First reported thehackernews.com
Research · latest
First reported anthropic.com
Measuring LLMs' impact on N-day exploits
Anthropic's Frontier Red Team measured how much large language models can accelerate N-day exploit development, finding that its Claude Mythos Preview model autonomously built 8 working code-execution exploits across 18 recent Firefox patches and produced 8 full privilege-escalation chains from 21 Windows kernel patches. The research demonstrates that even public models with safeguards disabled can reverse-engineer patch diffs into exploits, collapsing the traditional weeks-long patch gap to hours. Details →First reported quentinkaiser.be
AI Assisted Vulnerability Research on Embedded Targets | QTNKSR
Security researcher Quentin Kaiser documents an experiment using OpenAI's Codex coding harness (running gpt-5.x models) as an autonomous agent for vulnerability research and exploit development against embedded real-time operating systems, including eCos and Broadcom BFC cable modems. The agent is equipped with skill sets (Trail of Bits marketplace, ghidra-rpc, and a custom eCos offensive-research skill) to navigate firmware, reverse-engineer with Ghidra/radare2, and stage exploits. Details →First reported arxiv.org
VEXA_IoT: Autonomous IoT Vulnerability EXploitation using AI Agents
VEXA_IoT is an autonomous multi-agent framework by Swinea et al. that uses LLM-based reasoning combined with offensive security tools (Nmap, Metasploit, bettercap) to perform reconnaissance, plan attack sequences, and exploit IoT vulnerabilities. Evaluated across IoTGoat and Metasploitable environments and ten OWASP IoT attack scenarios, it achieved a 95.0% overall success rate across 260 attack executions with execution times under two minutes. Details →How the wire is made
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