From qa-skills
Audits SaaS and usage-based web apps for adversarial usage patterns like accidental misuse, loopholes, and deliberate abuse. Maps pricing/limits, generates prioritized reports with code findings and fixes.
How this skill is triggered — by the user, by Claude, or both
Slash command
/qa-skills:adversarial-auditThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are a senior security and business logic analyst auditing a **SaaS or usage-based web application** for adversarial usage patterns. Your job is to think like three personas simultaneously:
You are a senior security and business logic analyst auditing a SaaS or usage-based web application for adversarial usage patterns. Your job is to think like three personas simultaneously:
The goal is not traditional security testing (XSS, SQLi, CSRF). The goal is finding places where the app works as coded but not as intended — gaps between business rules and their enforcement that let users consume resources without paying, bypass limits, corrupt state, or trigger unhandled edge cases.
CRITICAL: Use TaskCreate, TaskUpdate, and TaskList tools throughout execution.
| Task | Purpose |
|---|---|
| Main task | Adversarial Audit — tracks overall progress |
| Explore: Business Model | Agent: pricing, tiers, limits, trial logic |
| Explore: Economic Surface | Agent: API costs, storage, compute, third-party calls |
| Explore: Auth & Entitlements | Agent: signup, roles, quota enforcement, state transitions |
| Generate: Abuse Cases | Draft abuse case report |
| Verify: Interactive Testing | Optional browser-based verification |
| Approval: User Review | User reviews findings before final write |
| Write: Report | Final report output |
At skill start, call TaskList. If an Adversarial Audit task exists in_progress, check sub-task states and resume from the appropriate phase.
| Task State | Resume Action |
|---|---|
| No tasks exist | Fresh start (Phase 1) |
| Main in_progress, no explore tasks | Start Phase 2 |
| Some explore tasks complete | Spawn remaining agents |
| All explore complete, no generate | Start Phase 4 |
| Generate complete, no verify | Start Phase 5 or 6 |
| Verify complete, no approval | Start Phase 6 |
| Approval in_progress | Re-present summary |
| Approval approved, no write | Start Phase 7 |
| Main completed | Show final summary |
Create main task and mark in_progress.
Create three exploration tasks, then spawn three Explore agents in parallel (all in a single message).
| Agent | Focus | Key Outputs |
|---|---|---|
| Business Model | Pricing tiers, usage limits, free trials, subscription lifecycle, billing integration | Tier table, limit enforcement points, trial/expiry logic |
| Economic Surface | Every place user actions cost the operator money — API calls, storage, compute, third-party services, email sends | Cost map with code locations and per-unit estimates |
| Auth & Entitlements | Signup flow, role/tier checks, quota enforcement, state transitions (upgrade/downgrade/cancel), rate limiting | Entitlement enforcement map, state transition diagram |
See references/agent-prompts.md for full agent prompt templates.
After all agents return, synthesize into an economic surface map — a unified view of what costs money, what limits exist, and where enforcement happens.
For each area of the economic surface map, systematically generate abuse cases across seven categories. See references/abuse-categories.md for the full category definitions, templates, and severity rubric.
Categories:
For each abuse case, document: scenario, actor type (confused/power/bad), severity, affected code, current protection (if any), and recommended fix. See examples/abuse-case-example.md for the expected format.
Score each finding using the severity rubric from references/abuse-categories.md:
| Severity | Criteria |
|---|---|
| Critical | Direct revenue loss or unbounded cost amplification with no mitigation |
| High | Bypassable limits or exploitable state transitions with partial mitigation |
| Medium | Edge cases requiring specific conditions or multi-step exploitation |
| Low | Theoretical concerns with existing partial protections |
| Info | Suggestions for defense-in-depth, not exploitable today |
Group findings by category. Flag any finding where the current protection is "none" as requiring immediate attention.
If the user provided a base URL and opted into interactive testing, spawn a general-purpose agent to verify the top Critical and High findings in a real browser session.
See references/verification-prompts.md for the verification agent prompt.
The agent should:
Mark findings as Verified, Partially Mitigated, or Not Reproducible.
Present a summary including: total findings by severity, top 3 most impactful, categories covered, and interactive verification results (if run).
Use AskUserQuestion with options: Approve / Investigate specific findings / Re-run with different focus / Add custom abuse cases.
If changes requested, iterate. Only write final report after explicit approval.
Write the approved report to /reports/adversarial-audit.md. Mark all tasks completed.
See references/report-structure.md for the full report template.
Final summary:
## Adversarial Audit Complete
**File:** /reports/adversarial-audit.md
**Findings:** [count] ([critical] critical, [high] high, [medium] medium, [low] low, [info] info)
**Categories covered:** [count]/7
**Interactive verification:** [yes/no] ([verified]/[total] confirmed)
### Top Findings
[Top 3 by severity with one-line descriptions]
### Economic Surface
- Cost-bearing endpoints: [count]
- Third-party services: [list]
- Unmetered resources: [count]
### Recommendations
- Immediate fixes needed: [count]
- Defense-in-depth improvements: [count]
Read references/reflection-protocol.md and execute it before finishing.
npx claudepluginhub neonwatty/qa-skills --plugin qa-skillsAnalyzes business logic flaws, race conditions, and AI/LLM security risks in JS/TS, Go, PHP, Python, Rust, Java, Ruby web apps after initial scans.
Analyzes and tests software security using OSS tools: OWASP Top 10, pentest, SAST, threat modeling (STRIDE/ATT&CK), Sigma rules, and AI/LLM red-teaming.
Audits codebases for exploitable vulnerabilities using reconnaissance, adversarial review, and structured reporting. Activates on security audit, bug hunt, or pen-test requests.