arXiv:2605.26548v1 Announce Type: cross Abstract: Large language models (LLMs) now support automated software security tasks, including vulnerability discovery and proof-of-concept (PoC) generation. Existing benchmarks do not faithfully evaluate LLMs in real-world bug hunting scenarios because they rely on fuzzing harnesses, target-specific descriptions, or vulnerability-reproduction tasks. We present SEC-bench Pro, a benchmark for measuring agent bug hunting on critical, high-complexity software systems. This work discloses reports with concrete PoC inputs and links fixes into reproducible ta
The rapid advancement of LLMs has reached a point where their application to complex, real-world software security challenges is becoming feasible and demands rigorous evaluation.
This development indicates a significant step towards autonomous AI agents capable of performing high-value and critical security tasks, which can profoundly impact cybersecurity defenses and the vulnerability landscape.
The ability of LLMs to independently discover and exploit software vulnerabilities changes the dynamics of software security, potentially shifting from human-centric to AI-augmented or even AI-driven defensive and offensive capabilities.
- · AI software security companies
- · Organizations with advanced cybersecurity AI
- · Developers leveraging AI for secure coding
- · Software developers with vulnerable codebases
- · Traditional manual bug hunting services
- · Cyber adversaries without AI defense capabilities
AI agents will become an indispensable tool in the software development lifecycle, specifically for security auditing and vulnerability management.
The cost and speed of discovering and patching software vulnerabilities will be dramatically altered, leading to a more secure-by-design software ecosystem but also potentially to more sophisticated AI-driven attacks.
The reliance on AI for critical security tasks could raise new concerns around the explainability, bias, and potential unintended consequences of autonomous systems in cybersecurity, necessitating new regulatory and ethical frameworks.
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