First reported paloaltonetworks.com
Research · latest
First reported portswigger.net
Can AI do novel security research? Meet the HTTP Terminator | PortSwigger Research
PortSwigger's James Kettle built HTTP Terminator, an AI-assisted autonomous research system that explored 30,000 candidate HTTP desync vectors, invented new attack techniques (novel desync triggers, a dual-matching Content-Length pattern, and a "dangling-byte" response-queue-poisoning method), and used them to find roughly 700 vulnerable targets across 30,000 authorized sites including banks, government infrastructure, and an airport, plus an Apache Traffic Server zero-day. Kettle presented the work at Black Hat USA 2026 and DEF CON 34 and open-sourced the HTTP Terminator system. Details →First reported thehackernews.com
Kimi K3 Agents Found Redis Zero-Days and Built RCE Exploit, Researchers Say
Researchers report that Kimi K3 AI agents autonomously discovered multiple Redis zero-day memory-corruption flaws and built working authenticated RCE proof-of-concept exploits against stock Redis 6.2.22, 7.4.9, 8.6.4, and 8.8.0; the chains abuse RESTORE (plus EVAL/XGROUP and the RedisBloom module), and Redis shipped seven security releases on July 23 to fix the Streams shared-NACK use-after-free and RedisBloom/TDigest out-of-bounds writes. Defenders are advised to upgrade and revoke RESTORE from accounts that do not need it. Details →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 bleepingcomputer.com
We built a vulnerability vending machine: AI tokens in, zero-days out
Intruder describes building an automated pipeline that pairs LLMs with the Joern code-scanning engine and a 'program slice' technique to find and exploit vulnerabilities in production software with no human in the loop. The team reports discovering a remote, multi-stage SQL injection zero-day (CVE-2026-3985) in a WordPress plugin with over 300,000 users, fully automated from discovery through exploitation. 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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