Individual skill
broken-access-control
Replay captured requests with swapped identities and bumped object IDs to surface broken access control. Use when testing for IDOR or authz flaws.
skills/applicative-pentest/broken-access-control/SKILL.md
Source commit 0c1bc93fd5124e7a862d61c1b434f32ba8790e3a
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- Yes
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- Observed behavior
- Not checked yet
- Last checked
- Nov 5, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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- Repository stars (not skill ratings)
- 153
- Repository last updated
- Nov 8, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-security Repository topic
- ai-skills Repository topic
- security-skills Repository topic
- dynamic-workflow Repository topic
- testing Derived category
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## Contents
- Scope & authorization
- Methodology (baseline, identity-swap, numeric IDOR)
- Runnable snippets
- IDOR numeric-parameter wordlist
- Thresholds (carry these exactly)
- Output
## Scope & authorization
Only run against an application the user owns or is contractually engaged to test. This is an ACTIVE, aggressive check: it re-sends real requests to the target under different identities and with mutated object-ids, so it creates traffic, may read or touch other users' data, and can trip rate-limits or alerts. Use a staging environment or a maintenance window where you can, keep the identities and object-ids to accounts you control, and stop if you start returning data that clearly belongs to real third parties. If scope is unclear, ask before replaying.
Two things must exist before you start:
1. A capture of the target's traffic taken as a **privileged / higher-role user** (from a proxy, HAR export, or your own request log). Each captured request gives you the method, URL, headers, query params, cookies, and body.