arXiv:2609.22664v1 Announce Type: new Abstract: Research on large language model agents for penetration testing is evaluated almost entirely by capability: whether the agent captures a flag or reproduces a proof of concept.
From Capability to Assurance in Autonomous Penetration-Testing Harnesses: A Framework and Reference Implementation
About this summary. This is a short, independently written summary of an article first published by arXiv cs.CR. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2609.22664
Source attribution: headline and facts are from arXiv cs.CR (arxiv.org). Summary method: excerpt of the source description. See our source attribution policy.
Related coverage
Code Security Review tool
Posted by E. Kellinis on Sep 22 Karma Pro is an open source code review tool that can assist code reviewers with a multitude of useful tools. Karma Pro is a macOS…
Anthropic-linked CVEs pile up, attackers mostly shrug
Despite the concern that advanced AI models’ bug-hunting prowess will lead to attackers exploiting more newly uncovered CVEs, fewer than 0.5 percent of the…
Roundcube security advisory (AV26-503) – Update 1
Serial number: AV26-503 Date: May 25, 2026 Updated: September 21, 2026 On May 24, 2026, Roundcube published security advisories to address vulnerabilities in the…
Re: Emacs arbitrary code execution: incomplete fix for CVE-2024-53920
Posted by Tomas Hoger on Sep 21 Is GitHub going to assign a CVE here? I think GitHub assignment would be ok per this part of the GitHub CNA scope definition…
Be alert: targeted attacks on prominent Rustaceans
Be alert: targeted attacks on prominent Rustaceans Important warning from Adam Harvey and the crates security team: We believe that there is an ongoing campaign…
LLMs respond differently to harmful prompts when AI watermarking is used
In response to a new European Union law, AI platforms are implementing new schemes for watermarking the content they generate. Anthropic recently disclosed its future…