SelfOp: An Optimization Algorithm for Self-Improving Security Agents

Reported by arXiv cs.CR (Saad Ullah, Yigitcan Kaya, Christopher Kruegel, Giovanni Vigna, Gianluca Stringhini)

Summary by Cyber Security News22 Sep 2026, 06:00 CEST

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/2609.22792

arXiv:2609.22792v1 Announce Type: new Abstract: LLM agents are increasingly used for security tasks: vulnerability discovery, exploit reproduction, and patch generation. Improving them at the model level demands expert demonstrations or computable rewards, which security tasks rarely offer: traces are costly, failures hard to diagnose, rewards sparse, and non-computable.

Read the full article at arXiv cs.CR →

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