and monitoring service-to-service communications, managing cross-account access, and implementing security patterns for microservices architectures.

NIS342 | Code talk | Sticky situations: Building advanced AWS WAF honeypots for better security
Speakers: Harith Gaddamanugu (AWS), Manuel Pata (AWS)
Discover how to transform AWS WAF into a powerful threat intelligence platform by building sophisticated honeypots that attract, analyze, and adapt to emerging threats. In this code talk, we’ll demonstrate how to combine AWS WAF with AWS Lambda functions to create intelligent traps that not only capture malicious activity but also generate actionable security insights. Through live coding demonstrations, you’ll learn to implement advanced honeypot techniques including dynamic bait generation, automated attacker profiling, and real-time threat pattern analysis.

NIS231 | Chalk talk | High noon duel: Live events tamed by AWS WAF
Speakers: Tzoori Tamam (AWS), Harith Gaddamanugu (AWS)
In this thrilling session, we’ll build a robust protection setup using AWS WAF and Amazon CloudFront, demonstrating how to fend off increasingly sophisticated live attacks. Learn to leverage CloudFront, configure rate-based rules, implement WAF-managed rules and bot control, and create custom defenses. As we construct our digital fortress, our resident “black hat” will launch progressively complex attacks, showcasing how each layer of defense performs under pressure. Suitable for both newcomers and experienced AWS security professionals.

NIS331 | Chalk talk | Enhance your cloud security infrastructure using Zero Trust techniques
Speakers: Pablo Sánchez Carmona (AWS), Adam Palmer (AWS)
Traditional perimeter-based security and network segmentation often fall short in today’s dynamic microservices environments, creating operational overhead and potential security gaps. Join us in this session to discuss how to evolve beyond conventional security models by implementing Zero Trust architecture in AWS. We will cover different services and techniques such as AWS Verified Access in the human-to-application connectivity, Amazon VPC Lattice for service-to-service communication, and the use of AWS Verified Permissions for fine-grained application authorization. We’ll explore how these services can work together to enable continuous authentication.

NIS332 | Chalk talk | Build secure connectivity with Amazon VPC Lattice and AWS PrivateLink
Speakers: Alexandra Huides (AWS), Jordan Rojas Garcia (AWS)
In this chalk talk, we review the best practices and reference architectures for building secure connectivity with Amazon VPC Lattice and AWS PrivateLink. We focus on service and resource oriented connectivity as we dive into the new VPC Lattice capabilities, such as support for VPC Resources and service network endpoints, and cross-Region support for AWS PrivateLink.

NIS333 | Chalk talk | Build defense-in-depth network designs to safeguard apps and data
Speakers: Raghavarao Sodabathina (AWS), Brian Soper (AWS)
Strong adherence to architecture best practices and proactive controls are the foundation of web application security. These techniques allow developers to build applications that are more resilient. In this chalk talk, learn how to build a layered network security approach to achieve defense-in-depth; to protect, detect, and respond to issues faster; and to accelerate your secure migrations to AWS. Discover key considerations, best practices, and reference architectures that include Amazon VPC, Amazon Route 53, Amazon CloudFront, AWS WAF, AWS Shield, Application Load Balancer, and AWS Elastic Disaster Recovery to achieve your defense-in-depth objectives.

NIS431 | Chalk talk | Cloud network defense: Advanced visibility and analysis on AWS
Speakers: Kyle Hanrahan (AWS), Anand Kumar Mandilwar (AWS)
Organizations struggle to maintain comprehensive network visibility in complex cloud environments. This session demonstrates how to implement advanced network monitoring and analysis using AWS’s native services. Learn to leverage VPC Flow Logs, AWS Network Firewall Logs, Route 53 Resolver Logs, WAF Logs and other data sources for traffic analysis. Discover practical implementation of tools for enhanced security and real-time monitoring. Walk away with reference architectures and best practices for building robust network visibility solutions that scale across your AWS environment while maintaining performance. Perfect for security teams modernizing their network defense strategy.

Register Now

Don’t miss this opportunity to learn from industry experts and AWS leaders about building secure, automated, and observable cloud foundations. Register for AWS re:Inforce 2025 today to reserve your spot in these Network and Infrastructure Security sessions covering everything from Zero Trust implementations to advanced DDoS protection, network visibility, and defense-in-depth strategies. Browse the full re:Inforce catalog to explore additional tracks, partner sessions, and code talks that can complement your network security journey.

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

Brandon Carroll

Brandon Carroll

Brandon is a Senior Product Marketing Manager with AWS who helps customers understand and implement robust cloud security solutions. At AWS, Brandon translates complex security concepts into actionable guidance, helping organizations successfully implement AWS security services while providing clear paths for getting started with cloud security.

A deep dive into data protection sessions at AWS re:Inforce 2025

Post Syndicated from Rahul Sahni original https://aws.amazon.com/blogs/security/a-deep-dive-into-data-protection-sessions-at-aws-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.

At Amazon Web Services (AWS), security is our top priority. We’re excited to announce the Data Protection track at AWS re:Inforce 2025, happening June 16–18, where we’ll explore how customers use AWS to push their innovation boundaries while protecting data in the age of quantum, AI, and digital sovereignty. This year’s sessions will spotlight innovative approaches to next-generation cryptography, trusted AI, privacy-enhancing technologies, and emerging best practices for safeguarding information across the entire data lifecycle.

The Data Protection track offers insights and practical guidance for organizations of all sizes, whether you’re new to AWS or an experienced security professional. We’ve carefully curated sessions that address today’s most pressing challenges, including regulatory compliance, cross-border data transfers, and protecting data in multi-cloud environments. From hands-on workshops about implementing encryption and data classification at scale to deep-dive technical sessions on the latest AWS data protection services, you’ll find content designed to help you build and maintain a robust data protection strategy.

In this post, we highlight key sessions that feature lecture-style presentations with real-world customer use cases, along with interactive small-group sessions led by AWS experts who will guide you through practical problems and solutions. Let’s explore what you can expect at this year’s conference.

Data access and management

DAP471-R1 | Workshop | Defend against ransomware with data defense, recovery, and response
Ransomware and malware can disrupt business applications. In this expert-level workshop, you will learn how to apply AWS Backup locking mechanisms, logically air-gapped vaults, and restore testing to help strengthen your cyber recovery posture. Experience hands-on configuration of air-gapped, immutable vaults and automated recovery point testing to meet your enterprise’s objectives. Explore how these features can be combined to build a comprehensive, recovery-focused data protection strategy to withstand evolving cyber threats. You must bring your laptop to participate.

Cryptography and post-quantum

DAP472 | Workshop | Examining hybrid post-quantum TLS key exchanges
This workshop provides a practical exploration of post-quantum cryptography, comparing its performance against classical algorithms and demonstrating real-world implementation using AWS services. You will learn how to establish quantum-safe tunnels using AWS Key Management Service (AWS KMS) and AWS SDK for Java v2, implementing hybrid post-quantum TLS for secure data transfer. The session covers critical aspects including CPU and bandwidth performance metrics of post-quantum key exchange algorithms, modifications to TLS handshake protocols, and integration with AWS Transfer Family. Hands-on demonstrations will illustrate how to protect sensitive communications against both current and future quantum computing threats through hybrid classical/quantum-resistant approaches. You must bring your laptop to participate.

DAP452 | Builders’ session | Cryptographic controls with AWS CloudHSM
Gain hands-on experience implementing strong cryptographic controls using AWS CloudHSM. Learn to deploy TLS offload with Nginx, integrate Windows code signing, and create custom key stores. Explore monitoring cryptographic key usage within FIPS 140-3 level 3 hardware security modules (HSMs), using the latest high-performance hsm2m.medium HSM types. This session shows how these advancements help you strengthen your security posture, meet stringent compliance requirements, simplify operational management, and scale your cryptographic operations to support growing workloads—all while maintaining the performance your applications demand. You must bring your laptop to participate.

Data migration and modernization

DAP302 | Breakout session | Fannie Mae’s practical path to modern PKI and certificate management
Explore Fannie Mae’s transformation of their public key infrastructure (PKI) from a legacy system to a cloud-native solution on AWS. This session details their phased migration strategy, addressing challenges such as decentralized trust store updates and securing buy-in from application teams. Learn how Fannie Mae overcame migration hurdles, including legacy dependencies and compliance requirements, to achieve 100 percent adoption while maintaining security and reducing certificate-related overhead. Gain insights into cost optimization, risk mitigation, and architectural best practices for enterprise-scale certificate management in the cloud. This presentation offers actionable strategies for organizations undertaking similar PKI modernization efforts. Finally, we share the latest in enterprise-scale certificate management in the cloud.

DAP322 | Lightning talk | How Monzo Bank protects critical workloads using AWS Nitro Enclaves
Monzo Bank deploys security-critical applications requiring a high level of assurance around code integrity, system hardening, and limited attack surface. They achieved this using reproducible builds and the cryptographic attestation and isolated compute environment provided by AWS Nitro Enclaves. In this talk, we describe the challenges they overcame in building and deploying production workloads using this approach and share what they learned along the way.

Data protection for AI

DAP201 | Breakout session | Veradigm’s security-first approach to amplifying potential with GenAI
How can organizations empower teams with generative AI capabilities while maintaining rigorous data security standards responsibly? Veradigm initially hesitated to adopt generative AI because of data privacy, security, and regulatory compliance concerns. Join Veradigm’s principal developer for internal AI solutions to discover how they implemented practical security measures to build and deploy a compliant generative AI assistant using Amazon Bedrock that enhanced their team capabilities while strengthening their security posture. Learn about essential security controls, architectural decisions, and valuable lessons learned from successfully implementing AI for employees operating in a highly regulated environment.

DAP332 | Chalk talk | Executive perspective: Risk management for generative AI workloads
Don’t let the perceived complexity of responsible AI keep you from deploying generative AI applications on AWS. In this chalk talk, we present a framework for breaking down AI safety and security risks, introduce AWS best practices for keeping enterprise data secure in generative AI applications using zero trust principles, and mitigate safety risks using technologies such as Amazon Bedrock Guardrails. Discover as a group with fellow security leaders how to identify safety and security risks relevant to your workload, implement appropriate mitigation strategies, and measure efficacy over time.

DAP371 | Workshop | Defend your AI: Mitigate prompt injection with Amazon Bedrock
Master the art of identifying and mitigating prompt injection vulnerabilities in generative AI systems through this hands-on workshop. Using Amazon Bedrock, you will explore both offensive and defensive prompt engineering techniques to understand the security implications of large language models in production environments. In this session, you learn how prompt injection attacks work, complete an interactive capture the flag style challenge attempting to exploit a simulated AI environment, and learn how to implement defensive controls using Amazon Bedrock Guardrails. You must bring your laptop to participate.

Data protection and compliance at scale

DAP331-R | Chalk talk | Architecting a secrets management strategy that scales
Dive deep into architectural patterns for enterprise secrets management in cloud-native environments. In this session, we dissect the implementation complexities of centralized versus decentralized secrets management and discuss the trade-offs between these patterns, including their impact on developer velocity, security, and operational overhead. You will learn how to use AWS services to implement a flexible secrets management strategy and manage secrets lifecycle that balances the needs of developers and security teams. We also cover best practices for centralized compliance and auditing regardless of your chosen architecture.

DAP202 | Breakout session | Navigating sovereignty requirements: Architectures and solutions on AWS
Evolving data protection regulations and digital sovereignty requirements mean that organizations are facing increasingly complex compliance requirements when using cloud capabilities. This breakout session explores practical architectural approaches for meeting sovereignty requirements on AWS, with a focus on European and global regulatory frameworks. We examine key architectural patterns that enable data residency control, operational transparency, and sovereign workload isolation. The session covers the AWS Sovereignty Pledge, including sovereign design best practices, as well as the upcoming AWS European Sovereign Cloud.

Advanced seat reservation

If you’re a registered attendee, you can secure your spot in sessions through reserved seating. To reserve your seat, sign in to the attendee portal, go to Event, and then select Sessions. Act quickly to make sure you get a place in your preferred sessions.

Conclusion

Whether you’re a security architect seeking to modernize your defenses or a security executive aiming to elevate your organization’s security posture to drive faster business growth, re:Inforce is your essential destination. With a roster of carefully vetted and certified AWS speakers, you can be confident that every moment at the conference will provide valuable insights and actionable strategies. Join us at re:Inforce to empower your team, protect your assets, and propel your business forward in the digital age.

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

Rahul Sahni

Rahul Sahni

Rahul is a Senior Product Marketing Manager at AWS Security. An avid Amazonian, Rahul embodies the company’s principle of Learn and Be Curious in both his professional and personal life. With a passion for continuous learning, he thrives on new experiences and adventures. Outside of his professional work, he enjoys experimenting with new dishes from around the world.

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.

Elevate your AI security: Must-see re:Inforce 2025 sessions

Post Syndicated from Margaret Jonson original https://aws.amazon.com/blogs/security/reinforce-2025-genai-sessions/

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.

From proof of concepts to large scale production deployments, the rapid advancement of generative AI has ushered in unique opportunities for innovation, but it also introduces a new set of security challenges (and opportunities) that organizations must address. How do you protect retrieval-augmented generation (RAG) or training data while maintaining model effectiveness? What controls are needed for large language model (LLM) interactions? How can I take full advantage of AI agents and model context protocol (MCP) while minimizing risk? At AWS re:Inforce 2025, we’re bringing together security experts, practitioners, and industry leaders to answer these questions with real-world, prescriptive guidance and more.

This year, our generative AI security sessions have been specifically curated and designed to help you build and maintain secure, production AI systems at scale. Whether you’re just beginning your AI security journey or leading mature, enterprise-wide AI initiatives, you’ll find deep practical guidance, hands-on experience, and strategic insights to advance your organization’s security posture.

From foundational concepts to advanced defensive techniques, these sessions encompass critical areas including data protection, model security, identity management, and AI agent resilience. You’ll learn directly from AWS security experts, customers who have successfully implemented secure AI systems, and industry leading partners who are setting new standards in AI safety and security.

In this blog, we highlight some “can’t miss” sessions that cover how to secure AI, but also how security practitioners can leverage AI to help with their critical security missions as well! Join in on the fun, and register for re:Inforce 2025!

Innovation talk

Engage with top AWS executives in our Innovation Talks series, where you’ll gain invaluable insights into the forefront of cloud technology. Explore the latest advancements in generative AI, discover robust cloud security strategies, and uncover pioneering architectural concepts that are revolutionizing application development and expanding the possibilities of the AWS Cloud.

SEC301 | Innovation Talk | From possibility to production: A strong, flexible foundation for AI security
Speakers: Hart Rossman (AWS) & Becky Weiss (AWS)
Discover how AWS removes the heavy lifting of AI security, enabling you to accelerate from development to production. This session reveals how the proven AWS security foundation, combined with flexible controls and automated reasoning, helps organizations confidently deploy AI innovations. Through real-world examples, learn how to transform security from a potential roadblock into an innovation enabler. Leave with practical guidance for securing AI workloads today and strategic insights into addressing emerging security challenges, including data security and agentic AI. Learn how the AWS approach to AI security helps you start ahead while maintaining strong security controls.

Breakout sessions, chalk talks, and lightning talks

Breakout sessions are lecture-style, one-hour sessions delivered by AWS experts, customers, and partners—perfect for deepening your knowledge on important topics, gaining actionable insights, and connecting with industry leaders.

Chalk talks are one-hour long, highly interactive sessions with a small audience. This format is ideal for diving deep into specific topics, engaging directly with AWS experts, and getting your questions answered in real time.

Lightning talks are short (20 minute) theater presentations dedicated to a specific customer story, service demo, or AWS Partner offering.

SEC303 | Breakout session | Behind the shields: AWS and Anthropic’s approach to secure AI
Speakers: Matt Saner (AWS) & Shahzeb Jiwani (Anthropic)
Enterprise AI adoption demands robust security. In this session, Join Anthropic’s head of risk governance along with AWS security leaders to reveal how AWS and Anthropic collaborate to deliver enterprise-grade security for LLMs and the generative AI workloads they enable. Learn about the multi-layered security approach spanning infrastructure, data, and models. We’ll explore real-world security architectures, governance frameworks, and risk mitigation strategies. You will leave with a deeper understanding of how to leverage AWS and Anthropic’s security capabilities to accelerate your organization’s AI initiatives while maintaining stringent security and compliance requirements.

SEC304 | Breakout session | Amazon.com testing frameworks and tools for GenAI security and privacy
Speakers: Alex Torres (AWS), Josh Haycraft (Amazon), & Jess Clark (Amazon)
GenAI solutions are launching in a unique, rapidly-shifting security landscape: they may be trained on customer data, they may integrate with internal services or datastores, and they will provide generated content to customers or to other systems. Learn how Amazon.com creates toolkits, systems and frameworks to leverage Large Language Models and Generative AI to enrich customer interactions to promote agility and innovation.

TDR301 | Breakout session | Innovations in AWS detection and response for integrated security outcomes
Speakers: Himanshu Verma (AWS) & Ryan Holland (AWS)
Discover how the latest AWS detection and response capabilities can help secure your cloud environment more effectively. Learn practical ways to achieve integrated security outcomes through enhanced threat detection, automated vulnerability management, and streamlined response – all at scale. We’ll show you how to use AWS security services to protect workloads and data, centralize security monitoring, manage security posture continuously, and unify security data, while leveraging generative AI for security operations. Walk away with actionable insights on integrating AWS detection and response services to strengthen and simplify your security across AWS.

SEC431 | Chalk talk | Dive deep into data protection architectures for Amazon Bedrock Agents
Speakers: Andrew Kane (AWS) & Gabrielle Dompreh (AWS)
Join this chalk talk to understand how Amazon Bedrock protects your data across Agents and related features, such as Knowledge Bases and Guardrails. Learn about security considerations for cross-region deployments, multi-agent collaboration, and prompt caching. Gain deep insights into architecting secure generative AI solutions that maintain data protection, and discover architectural patterns that keep your applications safe and secure.

APS231 | Chalk talk | Using AWS services to mitigate the OWASP Top 10 for LLM threats
Speakers: Mark Keating (AWS) & Cameron Smith (AWS)
You’ve identified your generative AI use case, tested it and are creating a secure application architecture design. How do you know what generative AI specific threats you should be protecting against, and what tools or services are available that can help? You may have heard of the OWASP Top 10 for LLM Applications, but where or how do you start? Join us as we discuss the OWASP Top 10 threats, the differences between versions, and how AWS can help you mitigate these threats.

DAP332 | Chalk talk | Executive perspective: Risk management for generative AI workloads
Speakers: Jason Garman (AWS) & Mark Ryland (AWS)
Don’t let the perceived complexity of responsible AI keep you from deploying generative AI applications on AWS. In this chalk talk, we will present a framework for breaking down AI safety and security risks, introduce AWS best practices for keeping enterprise data secure in generative AI applications using zero trust principles, and mitigate safety risks using technologies such as Bedrock Guardrails. Discover as a group with fellow security leaders how to identify safety and security risks relevant to your workload, implement appropriate mitigation strategies, and measure efficacy over time.

GRC337 | Chalk talk | Build compliant AI: Implementing controls for emerging regulations
Speakers: Samuel Waymouth (AWS) & Mark Keating (AWS)
As AI adoption accelerates, organizations face increasing regulatory scrutiny and compliance requirements. In this session, learn about the evolving global regulatory landscape for AI, data privacy, and data sovereignty, then see how you can map regulatory requirements and security controls to AWS services and features. We will demonstrate how generative AI can work as a tool for assessment, risk classification and generating compliance guidance. We also show you how to use the latest threat modelling resources developed by AWS. Security professionals and AI practitioners will learn actionable strategies for building AI systems aligned with compliance standards while also maintaining innovation velocity.

SEC221 | Lightning talk | Raising the tide: How AWS is shaping the future of secure AI
Speakers: Matt Saner (AWS)
AI security is a top priority for AWS. By building AI solutions that are secure by design, AWS helps customers 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 its participation industry standards bodies such as CoSAI (The Coalition for Secure AI), to make sure 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.

SEC322 | Lightning talk | Managing digital identity in the age of generative AI
Speakers: Arthur Mnev (AWS) & Lily Ashidam (AWS)
In this session, we will explore the challenges and solutions for managing identities in generative AI workloads. This session covers securing API access for LLMs, implementing proper authentication for, in, and with AI services, and maintaining data lineage. Learn practical approaches towards securing generative AI applications while maintaining compliance and governance requirements.

SEC323 | Lightning talk | A practical guide to generative AI agent resilience
Speakers: Yiwen Zhang (AWS) & Jennifer Moran (AWS)
As generative AI agents dominate headlines and technological discussions, enterprise adoption remains in its infancy. GenAI agent resilience is a crucial factor in successful implementation and building user trust. While traditional workload resilience practices—such as database availability, workload capacity, observability, and disaster recovery—remain relevant, GenAI agents present unique challenges. This session delves into the critical dimensions of GenAI agent resilience, including LLM model adaptability, latency management, tool availability, observability, and financial sustainability. We will share practical strategies for building robust, reliable GenAI agents that enterprises can trust and maintain.

SEC326 | Lightning Talk | Secure remote MCP server deployment for Gen AI on AWS
Speakers: Aaron Brown (AWS) & James Ferguson (AWS)
Discover how to securely build and deploy remote Model Context Protocol (MCP) servers on AWS that implement the protocol’s security and trust principles. This session demonstrates OAuth 2.1 authorization patterns that enforce user consent, data privacy, and tool safety requirements. Learn to implement robust security controls using Amazon Cognito, API Gateway, and Lambda while maintaining protocol compliance. Explore practical examples of authorization flows, access controls, and security monitoring that align with MCP specifications.

TDR322 | Lightning talk | How AWS uses generative AI to advance native security services
Speakers: Marshall Jones (AWS) & Himanshu Verma (AWS)
Discover how AWS leverages generative AI to enhance native security services. This session demonstrates how AWS implements AI capabilities across its security portfolio to improve threat detection, investigation, and response. Explore practical implementations in Amazon GuardDuty and Amazon Inspector that enable automated analysis and natural language security queries. Leave with insights into how AWS makes security more intelligent and efficient through generative AI.

Interactive sessions (builders’ sessions, code talks, and workshops)

Interact with small groups led by an AWS expert providing interactive learning about how to build on AWS. Each builders’ session begins with a short explanation or demonstration of what attendees are building—then it’s your turn to build! The expert will guide you end-to-end through this hands-on experience. Or join Code Talks, our code-focused interactive sessions where AWS experts lead a discussion featuring live coding or code samples as they illuminate the “why” behind AWS solutions. Attendees are encouraged to ask questions and follow along.

Workshops are two-hour interactive sessions where you collaborate in teams or work individually to solve real-world challenges by using AWS services, making them perfect for hands-on learning. Each workshop begins with a brief lecture, followed by dedicated time to work through the problem.

Note: Don’t forget to bring your laptop to build alongside AWS experts.

SEC351 | Builders’ session | Accelerating incident response, compliance & auditing using generative AI
Speakers: Snehal Nahar (AWS), Ravindra Kori (AWS), Rayette Toles-Abdullah (AWS), & Abhijit Barde (AWS)
In this session, we will learn how to use AWS native generative AI capabilities to reduce time to recovery after an incident using enterprise communication tools such as Slack. We will also learn how to use detective controls to identify events that may result in an incident, and also how to use preventive controls to mitigate the risk of an incident occurring. We will use services like Amazon Q Developer, AWS Config, AWS CloudTrail Lake, Amazon CloudWatch and other observability features.

SEC352 | Builders’ session | Agentic AI for security: Building intelligent egress traffic controls
Speakers: Ranjith Rayaprolu (AWS), Anil Nadiminti (AWS), Michael Leighty (AWS), & Dwaragha Sivalingam (AWS)
Learn to build AI-powered security agents that protect your cloud infrastructure. This hands-on session shows you how to use Amazon Bedrock and Bedrock Agents to create intelligent systems that watch over your network. You’ll build Generative AI agents that monitor egress traffic, spot potential threats, and automatically update network firewall to block malicious traffic. Walk away with the skills to implement AI-powered security agents that can reason, decide, and act to protect your cloud infrastructure.

SEC353 | Builders’ session | Threat modeling for generative AI applications
Speakers: Laura Verghote (AWS), Isabelle Mos (AWS), Samuel Waymouth (AWS), & Omar Zoma (AWS)
In this builders’ session, you will learn how to systematically identify and analyze security threats specific to generative AI applications. As organizations rapidly adopt large language models and other generative AI capabilities, understanding the unique security challenges – from prompt injection to data poisoning – becomes critical. You will be guided through the process of creating threat models for common generative AI architectures, with a particular focus on applications built using AWS services like Amazon Bedrock.

SEC451 | Builders’ session | From logs to defense: Generative AI for security automation
Speakers: Ravindra Kori (AWS), Siavash Iran (AWS), Lily Ashidam (AWS), & Yiwen Zhang (AWS)
In this technical session, we’ll demonstrate how to transform traditional operating system log analysis into an intelligent, automated defense system using AWS native services and generative AI. We’ll explore how to build a comprehensive solution that captures security-relevant logs from Windows and Linux systems.

APS351 | Builders’ session | Securing generative AI agents using AWS Well-Architected Framework
Speakers: Krupanidhi Jay (AWS), Ryan Dsouza (AWS), Birender Pal (AWS), & Omkar Mukadam (AWS)
Learn hands-on how to build secure generative AI agent solutions following the AWS Well-Architected Framework’s 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, involving Amazon Bedrock, Amazon CloudWatch, AWS Identity and Access Management (IAM), and more. You must bring your laptop to participate.

APS353 | Builders’ session | Red teaming your LLM security at scale
Speakers: Otto Kruse (AWS), Owen Hawkins (AWS), Aaron Brown (AWS), & Jeff Lombardo (AWS)
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 threat chains against GenAI applications, systematically discovering and exploiting vulnerabilities from prompt injection to boundary testing while mastering automated security testing workflows. In addition, you’ll learn 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.

GRC354 | Builders’ session | Best practices for using generative AI to manage cloud compliance
Speakers: Adnan Bilwani (AWS), Ali Maaz (AWS), Artur Rodrigues (AWS), & Peter Pereira (AWS)
Learn how to leverage Amazon Q Developer to streamline cloud compliance management using AWS Config. This hands-on builders’ session demonstrates how to create intelligent compliance checks, automate remediation workflows, and generate detailed compliance reports using generative AI capabilities. Through practical exercises, learn to implement automated compliance monitoring that combines the power of generative AI with AWS Config’s robust compliance framework. You must bring your laptop to participate.

IAM451 | Builders’ session | Securing GenAI apps: Fine-grained access control for Bedrock Agents
Speakers: Edward Sun (AWS), Pravin Nair (AWS), Dustin Ellis (AWS), & Kevin Hakanson (AWS)
Want to secure generative AI applications accessing your organizational data? Learn how to implement intelligent access controls for Amazon Bedrock-powered applications accessing your organizational data. In this builders’ session, you’ll build a defense-in-depth approach that combines authentication using Amazon Cognito and fine-grained authorization with Amazon Verified Permissions to secure access for Bedrock AI agents. Implement layered permissions that protect sensitive data without limiting your GenAI capabilities. You must bring your laptop to participate.

TDR251 | Builders’ session | Build your first AI security assistant with Amazon Q
Speakers: Scott Taggart (AWS), Joe Wagner (AWS), Laura Verghote (AWS), & Riggs Goodman III (AWS)
Discover how to build your first AI-powered security assistant using Amazon Q Business – no AI expertise required. In this hands-on session, you’ll create three practical security workflows: an automated Amazon GuardDuty incident investigator that contextualizes security findings, an AWS Security Hub compliance report generator that streamlines policy assessments, and an Amazon Inspector-based vulnerability management helper that accelerates remediation. Perfect for security practitioners who want to enhance AWS security operations with generative AI while mastering core AWS security services through practical application. You must bring your laptop to participate.

IAM441 | Code talk | The right way to secure AI agents with code examples
Speakers: Jeff Lombardo (AWS) & Fei Yuan (AWS)
Generative AI agents run tasks on behalf of human users and often interact with each other across on-premises environments and different cloud providers. This brings new challenges in identity authentication, propagation, delegation, and resource authorization in the overall agentic AI solution. Learn how Amazon Cognito’s OAuth2-based identity management, machine-to-machine authentication, combined with Amazon Verified Permissions fine-grained authorization can enable secure delegation patterns for AI agents, while preserving human identity and consent, agent machine identity, and other request context throughout the agent chain. We will walk through real-world examples with agents built on Amazon Bedrock or other frameworks.

TDR341 | Code talk | Build AI security agents with Amazon Bedrock and Amazon Security Lake
Speakers: Chris Lamont-Smith (AWS) & Pratima Singh (AWS)
In this code talk, explore how to enhance security operations by creating AI agents using Amazon Bedrock and Amazon Security Lake. Through live coding demonstrations, learn to build automated workflows that combine autonomous decision-making capabilities with generative AI for security analysis and response. See how to implement agents that analyze logs, provide contextual insights, and execute response procedures. Discover practical approaches for integrating custom tools and leveraging large language models in your security workflows.

SEC371 | Workshop | Red Team approaches to practical generative AI defenses
Speakers: Mac Stevens (AWS) & Cameron Smith (AWS)
This workshop takes a hands-on approach to Generative AI security, focusing on Amazon Bedrock, Amazon SageMaker, and related services. We’ll begin by examining Bedrock’s core security principles, including data protection during inference and in features like Agents, Guardrails, and Knowledge Bases. Participants will gain insights into the internal architectures and security implications of context windows, system prompts, agent orchestration, and more. The session then transitions into hands-on red teaming exercises using SageMaker. We’ll subsequently explore defensive strategies against these threat vectors and discuss methods for integrating these practices into development workflows. Participants will leave equipped with a holistic understanding of Generative AI security, from individual model protection to safeguarding complex, multi-component systems.

APS371 | Workshop | Securing your generative AI applications on AWS
Speakers: Mark Keating (AWS) & Maitreya Ranganath (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.

DAP371 | Workshop | Defend your AI: Mitigate prompt injection with Amazon Bedrock
Speakers: Mark Keating (AWS) & Maitreya Ranganath (AWS)
Master the art of identifying and mitigating prompt injection vulnerabilities in generative AI systems through this hands-on workshop. Using Amazon Bedrock, participants will explore both offensive and defensive prompt engineering techniques to understand the security implications of large language models in production environments. In this session you will understand how prompt injection attacks work, complete an interactive ‘capture the flag’ style challenge attempting to exploit a simulated AI environment, and learn to implement defensive controls using Amazon Bedrock Guardrails. You must bring your laptop to participate.

Register now

Don’t miss this opportunity to learn from industry experts and AWS leaders about securing your AI implementations. Register for AWS re:Inforce 2025 today to reserve your spot in these sessions. Browse the full re:Inforce catalog to learn more about sessions in other tracks, plus partner sessions and code talks.

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

Margaret Jonson

Margaret Jonson

Margaret is a Senior Product Marketing Manager for AWS generative AI security, where she partners with AI/ML teams to help customers implement secure and governed AI solutions across Amazon Bedrock, Amazon SageMaker, Amazon Q, and other AI/ML solutions.

Matt Saner

Matt Saner

As a Senior Manager at AWS, Matt leads a team of security specialists who help the world’s most complex organizations tackle critical security challenges. Matt and his team work to transform security organizations into strategic business enablers. Before joining AWS, Matt spent close to two decades in the financial services industry. Outside of work, Matt is a pilot who finds joy in flying general aviation aircraft.

Navigating the threat detection and incident response track at re:Inforce 2025

Post Syndicated from Nisha Amthul original https://aws.amazon.com/blogs/security/navigating-the-threat-detection-and-incident-response-track-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.

We’re counting down to AWS re:Inforce, our annual cloud security event! We are thrilled to invite security enthusiasts and builders to join us in Philadelphia, PA June 16–18, 2025, for an immersive three-day journey into cloud security learning. At AWS re:Inforce, you’ll have the chance to explore the breadth of the Amazon Web Services (AWS) security landscape, learn how to operationalize security services, and enhance your skills and confidence in cloud security to improve your organization’s security posture. As an attendee, you will have access to over 250 sessions across multiple topic tracks, including data protection; identity and access management; threat detection and incident response; network and infrastructure security; generative AI; governance, risk, and compliance; and application security. Plus, get ready to be inspired by our lineup of customer speakers, who will share their firsthand experiences of innovating securely on AWS.

In this post, we provide an overview of the key sessions that include lecture-style presentations featuring real-world use cases from our customers and interactive small-group sessions led by AWS experts that guide you through practical problems and solutions.

The threat detection and incident response track is designed to demonstrate how to detect and respond to security risks to help protect workloads at scale. AWS experts and customers will present key topics such as unified cloud security, threat detection, vulnerability management, cloud security posture management, integrated detection-to-response, threat intelligence, operationalization of AWS security services, container security, effective security investigation, security analytics, and incident response best practices. We’ll also explore both strengthening security through the use of generative AI and securing generative AI workloads.

Breakout sessions, chalk talks, and lightning talks

TDR301 | Breakout session | Innovations in AWS detection and response for integrated security outcomes
Discover how AWS’s latest detection and response capabilities can help secure your cloud environment more effectively. Learn practical ways to achieve integrated security outcomes through enhanced threat detection, automated vulnerability management, and streamlined response—all at scale. We’ll show you how to use AWS security services to protect workloads and data, centralize security monitoring, manage security posture continuously, and unify security data, while leveraging generative AI for security operations. Walk away with actionable insights on integrating AWS detection and response services to strengthen and simplify your security across AWS.

TDR302 | Breakout session | Multi-stage threat detection using GuardDuty and MITRE
Enhance your threat detection capabilities by leveraging Amazon GuardDuty Extended Threat Detection alongside MITRE frameworks. In this session, Shane Steiger Esq. from MITRE Corp demonstrates how to effectively identify and respond to multi-stage security events in your AWS environment. Learn practical strategies for implementing detection controls, developing response procedures, and building resilient cloud architectures. Discover how integrating GuardDuty with MITRE frameworks can strengthen your event detection and response strategy.

TDR303 | Breakout session | Building secure generative AI security tools, featuring Trellix
Learn how to build enterprise-grade generative AI security tools that unify security data and enable natural language investigations. This session demonstrates practical approaches for developing secure generative AI solutions, including implementation patterns for data privacy and compliance controls. Explore real-world architectures combining AWS foundation models with security orchestration. Hear how Trellix achieved 23x cost savings while maintaining 95% accuracy using Amazon Bedrock models. Leave with strategies to build secure AI assistants that support your security teams.

TDR304 | Breakout session | Scaling AWS threat intelligence to protect customers
Discover how AWS builds and operates threat intelligence at unprecedented scale to protect millions of customers. In this session, dive deep into two critical security functions: Amazon Threat Intelligence, which tracks and defends against sophisticated threats, and Active Defense, our security data processing architecture that analyzes over 4 billion records per second. Learn how these capabilities work together to power AWS security services and provide automated protection for your applications. See how AWS uses this intelligence to continuously enhance security services that help keep your workloads safe.

TDR305 | Breakout session | Scale Vulnerability Management Using Amazon Inspector
Want to strengthen Lambda security and streamline vulnerability management? Learn how Amazon Inspector uses generative AI to provide in-context code patches and automate SBOM management. Discover practical techniques for CI/CD integration, cross-account scanning, and automated remediation workflows. Explore built-in integrations with Security Hub and EventBridge to enhance security operations across your AWS environment.

TDR306 | Breakout session | Enterprise Security at Scale: SAP’s AWS Blueprint
How does SAP protect thousands of AWS accounts? Learn their blueprint for implementing Amazon GuardDuty protection plans alongside Extended Threat Detection to identify sophisticated threat patterns. Discover their framework for standardizing AWS Security Hub controls and automated remediation workflows at scale. Walk away with practical strategies to enhance enterprise security operations across AWS Organizations.

TDR331 | Chalk talk | Ask AWS: Your ransomware questions answered
Get answers to your most critical ransomware questions in this interactive Q&A session. Learn how AWS security features and best practices can help you detect, respond to, and recover from ransomware threats. Our experts will share practical guidance on identifying early warning signs, implementing effective incident response, and strengthening your overall ransomware resilience. Bring your toughest questions about emerging ransomware tactics and cloud protection strategies. Walk away with actionable insights to help secure your data and operations using AWS security capabilities.

TDR332 | Chalk talk | Decoding AWS CIRT tactics & techniques for proactive defense
Learn directly from AWS Customer Incident Response Team (CIRT) experts who help customers respond to critical security events. Discover real-world insights about emerging threat tactics and techniques observed across AWS environments. We’ll share practical detection and mitigation strategies that align with the Shared Responsibility Model, helping you strengthen your security posture. Walk away with actionable best practices from CIRT’s frontline experience defending against evolving threats, and learn how to apply these insights to protect your AWS workloads.

TDR333 | Chalk talk | Strategy for prioritization and response
Join this session to discuss managing security posture and risk across multiple accounts, regions, and resources. We will explore the decision-making process around how you prioritize security alerts and risk using AWS security services. After prioritization, we will discuss a framework for responding to and remediating security findings. We will talk through the decision-making process of responding to findings, considerations for auto-remediation, and how to facilitate a quick and thorough response to the most critical security findings.

TDR334 | Chalk talk | Strengthen Security: Making GuardDuty Protection Plans Work for You
Discover how to maximize your threat detection capabilities by selecting the right Amazon GuardDuty protection plans for your environment. Learn to evaluate protection features that matter most for your AWS workloads and understand the value each plan brings to your security strategy. Through practical scenarios, explore cost-effective implementation strategies across your AWS accounts. Leave with actionable insights for optimizing your Amazon GuardDuty deployment to enhance protection of your AWS workloads and data.

TDR431 | Chalk talk | Best practices for containing AWS resources during incident response
Learn best practices for implementing isolation controls for AWS resources and accounts during security events. Through practical scenarios, discover effective approaches for isolating Amazon EC2 instances, AWS Lambda functions, and Amazon ECS containers. Explore comprehensive strategies for account-level isolation including identity, resource, and network controls. This session provides guidance on implementing and safely removing isolation controls as part of your response procedures. Leave with actionable patterns for strengthening your AWS incident response capabilities. To help businesses move faster and deliver security outcomes, modern security teams need to identify opportunities to automate and simplify their workflows. One way of doing so is through generative AI. Join this chalk talk to learn how to identify use cases where generative AI can help with investigating, prioritizing, and remediating findings from Amazon GuardDuty, Amazon Inspector, and AWS Security Hub. Then find out how you can develop architectures from these use cases, implement them, and evaluate their effectiveness. The talk offers tenets for generative AI and security that can help you safely use generative AI to reduce cognitive load and increase focus on novel, high-value opportunities.

TDR336 | Chalk talk | Secure generative AI models and agents on AWS
Learn how to strengthen security controls for generative AI models and Amazon Bedrock agents in your AWS environment. This session explores implementation patterns for protecting API endpoints and securing agent interactions. Discover practical approaches for implementing protective controls and maintaining data security for your AI/ML workloads. Leave with actionable strategies for building secure generative AI implementations using AWS services.

TDR337 | Chalk talk | Implementing AWS security best practices: Insights & strategies
Learn how to optimize your AWS security services implementation including Amazon GuardDuty, AWS Security Hub, and AWS WAF. AWS security experts share practical insights and proven patterns derived from thousands of customer deployments. This session provides actionable strategies for operationalizing security services effectively in your environment. Discover implementation best practices and architectural approaches that help you maximize the value of your AWS security services.

TDR338 | Chalk talk | Building cloud-native forensic investigation architectures on AWS
Join this chalk talk to explore the advantages of cloud-native digital forensics and incident response on AWS. Engage in interactive discussions on best practices for establishing secure forensic investigation environments. We’ll explore architectural patterns for safely collecting and storing forensic artifacts, leveraging ephemeral resources to enhance security, and implementing effective network, account, and organizational designs. Bring your questions and scenarios as we collaboratively examine how to build scalable, standardized investigation processes using AWS services. Leave with practical strategies for enhancing your forensic and incident response capabilities in the cloud.

TDR231 | Chalk talk | Resilient security teams: Reduce burnout and boost performance
Learn strategies for building resilient security and incident response teams that prioritize wellbeing while maintaining high performance. This session explores approaches for implementing regular team check-ins, data-informed wellbeing initiatives, and a supportive team culture. Discover practical methods for fostering open communication, maintaining team engagement, and recognizing team contributions. Through real-world examples, develop actionable plans to enhance team resilience, improve retention, and sustain security excellence. Leave with strategies to build and maintain high-performing security teams.

TDR321 | Lightning talk | From Incidents to Insights: Creating a Security Learning Organization
Learn how to transform security events into organizational improvements. This session demonstrates practical approaches for building effective feedback loops, preserving institutional knowledge, and implementing sustainable enhancements to security operations. Discover AWS strategies for measuring the impact of improvements and fostering a culture of continuous learning. Leave with actionable frameworks for strengthening your security program through systematic learning and adaptation.

TDR322 | Lightning talk | How AWS uses generative AI to advance native security services
Discover how AWS leverages generative AI to enhance native security services. This session demonstrates how AWS implements AI capabilities across its security portfolio to improve threat detection, investigation, and response. Explore practical implementations in Amazon GuardDuty and Amazon Inspector that enable automated analysis and natural language security queries. Leave with insights into how AWS makes security more intelligent and efficient through generative AI.

TDR323 | Lightning talk | How Autodesk scales threat detection with Amazon GuardDuty
Learn how Autodesk elevated their threat detection strategy using Amazon GuardDuty. This lightning talk explores their implementation approach, operational insights, and best practices for leveraging the advanced detection capabilities of GuardDuty, including malware protection. Discover how they maintain robust security while efficiently managing their growing cloud footprint.

TDR421 | Lightning talk | Accelerating Incident Response with AWS Security Incident Response
Learn how AWS Security Incident Response helps security teams streamline investigation and response procedures. This session demonstrates service integration capabilities with Amazon GuardDuty, AWS CloudTrail, and AWS Security Hub to provide centralized incident management. Through customer examples and implementation patterns, discover practical approaches for building automated response strategies. Leave with actionable insights for enhancing your security operations using AWS services.

Interactive sessions (builders’ sessions, code talks, and workshops)

TDR251 | Builders’ session | Build your first AI security assistant with Amazon Q
Discover how to build your first AI-powered security assistant using Amazon Q Business—no AI expertise required. In this hands-on session, you’ll create three practical security workflows: an automated Amazon GuardDuty incident investigator that contextualizes security findings, an AWS Security Hub compliance report generator that streamlines policy assessments, and an Amazon Inspector-based vulnerability management helper that accelerates remediation. Perfect for security practitioners who want to enhance AWS security operations with generative AI while mastering core AWS security services through practical application.

TDR252 | Builders’ session | Detect ransomware events in Amazon S3 using Amazon GuardDuty
In this builders’ session, join the AWS Customer Incident Response Team (CIRT) to implement Amazon S3 ransomware detection using Amazon GuardDuty. Through hands-on scenarios, learn to identify unauthorized encryption operations and implement effective response procedures. Build detection patterns using AWS CloudTrail, Amazon Athena, Amazon GuardDuty, and Amazon CloudWatch. Practice investigating events and implementing preventive measures aligned with AWS Security’s latest guidance for Amazon S3 object protection. You must bring your laptop to participate.

TDR351 | Builders’ session | Build an OCSF security log pipeline with AWS
Build a complete security log pipeline that leverages the Open Cybersecurity Schema Framework (OCSF) in this hands-on session. Work alongside AWS experts to ingest, transform, and enrich your security data. Learn practical techniques to standardize security logs, whether using your own schema or our provided examples. Walk away with implementable solutions to enhance your threat detection capabilities through normalized security data flows. Bring your laptop and optional custom log samples to create solutions tailored to your use cases.

TDR451 | Builders’ session | Automate incident response for Amazon EC2 and Amazon EKS
Learn how to streamline incident response using the Automated Forensics Orchestrator solution for Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic Kubernetes Service (Amazon EKS). This session demonstrates how to implement automated workflows triggered by AWS Security Hub findings. Explore implementation prerequisites, customization options, and best practices for enhancing your security operations through automated forensics capabilities. Discover how to standardize response procedures across your Amazon EC2 and Amazon EKS environments.

TDR452 | Builders’ session | Build generative AI security runbooks with Amazon Bedrock
In this builders’ session, learn how to enhance security operations using generative AI-powered runbooks with Amazon Bedrock and Bedrock Agents. Create intelligent workflows that analyze AWS Security Hub findings and provide contextual remediation guidance. Through hands-on exercises, build Bedrock Agents that leverage AWS documentation and implement natural language interfaces for security investigations. Learn how to configure knowledge bases with organization-specific content and implement appropriate guardrails. Leave with a practical solution for streamlining security operations using generative AI. You must bring your laptop to participate.

TDR341 | Code talk | Build AI security agents with Amazon Bedrock and Security Lake
In this code talk, explore how to enhance security operations by creating AI agents using Amazon Bedrock and Amazon Security Lake. Through live coding demonstrations, learn to build automated workflows that combine autonomous decision-making capabilities with generative AI for security analysis and response. See how to implement agents that analyze logs, provide contextual insights, and execute response procedures. Discover practical approaches for integrating custom tools and leveraging large language models in your security workflows.

TDR342 | Code talk | Operationalizing Amazon Security Lake with analytics and generative AI
Roll up your sleeves for this hands-on coding session where we’ll build modern security analytics tools on top of Amazon Security Lake. Through interactive demos, we’ll craft queries and visualizations to operationalize your security data using AWS services like Amazon OpenSearch Service, Amazon QuickSight, Amazon Athena, and Amazon Bedrock. Leave with practical code samples and architectures to analyze security data. Get inspired with ideas on how to transform your threat detection and incident response stack.

TDR343 | Code talk | From detection to code: GuardDuty attack sequences with Amazon Q
In this code talk, explore how Amazon GuardDuty attack sequence detection capabilities work alongside Amazon Q to enhance security operations. Through live coding demonstrations, learn hoGuardDuty machine learning models identify connected security events and create comprehensive event sequences. See how to build automated response procedures using Amazon Q AI-assisted development capabilities. Discover practical approaches for implementing context-aware security automation. Leave with implementation patterns for enhancing your security operations using generative AI tools.

TDR371 | Workshop | Hands-on Threat Detection & Response using AWS Security
Get hands-on experience with AWS security services in this interactive workshop. Learn to detect and respond to simulated threats using Amazon GuardDuty, Amazon Inspector, AWS Security Hub, and Amazon Detective. Practice both manual and automated response techniques with AWS Lambda as you investigate security events across different resource types. Walk away with practical skills to operationalize threat detection and response in your AWS environment. Bring your laptop to participate in this hands-on workshop.

TDR372 | Workshop | Secure container workloads with AWS security services
In this workshop, learn how to implement AWS security services to protect container workloads end-to-end from code to operations. Gain hands-on experience with static code analysis, detective controls, threat detection, vulnerability management, and incident response for Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon Elastic Container Service (Amazon ECS). Through guided scenarios, discover how to use AWS security services to enhance your container security posture. Leave with practical strategies for implementing security controls in your container environments. You must bring your laptop to participate.

TDR471 | Workshop | AWS Security Incident Response Challenge: Defense in action
Put your AWS security incident response skills to the test in this interactive session. Assume the role of an AWS Security Engineer responding to a time-sensitive scenario. Using provided intelligence, you’ll have a limited time to implement security controls in your AWS environment. Learn to prioritize actions and leverage AWS security services effectively under realistic conditions. This hands-on exercise helps you practice rapid decision-making and security implementation in AWS environments. Leave with practical experience in incident response strategies. You must bring your laptop to participate.

TDR472 | Workshop | Active defense strategies using AWS AI/ML services
This workshop will help you learn how to develop and deploy active defense strategies, such as deception, using Amazon Bedrock and Amazon SageMaker. Gain hands-on experience developing AI-driven responses for security operations. You will learn how to develop adaptive responses that mimic what an actor may be trying use against you. You will Learn implementation patterns for prompt engineering, deployment strategies, and monitoring methodologies. You must bring your laptop to participate.

Browse the full re:Inforce catalog to learn more about sessions in other tracks, plus gamified learning, innovation sessions, partner sessions, and labs. Discover how to optimize your re:Inforce journey with our attendee guides—your essential resource for selecting perfect learning sessions and getting the greatest value from your experience.

Our comprehensive track content is designed to help arm you with the knowledge and skills needed to securely manage your workloads and applications on AWS. Don’t miss out on the opportunity to stay updated with the latest best practices in threat detection and incident response. Join us in Philadelphia for re:Inforce 2025 by registering today. We can’t wait to welcome you!

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

Nisha Amthul

Nisha Amthul

Nisha is a Senior Product Marketing Manager at AWS Security, specializing in detection and response solutions. She has a strong foundation in product management and product marketing within the domains of information security and data protection. When not at work, you’ll find her cake decorating, strength training, and chasing after her two energetic kiddos.

Secure cloud innovation starts at re:Inforce 2025

Post Syndicated from Chris Betz original https://aws.amazon.com/blogs/security/secure-cloud-innovation-starts-at-reinforce-2025/

Every day, I talk with security leaders who are navigating a critical balancing act. On one side, their organizations are moving faster than ever, adopting transformative technologies like generative AI and expanding their cloud footprint. On the other, they’re working to maintain strong security controls and visibility across an increasingly complex landscape. We all know that adding more tools and controls isn’t sustainable. We need a different approach to security at scale.

re:Inforce 2025: Your roadmap to security that powers innovation

This is what shaped our vision for AWS re:Inforce 2025. When done right, security at scale becomes a business accelerator, helping organizations move faster and more confidently in the cloud. This is more than just a philosophy; it’s a practical reality I’ve seen proven time and again by our customers, and it’s what we want to help every organization achieve.

At re:Inforce, we’ll share a vision for simplifying security at scale that’s deeply rooted in our experiences supporting millions of customers worldwide. We’ll explore how organizations are building inherently resilient applications that can withstand modern threats while accelerating innovation. I’m particularly excited to showcase real customer examples and architectural patterns that demonstrate how security better enables your business goals.

An environment built for learning cloud security

There’s a reason we created re:Inforce as a dedicated in-person security event. While I love our broader AWS events, security practitioners need space to dive deep into implementation details, ask tough questions, and work through complex scenarios. At re:Inforce, you can grab a whiteboard with the engineers who built our security services, collaborate with security partners, and schedule personal time with our leaders to tackle your specific security needs. It’s the kind of environment where real learning happens.

We’ve designed multiple learning paths to meet you wherever you are in your security journey. With over 250 technical sessions, you’ll find content that matches your needs – whether you’re looking to automate security controls, align development and security teams, or transform your security operations. You’ll find interactive workshops where you’ll build solutions in real-time, small-group technical deep-dives, hands-on labs where you can test new approaches, and solution-building sessions with AWS experts. Best of all, 70% of our content is at advanced or expert level, making sure you get the detailed implementation guidance you need.

I invite you to join us for three days that will transform how you think about and implement security in the cloud. Registration is now open, and I encourage you to secure your spot early—based on previous years, spots will fill up quickly. Join us to explore how simplified, scalable cloud security can fuel your organization’s future. Register today with the code SECBLObhZzr9 to receive a limited time $300 USD discount, while supplies last.

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

Chris Betz

Chris is CISO at AWS. He oversees security teams and leads the development and implementation of security policies with the aim of managing risk and aligning the company’s security posture with business objectives. Chris joined Amazon in August 2023 after holding CISO and security leadership roles at leading companies. He lives in Northern Virginia with his family.

AWS Audit Manager extends generative AI best practices framework to Amazon SageMaker

Post Syndicated from Matheus Guimaraes original https://aws.amazon.com/blogs/aws/aws-audit-manager-extends-generative-ai-best-practices-framework-to-amazon-sagemaker/

Sometimes I hear from tech leads that they would like to improve visibility and governance over their generative artificial intelligence applications. How do you monitor and govern the usage and generation of data to address issues regarding security, resilience, privacy, and accuracy or to validate against best practices of responsible AI, among other things? Beyond simply taking these into account during the implementation phase, how do you maintain long-term observability and carry out compliance checks throughout the software’s lifecycle?

Today, we are launching an update to the AWS Audit Manager generative AI best practice framework on AWS Audit Manager. This framework simplifies evidence collection and enables you to continually audit and monitor the compliance posture of your generative AI workloads through 110 standard controls which are pre-configured to implement best practice requirements. Some examples include gaining visibility into potential personally identifiable information (PII) data that may not have been anonymized before being used for training models, validating that multi-factor authentication (MFA) is enforced to gain access to any datasets used, and periodically testing backup versions of customized models to ensure they are reliable before a system outage, among many others. These controls perform their tasks by fetching compliance checks from AWS Config and AWS Security Hub, gathering user activity logs from AWS CloudTrail and capturing configuration data by making application programming interface (API) calls to relevant AWS services. You can also create your own custom controls if you need that level of flexibility.

Previously, the standard controls included with v1 were pre-configured to work with Amazon Bedrock and now, with this new version, Amazon SageMaker is also included as a data source so you may gain tighter control and visibility of your generative AI workloads on both Amazon Bedrock and Amazon SageMaker with less effort.

Enforcing best practices for generative AI workloads
The standard controls included in the “AWS generative AI best practices framework v2” are organized under domains named accuracy, fair, privacy, resilience, responsible, safe, secure and sustainable.

Controls may perform automated or manual checks or a mix of both. For example, there is a control which covers the enforcement of periodic reviews of a model’s accuracy over time. It automatically retrieves a list of relevant models by calling the Amazon Bedrock and SageMaker APIs, but then it requires manual evidence to be uploaded at certain times showing that a review has been conducted for each of them.

You can also customize the framework by including or excluding controls or customizing the pre-defined ones. This can be really helpful when you need to tailor the framework to meet regulations in different countries or update them as they change over time. You can even create your own controls from scratch though I would recommend you search the Audit Manager control library first for something that may be suitable or close enough to be used as a starting point as it could save you some time.

The Control library interface featuring a search box and three tabs: Common, Standard and Custom.

The control library where you can browse and search for common, standard and custom controls.

To get started you first need to create an assessment. Let’s walk through this process.

Step 1 – Assessment Details
Start by navigating to Audit Manager in the AWS Management Console and choose “Assessments”. Choose “Create assessment”; this takes you to the set up process.

Give your assessment a name. You can also add a description if you desire.

Step 1 screen of the assessment creation process. It has a textbox where you must enter a name for your assessment and a description text box where you can optionally enter a description.

Choose a name for this assessment and optionally add a description.

Next, pick an Amazon Simple Storage Service (S3) bucket where Audit Manager stores the assessment reports it generates. Note that you don’t have to select a bucket in the same AWS Region as the assessment, however, it is recommended since your assessment can collect up to 22,000 evidence items if you do so, whereas if you use a cross-Region bucket then that quota is significantly reduced to 3,500 items.

Interface with a textbox where you can type or search for your S3 buckets as well as buttons for browsing and creating a new bucket.

Choose the S3 bucket where AWS Audit Manager can store reports.

Next, we need to pick the framework we want to use. A framework effectively works as a template enabling all of its controls for use in your assessment.

In this case, we want to use the “AWS generative AI best practices framework v2” framework. Use the search box and click on the matched result that pops up to activate the filter.

The Framework searchbox where we typed "gene" which is enough to bring a few results with the top one being "AWS Generative AI Best Practices Framework v2"

Use the search box to find the “AWS generative AI best practices framework V2”

You then should see the framework’s card appear .You can choose the framework’s title, if you wish, to learn more about it and browse through all the included controls.

Select it by choosing the radio button in the card.

A widget containing the framework's title and summary with a radio button that has been checked.

Check the radio button to select the framework.

You now have an opportunity to tag your assessment. Like any other resources, I recommend you tag this with meaningful metadata so review Best Practices for Tagging AWS Resources if you need some guidance.

Step 2 – Specify AWS accounts in scope
This screen is quite straight-forward. Just pick the AWS accounts that you want to be continuously evaluated by the controls in your assessment. It displays the AWS account that you are currently using, by default. Audit Manager does support running assessments against multiple accounts and consolidating the report into one AWS account, however, you must explicitly enable integration with AWS Organizations first, if you would like to use that feature.

Screen displaying all the AWS accounts available for you to select that you want to include in your assessment.

Select the AWS accounts that you want to include in your assessment.

I select my own account as listed and choose “Next”

Step 3 – Specify audit owners
Now we just need to select IAM users who should have full permissions to use and manage this assessment. It’s as simple as it sounds. Pick from a list of identity and access management (IAM) users or roles available or search using the box. It’s recommended that you use the AWSAuditManagerAdministratorAccess policy.

You must select at least one, even if it’s yourself which is what I do here.

Interface for searching and selecting IAM users or roles.

Select IAM users or roles who will have full permissions over this assessment and act as owners.

Step 4 – Review and create
All that is left to do now is review your choices and click on “Create assessment” to complete the process.

Once the assessment is created, Audit Manager starts collecting evidence in the selected AWS accounts and you start generating reports as well as surfacing any non-compliant resources in the summary screen. Keep in mind that it may take up to 24 hours for the first evaluation to show up.

The summary screen for the assessment showing details such as how many controls are available, the status of each control displaying whether they "under review" or their compliance status plus tabs where you can revisit the assessment configuration.

You can visit the assessment details screen at any time to inspect the status for any of the controls.

Conclusion
The “AWS generative AI best practices framework v2” is available today in the AWS Audit Manager framework library in all AWS Regions where Amazon Bedrock and Amazon SageMaker are available.

You can check whether Audit Manager is available in your preferred Region by visiting AWS Services by Region.

If you want to dive deeper, check out a step-by-step guide on how to get started.

Simplify AWS CloudTrail log analysis with natural language query generation in CloudTrail Lake (preview)

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/simplify-aws-cloudtrail-log-analysis-with-natural-language-query-generation-in-cloudtrail-lake-preview/

Today, I am happy to announce in preview the generative artificial intelligence (generative AI)–powered natural language query generation in AWS CloudTrail Lake, which is a managed data lake for capturing, storing, accessing, and analyzing AWS CloudTrail activity logs to meet compliance, security, and operational needs. You can ask a question using natural language about these activity logs (management and data events) stored in CloudTrail Lake without having the technical expertise to write a SQL query or spend time to decode the exact structure of activity events. For example, you might ask, “Tell me how many database instances are deleted without a snapshot”, and the feature will convert that question to a CloudTrail Lake query, which you can run as-is or modify to get the requested event information. Natural language query generation makes the process of exploration of AWS activity logs simpler.

Now, let me show you how to start using natural language query generation.

Getting started with natural language query generation
The natural language query generator uses generative AI to produce a ready-to-use SQL query from your prompt, which you can then choose to run in the query editor of CloudTrail Lake.

In the AWS CloudTrail console, I choose Query under Lake. The query generator can only generate queries for event data stores that collect CloudTrail management and data events. I choose an event data store for my CloudTrail Lake query from the dropdown list in Event data store. In the Query generator, I enter the following prompt in the Prompt field using natural language:

How many errors were logged during the past month?

Then, I choose Generate query. The following SQL query is automatically generated:

SELECT COUNT(*) AS error_count
FROM 8a6***
WHERE eventtime >= '2024-04-21 00:00:00'
    AND eventtime <= '2024-05-21 23:59:59'
    AND (
        errorcode IS NOT NULL
        OR errormessage IS NOT NULL
    )

I choose Run to see the results.

This is interesting, but I want to know more details. I want to see which services had the most errors and why these actions were erroring out. So I enter the following prompt to request additional details:

How many errors were logged during the past month for each service and what was the cause of each error?

I choose Generate query, and the following SQL query is generated:

SELECT eventsource,
    errorcode,
    errormessage,
    COUNT(*) AS errorCount
FROM 8a6***
WHERE eventtime >= '2024-04-21 00:00:00'
    AND eventtime <= '2024-05-21 23:59:59'
    AND (
        errorcode IS NOT NULL
        OR errormessage IS NOT NULL
    )
GROUP BY 1,
    2,
    3
ORDER BY 4 DESC;

I choose Run to see the results.

In the results, I see that my account experiences most number of errors related to Amazon S3, and top errors are related to CORS and object level configuration. I can continue to dig deeper to see more details by asking further questions. But now let me give natural language query generator another instruction. I enter the following prompt in the Prompt field:

What are the top 10 AWS services that I used in the past month? Include event name as well.

I choose Generate query, and the following SQL query is generated. This SQL statement retrieves the field names (eventSource,
eventName, COUNT(*) AS event_count), restricts the rows with the date interval of the past month in the WHERE clause, groups the rows by eventSource and eventName, sorts them by the usage count, and limit the result to 10 rows as I requested in a natural language.

SELECT eventSource,
    eventName,
    COUNT(*) AS event_count
FROM 8a6***
WHERE eventTime >= timestamp '2024-04-21 00:00:00'
    AND eventTime <= timestamp '2024-05-21 23:59:59'
GROUP BY 1,
    2
ORDER BY 3 DESC
LIMIT 10;

Again, I choose Run to see the results.

I now have a better understanding of how many errors were logged during the past month, what service the error was for, and what caused the error. You can try asking questions in plain language and run the generated queries over your logs to see how this feature works with your data.

Join the preview
Natural language query generation is available in preview in the US East (N. Virginia) Region as part of CloudTrail Lake.

You can use natural language query generation in preview for no additional cost. CloudTrail Lake query charges apply when running the query to generate results. For more information, visit AWS CloudTrail Pricing.

To learn more and get started using natural language query generation, visit AWS CloudTrail Lake User Guide.

— Esra

Introducing Amazon GuardDuty Malware Protection for Amazon S3

Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/introducing-amazon-guardduty-malware-protection-for-amazon-s3/

Today we are announcing the general availability of Amazon GuardDuty Malware Protection for Amazon Simple Storage Service (Amazon S3), an expansion of GuardDuty Malware Protection to detect malicious file uploads to selected S3 buckets. Previously, GuardDuty Malware Protection provided agentless scanning capabilities to identify malicious files on Amazon Elastic Block Store (Amazon EBS) volumes attached to Amazon Elastic Compute Cloud (Amazon EC2) and container workloads.

Now, you can continuously evaluate new objects uploaded to S3 buckets for malware and take action to isolate or eliminate any malware found. Amazon GuardDuty Malware Protection uses multiple Amazon Web Services (AWS) developed and industry-leading third-party malware scanning engines to provide malware detection without degrading the scale, latency, and resiliency profile of Amazon S3.

With GuardDuty Malware Protection for Amazon S3, you can use built-in malware and antivirus protection on your designated S3 buckets to help you remove the operational complexity and cost overhead associated with automating malicious file evaluation at scale. Unlike many existing tools used for malware analysis, this managed solution from GuardDuty does not require you to manage your own isolated data pipelines or compute infrastructure in each AWS account and AWS Region where you want to perform malware analysis.

Your development and security teams can work together to configure and oversee malware protection throughout your organization for select buckets where new uploaded data from untrusted entities is required to be scanned for malware. You can configure post-scan action in GuardDuty, such as object tagging, to inform downstream processing, or consume the scan status information provided through Amazon EventBridge to implement isolation of malicious uploaded objects.

Getting started with GuardDuty Malware Protection for your S3 bucket
To get started, in the GuardDuty console, select Malware Protection for S3 and choose Enable.

Enter the S3 bucket name or choose Browse S3 to select an S3 bucket name from a list of buckets that belong to the currently selected Region. You can select All the objects in the S3 bucket when you want GuardDuty to scan all the newly uploaded objects in the selected bucket. Or you can also select Objects beginning with a specific prefix when you want to scan the newly uploaded objects that belong to a specific prefix.

After scanning a newly uploaded S3 object, GuardDuty can add a predefined tag with the key as GuardDutyMalwareScanStatus and the value as the scan status:

  • NO_THREATS_FOUND – No threat found in the scanned object.
  • THREATS_FOUND – Potential threat detected during scan.
  • UNSUPPORTED – GuardDuty cannot scan this object because of size.
  • ACCESS_DENIED – GuardDuty cannot access object. Check permissions.
  • FAILED – GuardDuty could not scan the object.

When you want GuardDuty to add tags to your scanned S3 objects, select Tag objects. If you use tags, you can create policies to prevent objects from being accessed before the malware scan completes and prevent your application from accessing malicious objects.

Now, you must first create and attach an AWS Identity and Access Management (IAM) role that includes the required permissions:

  • EventBridge actions to create and manage the EventBridge managed rule so that Malware Protection for S3 can listen to your S3 Event Notifications.
  • Amazon S3 and EventBridge actions to send S3 Event Notifications to EventBridge for all events in this bucket.
  • Amazon S3 actions to access the uploaded S3 object and add a predefined tag to the scanned S3 object.
  • AWS Key Management Service (AWS KMS) key actions to access the object before scanning and putting a test object on buckets with the supported DSSE-KMS and SSE-KMS

To add these permissions, choose View permissions and copy the policy template and trust relationship template. These templates include placeholder values that you should replace with the appropriate values associated with your bucket and AWS account. You should also replace the placeholder value for the AWS KMS key ID.

Now, choose Attach permissions, which opens the IAM console in a new tab. You can choose to create a new IAM role or update an existing IAM role with the permissions from the copied templates. If you want to create or update your IAM role in advance, visit Prerequisite – Create or update IAM PassRole policy in the AWS documentation.

Finally, go back to the GuardDuty browser tab that has the IAM console open, choose your created or updated IAM role, and choose Enable.

Now, you will see Active in the protection Status column for this protected bucket.

Choose View all S3 malware findings to see the generated GuardDuty findings associated with your scanned S3 bucket. If you see the finding type S3Object:S3/MaliciousFile, GuardDuty has detected the listed S3 object as malicious. Choose the Threats detected section in the Findings details panel and follow the recommended remediation steps. To learn more, visit Remediating a potentially malicious S3 object in the AWS documentation.

Things to know
You can set up GuardDuty Malware Protection for your S3 buckets even without GuardDuty enabled for your AWS account. However, if you enable GuardDuty in your account, you can use the full monitoring of foundational sources, such as AWS CloudTrail management events, Amazon Virtual Private Cloud (Amazon VPC) Flow Logs, and DNS query logs, as well as malware protection features. You can also have security findings sent to AWS Security Hub and Amazon Detective for further investigation.

GuardDuty can scan files belonging to the following synchronous Amazon S3 storage classes: S3 Standard, S3 Intelligent-Tiering, S3 Standard-IA, S3 One Zone-IA, and Amazon S3 Glacier Instant Retrieval. It will scan the file formats known to be used to spread or contain malware. At the launch, the feature supports file sizes up to 5 GB, including archive files with up to five levels and 1,000 files per level after it is decompressed.

As I said, GuardDuty will send scan metrics to your EventBridge for each protected S3 bucket. You can set up alarms and define post-scan actions, such as tagging the object or moving the malicious object to a quarantine bucket. To learn more about other monitoring options, such as Amazon CloudWatch metrics and S3 object tagging, visit Monitoring S3 object scan status in the AWS documentation.

Now available
Amazon GuardDuty Malware Protection for Amazon S3 is generally available today in all AWS Regions where GuardDuty is available, excluding China Regions and GovCloud (US) Regions.

The pricing is based on the GB volume of the objects scanned and number of objects evaluated per month. This feature comes with a limited AWS Free Tier, which includes 1,000 requests and 1 GB each month, pursuant to conditions for the first 12 months of account creation for new AWS accounts, or until June 11, 2025, for existing AWS accounts. To learn more, visit the Amazon GuardDuty pricing page.

Give GuardDuty Malware Protection for Amazon S3 a try in the GuardDuty console. For more information, visit the Amazon GuardDuty User Guide and send feedback to AWS re:Post for Amazon GuardDuty or through your usual AWS support contacts.

— Channy

IAM Access Analyzer Update: Extending custom policy checks & guided revocation

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/iam-access-analyzer-update-extending-custom-policy-checks-guided-revocation/

We are making IAM Access Analyzer even more powerful, extending custom policy checks and adding easy access to guidance that will help you to fine-tune your IAM policies. Both of these new features build on the Custom Policy Checks and the Unused Access analysis that were launched at re:Invent 2023. Here’s what we are launching:

New Custom Policy Checks – Using the power of automated reasoning, the new checks help you to detect policies that grant access to specific, critical AWS resources, or that grant any type of public access. Both of the checks are designed to be used ahead of deployment, possibly as part of your CI/CD pipeline, and will help you proactively detect updates that do not conform to your organization’s security practices and policies.

Guided Revocation – IAM Access Analyzer now gives you guidance that you can share with your developers so that they can revoke permissions that grant access that is not actually needed. This includes unused roles, roles with unused permissions, unused access keys for IAM users, and unused passwords for IAM users. The guidance includes the steps needed to either remove the extra items or to replace them with more restrictive ones.

New Custom Policy Checks
The new policy checks can be invoked from the command line or by calling an API function. The checks examine a policy document that is supplied as part of the request and return a PASS or FAIL value. In both cases, PASS indicates that the policy document properly disallows the given access, and FAIL indicates that the policy might allow some or all of the permissions. Here are the new checks:

Check No Public Access – This check operates on a resource policy, and checks to see if the policy grants public access to a specified resource type. For example, you can check a policy to see if it allows public access to an S3 bucket by specifying the AWS::S3::Bucket resource type. Valid resource types include DynamoDB tables and streams, EFS file systems, OpenSearch domains, Kinesis streams and stream consumers, KMS keys, Lambda functions, S3 buckets and access points, S3 Express directory buckets, S3 Outposts buckets and access points, Glacier, Secrets Manager secrets, SNS topics and queues, and IAM policy documents that assume roles. The list of valid resource types will expand over time and can be found in the CheckNoPublicAccess documentation,

Let’s say that I have a policy which accidentally grants public access to an Amazon Simple Queue Service (Amazon SQS) queue. Here’s how I check it:

$ aws accessanalyzer check-no-public-access --policy-document file://resource.json \
  --resource-type AWS::SQS::Queue --output json

And here is the result:

{
    "result": "FAIL",
    "message": "The resource policy grants public access for the given resource type.",
    "reasons": [
        {
            "description": "Public access granted in the following statement with sid: SqsResourcePolicy.",
            "statementIndex": 0,
            "statementId": "SqsResourcePolicy"
        }
    ]
}

I edit the policy to remove the access grant and try again, and this time the check passes:

{
    "result": "PASS",
    "message": "The resource policy does not grant public access for the given resource type."
}

Check Access Not Granted – This check operates on a single resource policy or identity policy at a time. It also accepts an list of actions and resources, both in the form that are acceptable as part of an IAM policy. The check sees if the policy grants unintended access to any of the resources in the list by way of the listed actions. For example, this check could be used to make sure that a policy does not allow a critical CloudTrail trail to be deleted:

$ aws accessanalyzer check-access-not-granted --policy-document file://ct.json \
  --access resources="arn:aws:cloudtrail:us-east-1:123456789012:trail/MySensitiveTrail" \
  --policy-type IDENTITY_POLICY --output json

IAM Access Analyzer indicates that the check fails:

{
    "result": "FAIL",
    "message": "The policy document grants access to perform one or more of the listed actions or resources.",
    "reasons": [
        {
            "description": "One or more of the listed actions or resources in the statement with index: 0.",
            "statementIndex": 0
        }
    ]
}

I fix the policy and try again, and this time the check passes, indicating that the policy does not grant access to the listed resources:

{
    "result": "PASS",
    "message": "The policy document does not grant access to perform the listed actions or resources."
}

Guided Revocation
In my earlier post I showed you how IAM Access Analyzer discovers and lists IAM items that grant access which is not actually needed. With today’s launch, you now get guidance to help you (or your developer team) to resolve these findings. Here are the latest findings from my AWS account:

Some of these are leftovers from times when I was given early access to a service so that I could use and then blog about it; others are due to my general ineptness as a cloud admin! Either way, I need to clean these up. Let’s start with the second one, Unused access key. I click on the item and can see the new Recommendations section at the bottom:

I can follow the steps and delete the access key or I can click Archive to remove the finding from the list of active findings and add it to the list of archived ones. I can also create an archive rule that will do the same for similar findings in the future. Similar recommendations are provided for unused IAM users, IAM roles, and passwords.

Now let’s take a look at a finding of Unused permissions:

The recommendation is to replace the existing policy with a new one. I can preview the new policy side-by-side with the existing one:

As in the first example I can follow the steps or I can archive the finding.

The findings and the recommendations are also available from the command line. I generate the recommendation by specifying an analyzer and a finding from it:

$ aws accessanalyzer generate-finding-recommendation \
  --analyzer-arn arn:aws:access-analyzer-beta:us-west-2:123456789012:analyzer/MyAnalyzer \
  --id 67110f3e-05a1-4562-b6c2-4b009e67c38e

Then I retrieve the recommendation. In this example, I am filtering the output to only show the steps since the entire JSON output is fairly rich:

$ aws accessanalyzer get-finding-recommendation \
  --analyzer-arn arn:aws:access-analyzer-beta:us-west-2:123456789012:analyzer/MyAnalyzer \
  --id 67110f3e-05a1-4562-b6c2-4b009e67c38e --output json | \
  jq .recommendedSteps[].unusedPermissionsRecommendedStep.recommendedAction
"CREATE_POLICY"
"DETACH_POLICY"

You can use these commands (or the equivalent API calls) to integrate the recommendations into your own tools and systems.

Available Now
The new checks and the resolution steps are available now and you can start using them today in all public AWS regions!

— Jeff;