Tag Archives: Uncategorized

FBI Shuts Down Chinese Botnet

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/fbi-shuts-down-chinese-botnet.html

The FBI has shut down a botnet run by Chinese hackers:

The botnet malware infected a number of different types of internet-connected devices around the world, including home routers, cameras, digital video recorders, and NAS drives. Those devices were used to help infiltrate sensitive networks related to universities, government agencies, telecommunications providers, and media organizations…. The botnet was launched in mid-2021, according to the FBI, and infected roughly 260,000 devices as of June 2024.

The operation to dismantle the botnet was coordinated by the FBI, the NSA, and the Cyber National Mission Force (CNMF), according to a press release dated Wednesday. The U.S. Department of Justice received a court order to take control of the botnet infrastructure by sending disabling commands to the malware on infected devices. The hackers tried to counterattack by hitting FBI infrastructure but were “ultimately unsuccessful,” according to the law enforcement agency.

Remotely Exploding Pagers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/remotely-exploding-pagers.html

Wow.

It seems they all exploded simultaneously, which means they were triggered.

Were they each tampered with physically, or did someone figure out how to trigger a thermal runaway remotely? Supply chain attack? Malicious code update, or natural vulnerability?

I have no idea, but I expect we will all learn over the next few days.

EDITED TO ADD: I’m reading nine killed and 2,800 injured. That’s a lot of collateral damage. (I haven’t seen a good number as to the number of pagers yet.)

EDITED TO ADD: Reuters writes: “The pagers that detonated were the latest model brought in by Hezbollah in recent months, three security sources said.” That implies supply chain attack. And it seems to be a large detonation for an overloaded battery.

This reminds me of the 1996 assassination of Yahya Ayyash using a booby trapped cellphone.

EDITED TO ADD: I am deleting political comments. On this blog, let’s stick to the tech and the security ramifications of the threat.

EDITED TO ADD (9/18): More explosions today, this time radios. Good New York Times explainer. And a Wall Street Journal article. Clearly a physical supply chain attack.

EDITED TO ADD (9/18): Four more good articles.

Python Developers Targeted with Malware During Fake Job Interviews

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/python-developers-targeted-with-malware-during-fake-job-interviews.html

Interesting social engineering attack: luring potential job applicants with fake recruiting pitches, trying to convince them to download malware. From a news article

These particular attacks from North Korean state-funded hacking team Lazarus Group are new, but the overall malware campaign against the Python development community has been running since at least August of 2023, when a number of popular open source Python tools were maliciously duplicated with added malware. Now, though, there are also attacks involving “coding tests” that only exist to get the end user to install hidden malware on their system (cleverly hidden with Base64 encoding) that allows remote execution once present. The capacity for exploitation at that point is pretty much unlimited, due to the flexibility of Python and how it interacts with the underlying OS.

Reinventing the Amazon Q Developer agent for software development

Post Syndicated from Laurent Callot original https://aws.amazon.com/blogs/devops/reinventing-the-amazon-q-developer-agent-for-software-development/

Amazon Q Developer is the most capable AI-powered assistant for software development that reimagines the experience across the entire software development lifecycle, making it easier and faster to build, secure, manage, and optimize applications on AWS. Using your natural language input and your project context, Amazon Q Developer’s agent for software development autonomously implements multi-file features, bug fixes, and unit tests in your integrated development environment (IDE) workspace. For example, you can ask Amazon Q Developer to add a new checkout feature to your e-commerce app, and it will analyze your existing codebase, map out the implementation plan spanning multiple files, and upon your approval, execute all the required code changes and tests in minutes. To get started building with the Q Developer agent, install the Amazon Q extension and use the /dev command inside the chat window.

Amazon Q Developer is constantly improving and redefining what the state-of-the-art is for software development agents. The Amazon Q Developer agent for software development was one of the first agents to publish their results on the industry-recognized SWE-bench benchmark leaderboard. This benchmark is designed to measure the ability to solve real-world coding problems a Python software developer would encounter. This newest update to the Amazon Q Developer agent for software development out-performs the previous version released in May, resolving 51% more tasks on the SWE-bench verified dataset and 43% more on the full dataset. In just a few months, the agent’s scores have increased from 25.6% tasks resolved to 38.8% on the verified dataset and from 13.82% to 19.75% on the full dataset, making it the top performing agent on the leaderboard for 4 weeks. In our June 2024 blog post, we provided an overview explaining how our first submission of Amazon Q Developer was able to top the benchmarks. Since then, the SWE-bench submission process has begun to require the publication of agent trajectories — meaning, a log of the steps taken by an agent to solve a given problem. We welcome this transparency as a critical ingredient of developer trust, so we are proud to share the trajectories of our newest agent.

This video demonstrates the kind of tasks you can now accomplish with the Amazon Q Developer agent for software development. For example, you can refactor a Lambda function to improve clarity and scalability of an app in mere minutes. In the prompt we provide a few specific requirements to the agent: split the logic into multiple Lambdas, avoid duplication of functionality, keep permissions locked down, and update the infrastructure as code to support the change. The agent gets to work and keeps you updated in real time about what it is doing. Once it is done, you can review the code and merge it with a single click.

We have reinvented our agent to take advantage of the new capabilities offered by state-of-the-art AI models, incorporate developer feedback, and bring together the results of dozens of experiments, with proven results. SWE-bench offers a tangible way to share performance measurements, but it is only one component of the way we evaluate the Amazon Q Developer agent for software development. The best way to measure the capabilities of the agent is to test it out for yourself on the tasks that you care about. This blog post shows you how to use the new agent and provides an overview of how the technology behind our reinvented agent works.

Getting started with the Amazon Q Developer agent

To get started, you need to have an AWS Builder ID or be part of an organization with an AWS IAM Identity Center instance set up that allows you to use Amazon Q. To use Amazon Q Developer agent for software development in Visual Studio Code, start by installing the Amazon Q extension. The extension is also available for JetBrains, Visual Studio (in preview), and in the Command Line on macOS. Find the latest version on the Amazon Q Developer page.

The Amazon Q extension tile in the VSCode marketplace

After authenticating, you can invoke the feature development agent by entering /dev in the chat field.

Invoking /dev in the Amazon Q chat window

Let’s say you are exploring the amazon-science/auto-rag-eval GitHub repository. This repository contains a method to automatically evaluate retrieval-augmented language models as described in this amazon.science blog. This method constructs multiple choice questions based on the documents contained in a RAG index. Each question has a single correct answer and multiple incorrect answers, or distractors. You notice that the number of distractors is hard coded to be 3. You would like it to be a parameter instead, so you ask the agent to make this change.

The query to the agent and its initial response

The agent starts exploring your code base and shares updates in real-time summarizing its state, the changes that it is making, and the files being used. The agent starts by exploring the code base.

The agent reports a summary of changes in real-time and lists files used

After a few steps, the agent has identified the key chunks of code to modify and how to modify them.

The state of the agent after 4 steps

The agent iterates on implementing its modifications until it succeeds. At that point, you can see that one file auto-rag-eval/ExamGenerator/distractors_generator.py has been changed.

The final state of the agent with the changed file

Once it is done, the agent shows you a list of the files that it has modified, here distractors_generator.py. Clicking on the file name opens a diff view in your IDE.

The list of modified files

You can review the modifications in each file and decide whether to accept them. If the generated code could be improved, you can provide this feedback to the agent and request that it regenerates it.

The code diff created by the agent

Getting the most out of the AI-powered software development agent

The Amazon Q Developer agent for software development works at its best when requests are aimed and precise. This does not mean that you have to write very long requests, “add unit tests to MyMethod” is clear. When the task is more ambiguous, for example, when you want the agent to resolve a bug in your code, it is helpful to include an error trace. When you want the agent to develop new features, explaining the context, being specific about desired behavior, specifying where the change should be made when known, or even relevant snippets of code or pseudo-code helps the agent focus to achieve the best results.

How the improved Amazon Q Developer agent for software development works

The agent is continuously updated and improved to give you better performance. During the past months the ability of foundation models to drive agentic workflows and leverage large sets of tools to accomplish complex tasks has improved significantly. Guided by customer feedback, we have redesigned our agent to take advantage of these new abilities. Our inspiration is the workflow of experienced developers getting to work on an unfamiliar code base.

When developers want to accomplish a task on an unfamiliar code base, they start by getting a bird’s-eye view of the repository to obtain a general understanding of the project. They then dive deeper into the parts that are relevant to their task. Developers frequently rely on visual IDEs such as VSCode or IntelliJ to explore repositories and implement changes. Although some LLMs have the ability to interpret images, the fidelity of that interpretation, particularly for information-dense images, is far from what is required for an application as complex as software development agents.

AWS has developed a new framework for the Amazon Q Developer agent — textcode — which provides a text-based alternative to visual IDEs specifically designed for LLMs. It effectively equips the agent with its own IDE with which it interacts exclusively through text. The agent is able to use it similarly to how a developer would use a regular IDE to solve your tasks. textcode is designed to provide token-efficient text representations of code, code files, and code workspaces. It allows LLMs to interact with a code base in a similar manner to how a developer interacts with it in a visual IDE. This framework offers structured and efficient environment within which it is easy for the agent to use tools, take actions, and evaluate its progress towards the completion of the assigned task.

The agent is equipped with tools to explore the workspace, act on it, and evaluate its solutions. For example, the agent can open, create, and close files, select and deselect code chunks, find and replace code, and revert changes if needed. These tools allows the agent to navigate the workspace in order to identify and retain the critical pieces of information to solve your tasks while discarding superfluous code to not clog its context. We are continuously expanding the toolkit of the agent with more powerful tools.

A diagram representing the agent's workflow

When you use the \dev command in your IDE, the Q Developer agent for software development is initialized with your problem statement as well as some guidance on how to solve the problem and use the tools it is equipped with. The agent determines what actions to use on the workspace. It generally starts by exploring the workspace to discover the parts of the code relevant to solving your task. The agent takes action by using the tools it is equipped with. The response of the tools is incorporated in an updated prompt that is provided back to the LLM to decide its next actions.

The Q Developer agent is equipped with logic to prevent it from getting stuck in unproductive paths and help it progress towards a solution to your problem. The agent will autonomously decide that it has generated the appropriate changes (including writing unit tests and updating documentation) to fulfill your request. At that point, the agent exits its loop and returns the candidate code patches for your review. You can decide to accept them entirely or in part, or ask the agent to modify them. If you ask for modifications, the agent will resume its loop using your feedback as additional information about the problem statement.

Conclusion

This post introduced the updated Amazon Q Developer agent for software development. The agent autonomously implements features that you describe using natural language directly from your IDE. We gave you an overview of how the agent works behind the scenes and discussed its significantly increased accuracy.

You are now ready to explore the capabilities of Amazon Q Developer agent for software development and make it your AI coding assistant! Install the Amazon Q Developer extension in your IDE of choice and start using Amazon Q (including the agent for software development) for free using your AWS Builder ID or subscribe to Amazon Q Developer to unlock higher limits.

Upcoming Speaking Engagements

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/upcoming-speaking-engagements-40.html

This is a current list of where and when I am scheduled to speak:

  • I’m speaking at eCrime 2024 in Boston, Massachusetts, USA. The event runs from September 24 through 26, 2024, and my keynote is at 8:45 AM ET on the 24th.
  • I’m briefly speaking at the EPIC Champion of Freedom Awards in Washington, DC on September 25, 2024.
  • I’m speaking at SOSS Fusion 2024 in Atlanta, Georgia, USA. The event will be held on October 22 and 23, 2024, and my talk is  at 9:15 AM ET on October 22, 2024.

The list is maintained on this page.

Microsoft Is Adding New Cryptography Algorithms

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/microsoft-is-adding-new-cryptography-algorithms.html

Microsoft is updating SymCrypt, its core cryptographic library, with new quantum-secure algorithms. Microsoft’s details are here. From a news article:

The first new algorithm Microsoft added to SymCrypt is called ML-KEM. Previously known as CRYSTALS-Kyber, ML-KEM is one of three post-quantum standards formalized last month by the National Institute of Standards and Technology (NIST). The KEM in the new name is short for key encapsulation. KEMs can be used by two parties to negotiate a shared secret over a public channel. Shared secrets generated by a KEM can then be used with symmetric-key cryptographic operations, which aren’t vulnerable to Shor’s algorithm when the keys are of a sufficient size.

The ML in the ML-KEM name refers to Module Learning with Errors, a problem that can’t be cracked with Shor’s algorithm. As explained here, this problem is based on a “core computational assumption of lattice-based cryptography which offers an interesting trade-off between guaranteed security and concrete efficiency.”

ML-KEM, which is formally known as FIPS 203, specifies three parameter sets of varying security strength denoted as ML-KEM-512, ML-KEM-768, and ML-KEM-1024. The stronger the parameter, the more computational resources are required.

The other algorithm added to SymCrypt is the NIST-recommended XMSS. Short for eXtended Merkle Signature Scheme, it’s based on “stateful hash-based signature schemes.” These algorithms are useful in very specific contexts such as firmware signing, but are not suitable for more general uses.

The 360’s have a new home!

Post Syndicated from Adam Bradley original https://www.ibm360.co.uk/?p=916

So, if you read our last post, you undoubtedly know that we were looking to relocate the collection to an organisation that was going to display it and potentially restore it. We had many, many interested parties reach out to us from museums all over the world to private collectors interested in acquiring the machines. When we set out to rescue the 360’s Chris and I decided that our main goal was their preservation, and everything else was by the wayside. We evaluated each and every opportunity presented to us for a new home for the 360’s, and found an organisation who we considered to be exactly what we’d been looking for.

System Source Museum got in touch with us very shortly after we made the post to register their interest. We had an initial engagement call with them, and were very impressed by their attitude and approach. Ideally Chris & I wanted to maintain ownership of the systems, and System Source were very happy to take them on a long term loan basis. Chris flew over to see them in Maryland and was again extremely impressed with their collection, display, team, and approach to restoration & conservation. We drew up a contract together, signed the various agreements, and two of their team, Ryan Schiff (Vice President) & Ryan Burke (Assistant Museum Director), flew to the UK to package and ship the systems.

Soon enough, a delivery of bespoke sized pallets (made for the sizes of the machines) arrived at Creslow, and a huge delivery of packing material was delivered to my house (filling my lounge!):

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The team arrived the next day and we set about planning how to package the machines, spares, consumables etc. safely and securely for their transatlantic voyage. The System Source chaps had procured and had delivered a steel strapping machine and a large amount of strapping which would be used to secure the machines to the pallets. This was coupled with moving blankets, cardboard corners, bubble wrap, packaging tape etc. etc. Soon enough we started loading machines onto the pallets:

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When it came to the larger items, these presented a problem. The forklift truck available at Creslow doesn’t fit into the building because of the cage height, and the floor probably wouldn’t support its weight anyway. We therefore had to come up with a different solution. Cue the return of the ramp we built all of those years ago on a street in Nuremberg!

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Yes, it still exists, and it had one final use moving IBM’s. It may have cost 150 euros in wood, but we’ve had our moneys worth!

Pretty quickly the 370 was loaded, strapped, and wrapped:

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Now, the big question arrived. With a long, custom sized pallet, how do you move it? Two pallet trucks, one at each end, would’ve been possible but would’ve restricted where the machines could be placed. It was then we discovered that you can buy double length, wide fork pallet trucks. Dutifully the next day the System Source team went off to Pallet Truck World (yes, really) to acquire such an item:

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This made moving everything about 100 times easier, and we could now shift the pallets around the room with ease.

So, next up was the first 360 CPU. This presented more of a challenge as the cables hanging under the system, which are wired directly into the backplane, meant we couldn’t use the ramp method. After scratching our heads for a few minutes we concocted a solution involving a car jack & a pile of wood:

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Now this probably looks really sketchy, and thats because, like everything moving big iron related, it was. First, we jacked up the front of the machine to a height slightly above that of the pallet, and then wedged in some wood on the supporting rail. We then positioned the pallet under the front wheels of the CPU, and smacked out the wood. This enabled us to roll the machine forward onto the pallet as far as the angle of attack would allow, and we then jacked up the back of the machine and rolled it forward on the jack enabling us to locate it fully onto the pallet. This may sound slightly convoluted but it was actually a very quick operation, and by the third machine we were getting quite good at it!

Because the cables are hard wired into the CPU’s, we had to bundle them and cable tie them to the ends of the machines, later wrapping them in a significant amount of bubble wrap and blankets to protect them from crush risk:

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We continued loading items throughout the next few days, using the same method each time:

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For the exceptionally heavy item, the master tape drive, we decided to reinforce the pallet for extra security. This involved a trip to Wickes to buy some plywood (Wickes is no Bauhaus, trust me), which we then cut and secured to the pallet:

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This enabled the loading of the nearly 1 tonne tape drive:

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We then boxed and crated up the spares & consumables for easy shipping:

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Some of the slightly more bizarre items we had acquired, like spare System 3 parts, were also palletised and used as support structures to ship other items such as loose pannels:

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With all of the machines palletised and strapped down, we set about wrapping everything in bubble wrap, moving blankets, and pallet wrap:

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We also cut and used pieces of 2×4 to box in the wheels so the machines wouldn’t move at all during transit:

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Having started on the 10th of May, and finished packing everything on the 17th, it was time for the trucks. Because of the Francis Scott Key Bridge collapse at the Port of Baltimore, shipping had become a real challenge. It took the team several days to identify and engage with a shipping provider that could do the end to end move for a reasonable price. Eventually they did, and two trucks arrived to take the machines. I dutifully climbed into the forklift and loaded them one by one onto the trucks. Please don’t judge my forklift driving too harshly, at the time the brakes were… well, the less said the better.


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With everything loaded up, the trucks departed and we waved goodbye to the machines as they’re off to their new home.

On October 18th System Source Museum will be holding a special gallery opening for the IBM 360’s, and I’m very happy to say that we’ll be in attendance to see them in their new home. We’re exceptionally pleased that we found somewhere that was not only willing to take the machines on a loan basis, but is going to display them to the public, restore them to working order, and use them as tools to educate future generations. It was a real pleasure working with the team from System Source on the project, and I’d like to extend to them my personal thanks for the highly professional and effective approach they’ve taken to the project.

I’ll write an update when we go to see the machines in their new home, and hopefully we’ll be able to keep updating the blog as they progress with their restoration.

Evaluating the Effectiveness of Reward Modeling of Generative AI Systems

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/evaluating-the-effectiveness-of-reward-modeling-of-generative-ai-systems-2.html

New research evaluating the effectiveness of reward modeling during Reinforcement Learning from Human Feedback (RLHF): “SEAL: Systematic Error Analysis for Value ALignment.” The paper introduces quantitative metrics for evaluating the effectiveness of modeling and aligning human values:

Abstract: Reinforcement Learning from Human Feedback (RLHF) aims to align language models (LMs) with human values by training reward models (RMs) on binary preferences and using these RMs to fine-tune the base LMs. Despite its importance, the internal mechanisms of RLHF remain poorly understood. This paper introduces new metrics to evaluate the effectiveness of modeling and aligning human values, namely feature imprint, alignment resistance and alignment robustness. We categorize alignment datasets into target features (desired values) and spoiler features (undesired concepts). By regressing RM scores against these features, we quantify the extent to which RMs reward them ­ a metric we term feature imprint. We define alignment resistance as the proportion of the preference dataset where RMs fail to match human preferences, and we assess alignment robustness by analyzing RM responses to perturbed inputs. Our experiments, utilizing open-source components like the Anthropic preference dataset and OpenAssistant RMs, reveal significant imprints of target features and a notable sensitivity to spoiler features. We observed a 26% incidence of alignment resistance in portions of the dataset where LM-labelers disagreed with human preferences. Furthermore, we find that misalignment often arises from ambiguous entries within the alignment dataset. These findings underscore the importance of scrutinizing both RMs and alignment datasets for a deeper understanding of value alignment.

Australia Threatens to Force Companies to Break Encryption

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/australia-threatens-to-force-companies-to-break-encryption.html

In 2018, Australia passed the Assistance and Access Act, which—among other things—gave the government the power to force companies to break their own encryption.

The Assistance and Access Act includes key components that outline investigatory powers between government and industry. These components include:

  • Technical Assistance Requests (TARs): TARs are voluntary requests for assistance accessing encrypted data from law enforcement to teleco and technology companies. Companies are not legally obligated to comply with a TAR but law enforcement sends requests to solicit cooperation.
  • Technical Assistance Notices (TANs): TANS are compulsory notices (such as computer access warrants) that require companies to assist within their means with decrypting data or providing technical information that a law enforcement agency cannot access independently. Examples include certain source code, encryption, cryptography, and electronic hardware.
  • Technical Capability Notices (TCNs): TCNs are orders that require a company to build new capabilities that assist law enforcement agencies in accessing encrypted data. The Attorney-General must approve a TCN by confirming it is reasonable, proportionate, practical, and technically feasible.

It’s that final one that’s the real problem. The Australian government can force tech companies to build backdoors into their systems.

This is law, but near as anyone can tell the government has never used that third provision.

Now, the director of the Australian Security Intelligence Organisation (ASIO)—that’s basically their FBI or MI5—is threatening to do just that:

ASIO head, Mike Burgess, says he may soon use powers to compel tech companies to cooperate with warrants and unlock encrypted chats to aid in national security investigations.

[…]

But Mr Burgess says lawful access is all about targeted action against individuals under investigation.

“I understand there are people who really need it in some countries, but in this country, we’re subject to the rule of law, and if you’re doing nothing wrong, you’ve got privacy because no one’s looking at it,” Mr Burgess said.

“If there are suspicions, or we’ve got proof that we can justify you’re doing something wrong and you must be investigated, then actually we want lawful access to that data.”

Mr Burgess says tech companies could design apps in a way that allows law enforcement and security agencies access when they request it without comprising the integrity of encryption.

“I don’t accept that actually lawful access is a back door or systemic weakness, because that, in my mind, will be a bad design. I believe you can ­ these are clever people ­ design things that are secure, that give secure, lawful access,” he said.

We in the encryption space call that last one “nerd harder.” It, and the rest of his remarks, are the same tired talking points we’ve heard again and again.

It’s going to be an awfully big mess if Australia actually tries to make Apple, or Facebook’s WhatsApp, for that matter, break its own encryption for its “targeted actions” that put every other user at risk.

YubiKey Side-Channel Attack

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/yubikey-side-channel-attack.html

There is a side-channel attack against YubiKey access tokens that allows someone to clone a device. It’s a complicated attack, requiring the victim’s username and password, and physical access to their YubiKey—as well as some technical expertise and equipment.

Still, nice piece of security analysis.

Security Researcher Sued for Disproving Government Statements

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/security-researcher-sued-for-disproving-government-statements.html

This story seems straightforward. A city is the victim of a ransomware attack. They repeatedly lie to the media about the severity of the breach. A security researcher repeatedly proves their statements to be lies. The city gets mad and sues the researcher.

Let’s hope the judge throws the case out, but—still—it will serve as a warning to others.

List of Old NSA Training Videos

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/09/list-of-old-nsa-training-videos.html

The NSA’s “National Cryptographic School Television Catalogue” from 1991 lists about 600 COMSEC and SIGINT training videos.

There are a bunch explaining the operations of various cryptographic equipment, and a few code words I have never heard of before.