Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Configure perform API fuzzing to discover edge cases, crashes, and security vulnerabilities. Use when performing specialized testing. Trigger with phrases like "fuzz the API", "run fuzzing tests", or "discover edge cases".
.claude/skills/jeremylongshore-fuzzing-apis/SKILL.md| Model | Eval pass | Runs |
|---|---|---|
| gemini-3.6-flash | 100% | 19 |
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-06 | ✗→✓ | ▲ Improved | 68% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 77% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 61% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 33% | 0% |
| case-23 | ✗→✓ | ▲ Improved | 94% | 0% |
Perform API fuzzing to discover crashes, unhandled exceptions, security vulnerabilities, and edge case failures by sending malformed, unexpected, and boundary-value inputs to API endpoints. Supports RESTler (stateful REST API fuzzing), Schemathesis (OpenAPI-driven property-based testing), custom fuzz harnesses with fast-check, and OWASP ZAP active scanning.
**/openapi.yaml, **/swagger.json).%s%n), path traversal (../../etc/passwd).schemathesis run http://localhost:3000/openapi.json --stateful=links.restler-fuzzer fuzz --grammar_file grammar.py.| Error | Cause | Solution | |-------|-------|---------| | Fuzzer cannot parse API spec | Invalid or incomplete OpenAPI specification | Validate the spec with swagger-cli validate; fix schema errors before fuzzing | | All requests return 401 | Authentication not configured in fuzzer | Provide auth headers via --set-header "Authorization: Bearer TOKEN" or config file | | Server crashes during fuzzing | Unhandled exception or resource exhaustion | Restart the server with a process manager; enable crash dump collection; add OOM killer threshold | | Too many false positives (500 errors) | Application returns 500 for expected validation errors | Filter known error patterns; configure the fuzzer to ignore specific response bodies | | Fuzzer generates unrealistic inputs | Schema-based generation produces impossible combinations | Add x-examples to the OpenAPI spec; use stateful fuzzing to maintain valid sequences |
Schemathesis OpenAPI fuzzing:
bash# Basic schema-based fuzzing schemathesis run http://localhost:3000/api/openapi.json \ # 3000: 3 seconds in ms --stateful=links \ --hypothesis-max-examples=500 \ # HTTP 500 Internal Server Error --base-url=http://localhost:3000 \ # 3 seconds in ms --header "Authorization: Bearer $TEST_TOKEN" # With specific checks schemathesis run http://localhost:3000/api/openapi.json \ # 3 seconds in ms --checks all \ --validate-schema=true
fast-check property-based API test:
typescriptimport fc from 'fast-check'; import request from 'supertest'; import { app } from '../src/app'; test('POST /api/users handles arbitrary input without crashing', async () => { await fc.assert( fc.asyncProperty( fc.record({ name: fc.string(), email: fc.string(), age: fc.oneof(fc.integer(), fc.string(), fc.constant(null)), }), async (body) => { const res = await request(app).post('/api/users').send(body); expect(res.status).toBeLessThan(500); // No server errors # HTTP 500 Internal Server Error } ), { numRuns: 200 } # HTTP 200 OK ); });
Custom fuzz dictionary for injection testing:
json[ "' OR '1'='1", "<script>alert(1)</script>", "${7*7}", "{{7*7}}", "../../../etc/passwd", "\u0000", "A".repeat(100000) # 100000 = configured value ]
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 8,626 | 15,212 | +76% | 1 | 1 | 0% | 891 | 2,671 | +200% | 0 | 0 | — |
case-02 | fail→fail | 15,304 | 15,365 | +0% | 1 | 1 | 0% | 1,365 | 2,490 | +82% | 0 | 0 | — |
case-03 | pass→pass | 16,799 | 17,286 | +3% | 1 | 1 | 0% | 2,206 | 3,690 | +67% | 0 | 0 | — |
case-04 | pass→pass | 16,516 | 17,245 | +4% | 1 | 1 | 0% | 3,319 | 5,054 | +52% | 0 | 0 | — |
case-05 | pass→pass | 13,067 | 17,855 | +37% | 1 | 1 | 0% | 2,519 | 4,035 | +60% | 0 | 0 | — |
case-06 | fail→pass | 6,856 | 8,687 | +27% | 1 | 1 | 0% | 1,285 | 2,155 | +68% | 0 | 0 | — |
case-07 | fail→fail | 9,965 | 4,156 | -58% | 1 | 1 | 0% | 914 | 2,318 | +154% | 0 | 0 | — |
case-08 | pass→fail | 21,539 | 26,441 | +23% | 1 | 1 | 0% | 3,693 | 5,289 | +43% | 0 | 0 | — |
case-09 | pass→pass | 29,368 | 28,863 | -2% | 1 | 1 | 0% | 4,052 | 6,190 | +53% | 0 | 0 | — |
case-10 | pass→pass | 9,941 | 3,319 | -67% | 1 | 1 | 0% | 1,488 | 2,154 | +45% | 0 | 0 | — |
case-11 | fail→pass | 13,399 | 5,609 | -58% | 1 | 1 | 0% | 1,481 | 2,626 | +77% | 0 | 0 | — |
case-12 | pass→pass | 11,801 | 9,733 | -18% | 1 | 1 | 0% | 2,213 | 3,436 | +55% | 0 | 0 | — |
case-13 | fail→fail | 24,658 | 18,781 | -24% | 1 | 1 | 0% | 3,638 | 2,931 | -19% | 0 | 0 | — |
case-14 | fail→fail | 18,823 | 17,557 | -7% | 1 | 1 | 0% | 3,541 | 3,422 | -3% | 0 | 0 | — |
case-15 | pass→pass | 25,261 | 26,237 | +4% | 1 | 1 | 0% | 4,694 | 6,449 | +37% | 0 | 0 | — |
case-16 | pass→pass | 15,620 | 13,579 | -13% | 1 | 1 | 0% | 3,023 | 4,241 | +40% | 0 | 0 | — |
case-17 | pass→pass | 16,948 | 10,423 | -39% | 1 | 1 | 0% | 2,140 | 3,871 | +81% | 0 | 0 | — |
case-18 | fail→pass | 16,239 | 19,742 | +22% | 1 | 1 | 0% | 2,903 | 4,682 | +61% | 0 | 0 | — |
case-19 | fail→pass | 14,030 | 8,174 | -42% | 1 | 1 | 0% | 2,067 | 2,749 | +33% | 0 | 0 | — |
case-20 | pass→pass | 18,284 | 22,984 | +26% | 1 | 1 | 0% | 2,815 | 4,520 | +61% | 0 | 0 | — |
case-21 | pass→pass | 18,217 | 23,602 | +30% | 1 | 1 | 0% | 2,936 | 4,676 | +59% | 0 | 0 | — |
case-22 | pass→pass | 9,417 | 9,239 | -2% | 1 | 1 | 0% | 1,567 | 3,108 | +98% | 0 | 0 | — |
case-23 | fail→pass | 11,493 | 9,532 | -17% | 1 | 1 | 0% | 1,261 | 2,449 | +94% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +17 percentage points is the difference between those two pass rates over the 23 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.