
XBOW: Getting to 'Should I?' Instead of 'Can I?'
XBOW describes how its autonomous pentesting agent detects IDORs (insecure direct object references) with fewer false positives by first having agents log in as different roles (admin, manager, user) and passively document expected access boundaries, then using that observed baseline to validate suspicious findings instead of reasoning about authorization in a vacuum. The post argues traditional DAST tools miss IDORs because they lack ownership context, and details XBOW's shift from an "attacker/validator debate" model to multi-role, multi-account exploration for grounding authorization judgments.
TL;DR XBOW explains its approach to reducing false positives in AI-driven IDOR/authorization testing by first learning per-role "normal" behavior before validating access-control violations.
Technologies named here
Techniques named here
- IDOR testing
- Role-based exploration / behavioral baselining
- Self-debate validation reasoning
- Multi-account / multi-authentication testing
- IDOR
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