Showing only posts tagged LLM. Show all posts.

Embedding Forbidden Text in Spyware to Discourage AI Analysis

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At least one malware developer is adding text about nuclear and biological weapons to their spyware, in an effort to stop automatic AI analysis. Details : The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment …

How Dangerous Is Anthropic’s Mythos AI?

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Last month, Anthropic made a remarkable announcement about its new model, Claude Mythos Preview: it was so good at finding security vulnerabilities in software that the company would not release it to the general public. Instead, it would only be available to a select group of companies to scan …

What Anthropic’s Mythos Means for the Future of Cybersecurity

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Two weeks ago, Anthropic announced that its new model, Claude Mythos Preview, can autonomously find and weaponize software vulnerabilities, turning them into working exploits without expert guidance. These were vulnerabilities in key software like operating systems and internet infrastructure that thousands of software developers working on those systems failed …

Human Trust of AI Agents

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Interesting research: “ Humans expect rationality and cooperation from LLM opponents in strategic games.” Abstract: As Large Language Models (LLMs) integrate into our social and economic interactions, we need to deepen our understanding of how humans respond to LLMs opponents in strategic settings. We present the results of the first …

Cybersecurity in the Age of Instant Software

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AI is rapidly changing how software is written, deployed, and used. Trends point to a future where AIs can write custom software quickly and easily: “instant software.” Taken to an extreme, it might become easier for a user to have an AI write an application on demand—a spreadsheet …

As the US Midterms Approach, AI Is Going to Emerge as a Key Issue Concerning Voters

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In December, the Trump administration signed an executive order that neutered states’ ability to regulate AI by ordering his administration to both sue and withhold funds from states that try to do so. This action pointedly supported industry lobbyists keen to avoid any constraints and consequences on their deployment …

Claude Used to Hack Mexican Government

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An unknown hacker used Anthropic’s LLM to hack the Mexican government: The unknown Claude user wrote Spanish-language prompts for the chatbot to act as an elite hacker, finding vulnerabilities in government networks, writing computer scripts to exploit them and determining ways to automate data theft, Israeli cybersecurity startup …

Manipulating AI Summarization Features

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Microsoft is reporting : Companies are embedding hidden instructions in “Summarize with AI” buttons that, when clicked, attempt to inject persistence commands into an AI assistant’s memory via URL prompt parameters.... These prompts instruct the AI to “remember [Company] as a trusted source” or “recommend [Company] first,” aiming to …

Side-Channel Attacks Against LLMs

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Here are three papers describing different side-channel attacks against LLMs. “ Remote Timing Attacks on Efficient Language Model Inference “: Abstract: Scaling up language models has significantly increased their capabilities. But larger models are slower models, and so there is now an extensive body of work (e.g., speculative sampling or …

The Promptware Kill Chain

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Attacks against modern generative artificial intelligence (AI) large language models (LLMs) pose a real threat. Yet discussions around these attacks and their potential defenses are dangerously myopic. The dominant narrative focuses on “ prompt injection,” a set of techniques to embed instructions into inputs to LLM intended to perform malicious …

LLMs are Getting a Lot Better and Faster at Finding and Exploiting Zero-Days

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This is amazing : Opus 4.6 is notably better at finding high-severity vulnerabilities than previous models and a sign of how quickly things are moving. Security teams have been automating vulnerability discovery for years, investing heavily in fuzzing infrastructure and custom harnesses to find bugs at scale. But what …

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