hunt-rce
Hunt-RCE identifies remote code execution vulnerabilities in bug bounty targets by analyzing 67 public reports to reveal high-value attack surfaces. Use this skill when testing enterprise servers, package registries, Kubernetes infrastructure, mobile backends, and admin consoles for RCE through template injection, deserialization, dependency confusion, and configuration parameter manipulation. The skill maps specific URL patterns, response headers, and technology stacks to their corresponding exploitation vectors.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/hunt-rce && cp -r /tmp/hunt-rce/skills/hunt-rce ~/.claude/skills/hunt-rceSKILL.md
## Autonomous Testing Priority
**Content-type is the #1 silent failure mode for command injection.**
Traditional web forms use `Content-Type: application/x-www-form-urlencoded`. If you send a JSON body (`{"host":"127.0.0.1;id"}`) to a form endpoint, the server reads `request.form['host']` and gets nothing — the app executes normally with no injection, returning a plausible 200 response. You get a false negative with no indication anything went wrong.
**Rule:** If the page has an HTML form (`<form method="POST">`), use form-encoding. If the path is `/api/...` or the response is JSON, use JSON.
**Command injection operators to try (in order of prevalence):**
```
value;id ← Unix semicolon (most common)
value|id ← pipe
value&&id ← AND
value$(id) ← subshell
value`id` ← backtick
```
**Proof:** OS command output (`uid=N(username) gid=...`) in the response body confirms code execution. The output may be HTML-wrapped — that still counts. If the response is otherwise normal (200, expected content) with the command output appended or embedded, exploitation is confirmed.
---
## Crown Jewel Targets
RCE vulnerabilities command the highest payouts in bug bounty programs because they grant attackers direct execution control over target infrastructure. The highest-value targets are:
**Highest-paying asset types:**
- **Enterprise server products** (GitHub Enterprise Server, self-hosted GitLab) — privilege escalation chains from low-privileged console roles to root SSH access consistently pay critical/high
- **Supply chain / package registries** — dependency confusion attacks against npm, PyPI, etc. hit critical severity across every major program
- **Cloud-native infrastructure** — exposed Kubernetes API servers, ingress controllers, and misconfiqured CI/CD pipelines
- **Mobile app backends and OAuth flows** — where server-side processing of attacker-controlled data meets execution contexts
- **Admin/management consoles** — template injection in configuration panels reaches root with a single payload
**Why this class pays most:**
- Blast radius is infrastructure-wide, not user-scoped
- Proof-of-concept is unambiguous — shell output is undeniable
- Fix requires architectural changes, not just a patch
- Programs cannot afford false negatives on RCE
---
## Attack Surface Signals
### URL Patterns
```
/management-console/*
/admin/settings/*
/api/v*/exec
/api/v*/run
/webhook/*
/_internal/*
/import?url=
/render?template=
/preview?format=
```
### Response Headers / Tech Stack Signals
```
X-Powered-By: Express # Node.js — npm dependency surface
X-Powered-By: Phusion Passenger
Server: nginx (ingress-nginx) # Kubernetes ingress — path field injection
X-Runtime: Ruby # Rails ActiveStorage, RDoc, REXML attack surface
Content-Type: application/yaml # YAML parsers (SnakeYAML, Psych) — deserialization
X-GitHub-Enterprise-Version # GHAS — nomad template, collectd, syslog-ng injection
```
### JavaScript / Frontend Signals
```javascript
// Look for these patterns in JS bundles
fetch('/api/exec', {method:'POST', body: cmd})
eval(userInput)
new Function(userInput)
document.write(unsafeData)
window.location = userControlled // URL scheme bypass → JS execution
```
### Tech Stack Signals
| Signal | RCE Vector |
|--------|-----------|
| `nomad` in config UI | Template injection → `{{ ... }}` |
| `syslog-ng` config editable | Config injection → `program()` destination |
| `collectd` config editable | Plugin exec injection |
| `SnakeYAML` in classpath | `!!javax.script.ScriptEngineManager [...]` |
| npm `package.json` internal scope | Dependency confusion |
| ingress-nginx annotations | Path field regex bypass |
---
## Step-by-Step Hunting Methodology
1. **Map the execution contexts first.** Before testing payloads, identify everywhere user-controlled input touches an execution layer: template engines, shell commands, YAML parsers, file paths used in operations, package resolution, and configuration files.
2. **Enumerate admin/management interfaces.** Crawl for `/management-console`, `/admin`, `/_internal`, `/setup`, `/config`. These surfaces are lower-auth and higher-privilege — the GHES cluster produced 6 separate RCEs from one console role.
3. **Check template injection in every config field.** In any management UI that accepts free-form configuration (log destinations, notification formats, proxy settings), submit `{{7*7}}`, `${7*7}`, `<%= 7*7 %>`. Look for `49` in responses, logs, or DNS callbacks.
4. **Test YAML/XML/serialized input for code execution.** Any endpoint accepting `Content-Type: application/yaml` or `application/xml`:
- SnakeYAML: submit `!!javax.script.ScriptEngineManager` gadget
- Ruby YAML: submit `!ruby/object:Gem::Installer` gadget
- REXML: submit billion-laughs / quadratic blowup XML
5. **Hunt dependency confusion.** For every npm/pip/gem internal package name visible in JS bundles, error messages, or `package.json` in public repos — register a higher-versioned package on the public registry pointing to a canary callback.
6. **Check file path operations for traversal → execution.** ActiveStorage, file upload handlers, symlink operations: submit `../../../etc/cron.d/shell` as filename. Confirm write then trigger execution.
7. **Audit Kubernetes/cloud-native surfaces.** Run `kubectl` against any exposed API server. Check ingress annotations, especially `nginx.ingress.kubernetes.io/configuration-snippet` and `spec.rules.http.paths.path` for Lua/regex injection.
8. **Test OAuth redirect URI and URL scheme handlers.** Mobile apps processing `javascript:` or `intent://` URIs via OAuth redirect may execute JavaScript. Try `javascript:alert(document.cookie)` and custom scheme URIs.
9. **Verify with out-of-band callbacks.** Never rely solely on visible output. Use Burp Collaborator, interactsh, or `canarytokens.org` DNS tokens. Blind RCE is common in backend processors.
10. **Chain privileges.** A low-severity misconfigEnd-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.