MetaVul: Agentic Harness Discovery for Vulnerability Detection

Reported by arXiv cs.CR (Ira Ceka, Arnav Garg, Ryan Lutz, Ting Zhang, Ratnadira Widyasari, Gail Kaiser, Baishakhi Ray)

Summary by Cyber Security News2 Nov 2026, 06:00 CET

About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.40721

arXiv:2610.40721v1 Announce Type: new Abstract: LLM agents are increasingly used to automate vulnerability detection, but reliable detection is challenging because agents must distinguish subtle, security-relevant fixes from benign code variation. While underlying LLM capability has improved significantly, the accuracy of the agent still depends heavily on the harness: the code that defines the scaffolding around the LLM.

Read the full article at arXiv cs.CR →

Source attribution: headline and facts are from arXiv cs.CR (arxiv.org). Summary method: excerpt of the source description. See our source attribution policy.

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