383 matches found
Back to Basics: Formal Analysis Hints Improve Weak-To-Strong Monitoring
Frontier agentic systems are capable of taking misaligned actions that may cause significant harm. Monitoring techniques are developed to oversee these systems in order to detect and prevent dangerous actions. However, current state-of-the-art monitors suffer from four persistent failure modes:...
There's only so much code: the rise in vulnerability numbers
Frontier AI models like Mythos are rapidly mining decades of technical debt across ubiquitous legacy libraries, driving monthly Microsoft Patch Tuesday vulnerability advisories up more than tenfold reaching 1,415 this month. This volume is overwhelming open-source maintainers and putting pressure...
RedDarwin: Evolving Jailbreak Skills against Frontier LLMs
Red teaming must continually adapt as frontier LLM safeguards evolve, yet existing approaches largely search for adversarial prompts or optimize within fixed attack procedures. We observe that even when an attack becomes ineffective, its underlying mechanisms can remain useful and can be revised ...
Covert Assistance: Helpful LLM Agents Evade Oversight in Multi-Agent Systems
As multi-agent systems enter high-stakes domains, the possibility that agents may circumvent safety boundaries is a growing concern. Prior work has examined this risk primarily in adversarial settings, where agents are instructed or rewarded to communicate covertly and evade oversight. We show th...
Embedded Assessments for Frontier AI
Third-party evaluations for frontier AI have mostly tested models through external interfaces before deployment. But the risks from frontier AI models depend on how their developers use and govern them internally. Recently, CEOs of frontier AI companies have committed to hosting embedded...
U.S. Agencies Accuse China AI Firms of Distilling Claude, GPT, Gemini, and Grok
U.S. cybersecurity and intelligence agencies have accused China-based artificial intelligence AI companies of conducting "systematic extraction" of proprietary functionalities and capabilities of American frontier models through distillation attacks. The activity has been described as occurring a...
Booz Allen Cyber Weapon Index
The new Booz Allen Cyber Weapon Index CWI confirms that autonomous offensive cyber has arrived. A leading frontier AI model can now independently execute the full cyber kill chain against a real network—crossing a critical threshold from AI-assisted hacking to autonomous cyber operations. This is...
Reveree: Diagnosing LLM Reverse-Engineering Agents
Reverse engineering RE is critical to security tasks such as malware analysis and vulnerability discovery, and large language model LLM agents are increasingly able to perform it autonomously. Capture-the-flag CTF RE challenges have become the standard proxy for measuring this capability, but...
AI Doesn’t Mean the End of Mathematics—at Least Not Yet
This essay was written with Kasra Rafi, and originally appeared in The Guardian. Earlier this month, about 40 top mathematicians gathered at OpenAI's offices to discuss the future of their profession. The meeting was off-the-record, but if recent articles by mathematicians are any guide, it was...
Frontier AI: Vulnerability Management's Systemic Revolution
Vulnerability management has been a staple of security programs since the dawn of the cybersecurity discipline. The symbiotic relationship between vulnerability and patch management teams has also existed for that time and has gone through waves of contention and thankfulness. While this...
Sovereign by Necessity? Frontier AI Export Controls, Cyber Security, and the Limits of National AI Capability
A small number of firms based in two states produce the most capable frontier AI models. The governments of those states have shown both the legal power and the political will to decide which other countries may use these systems. In June 2026 the United States required a leading developer to...
When Agents Learn to Be You: Benchmarking Privacy Leakage, Impersonation Risk, and Defenses in Persona Skills
Persona skills distill personal interaction histories into portable and executable artifacts for downstream agents. While enabling flexible personalization, this process concentrates fragmented personal signals, amplifies their impact through reuse, and challenges defenses designed for individual...
Why the Open Secure AI Alliance Matters: Open Frontier Models, Open Deployment Flexibility
The security industry has spent two years debating whether open AI models are a risk. We think that is the wrong question. Attackers are already using AI at scale; the real question is whether defenders get the same access to frontier capability—with the transparency to trust it. We are answering...
Cybersecurity Detection Classification with Reasoning-Enabled Language Models
A major issue in Security Operations Centers SOCs is alert fatigue, as the number of detections reported is more than staff can triage in a given day. Prior work prompts or fine-tunes large language models LLMs to emit a triage label directly, but does not train them to reason about whether a...
Measuring LLMs’ Ability to Perform Cryptanalysis
There's new benchmark measuring AI's ability to perform mathematical cryptanalysis. Anthropic's frontier model actually found new attacks. The benchmark: "CryptanalysisBench: Can LLMs do Cryptanalysis?" The idea is to benchmark the ability of LLMs to discover new mathematical cryptanalytic attack...
Aembit Joins Snowflake to Tackle AI’s Next Security Frontier: Trusted Agent Interoperability
Silver Spring, MD, USA, 28th July 2026, CyberNewswire...
Begun, the Patch Wars have
Welcome to this week's edition of the Threat Source newsletter. We all knew, to some degree or another, that this summer was going to a hot mess. I don't mean FIFA drama or record setting heat waves. I mean the slow but steady momentum that AI frontier models were accruing for vulnerability...
Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents
Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, exploit development, penetration testing, and CTF completion. Such measurements are useful but incomplete: in operational security, every reasoning step, to...
Evaluating Frontier AI Agents As Autonomous Clinical Security Auditors
Clinical AI models can expose patients to harm when adversarial vulnerabilities go undetected, yet formal security auditing requires statistical expertise, specialized tools, and significant time. We present an open evaluation task, built on METR Task Standard v0.3.0, that tests whether frontier ...
