AWE: Adaptive Agents for Dynamic Web Penetration Testing
Modern web applications are increasingly produced through AI-assisted development and rapid no-code deployment pipelines, widening the gap between accelerating software velocity and the limited adaptability of existing security tooling. Pattern-driven scanners fail to reason about novel contexts, while emerging LLM-based penetration testers rely on unconstrained exploration, yielding high cost, unstable behavior, and poor reproducibility. We introduce AWE, a memory-augmented multi-agent framework for autonomous web penetration testing that embeds structured, vulnerability-specific analysis pipelines within a lightweight LLM orchestration layer. Unlike general-purpose agents, AWE couples c...
| Authors | Akshat Singh Jaswal, Ashish Baghel |
|---|---|
| Primary category | cs.CR |
| Published | 1 March 2026 |
| Last updated at source | 1 March 2026 |
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