evidence-hygiene
Evidence Hygiene is a bug-bounty submission discipline for redacting cookies, tokens, and personally identifiable information from screenshots, HAR files, and proof-of-concept artifacts before sharing with platforms or triagers. Use it whenever capturing screenshots, exporting HAR files, or preparing any evidence containing session cookies, OAuth tokens, real user names/emails, or account credentials to prevent accidental disclosure of sensitive data while preserving triager-useful metadata like trace IDs and request identifiers.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/evidence-hygiene && cp -r /tmp/evidence-hygiene/skills/evidence-hygiene ~/.claude/skills/evidence-hygieneSKILL.md
# EVIDENCE HYGIENE — PoC Capture & Redaction Discipline
> Use this skill BEFORE capturing any screenshot, exporting any HAR, or attaching any evidence to a bug-bounty submission. It catches the most common evidence-hygiene mistakes that cause cookies to leak, PII to be shared without consent, or screenshots to be unsuitable for triage.
The core principle: **Bug-bounty evidence is meant to convince a triager. Anything beyond that — live cookies, real-user PII, internal trace IDs that aren't useful — should not be in the evidence.**
---
## 1. Two Categories of Sensitive Data
Every PoC artifact (screenshot, HAR, raw HTTP request, terminal transcript) potentially contains data that needs different treatment.
| Category | Examples | Treatment |
|---|---|---|
| **Your-account secrets** | Session cookies, OAuth tokens, refresh tokens, API keys | Always redact. Even in private bug-bounty platform attachments. Your account, your session — protect it. |
| **Other users' PII** | Real names, emails, phone numbers, addresses, profile photos, account IDs | Redact unless explicitly demonstrating cross-account impact. Even then, mask faces and minimize the data you display. |
| **Triager-useful metadata** | Trace IDs (`x-datadog-trace-id`), request IDs, server timestamps, your test account UID/email, GraphQL operation names, response shapes | **Leave visible** — these help the triager correlate to logs and reproduce. |
| **Test-account passwords (limited use)** | Throwaway passwords on a test account (e.g., `Testing@5678`) | Acceptable in screenshots if you rotate immediately after submission so the value shown is dead. Don't leave real-use passwords in evidence. |
---
## 2. Cookie Redaction Protocol
### 2.1 What must be masked
The session cookie value is the highest-value secret in any PoC. Mask:
- The session cookie (`authn`, `session`, `sid`, `__Secure-id`, etc. — name varies per target)
- `csrf-token` if it's bound to your session
- `Authorization` headers (Bearer tokens, JWT)
- `Cookie` request header values for any session-bearing cookie
- `Set-Cookie` response header values for any session-bearing cookie
### 2.2 What's safe to leave visible
- Cloudflare cookies (`__cf_bm`, `_cfuvid`) — these are bot-management, not session-bearing
- Analytics cookies (`ajs_anonymous_id`, `_ga`)
- Trace correlation IDs (`x-datadog-trace-id`, `x-request-id`)
- Server / framework headers (`Server: cloudflare`, `X-Frame-Options`)
- Your test account email/UID (per Bugcrowdninja alias section in `bugcrowd-reporting`)
### 2.3 Redaction methods (ranked by practicality)
**Method A — Don't capture the cookies in the first place** (preferred when possible)
- For DevTools Console PoCs: use `credentials: 'include'` so the browser sends cookies automatically. Console output won't echo the cookie. Screenshot the Console output, never the Network tab Headers panel.
- For Burp Repeater PoCs: drag the bottom request/response panel divider DOWN to hide the request body before screenshotting. Capture only the Results table for Intruder runs.
**Method B — Black-bar in image editor** (when capture inevitably includes cookies)
- macOS: Open screenshot in Preview → Tools → Annotate → Rectangle → set fill color to black → drag rectangle over the cookie value → save
- Windows: Use Snip & Sketch's annotation tools or any image editor (Paint.NET, etc.)
- Burp itself: in Burp's Proxy → Match and Replace, you can pre-emptively redact cookie values to placeholder strings before screenshotting
**Method C — Find/replace in raw text** (for HAR files, terminal transcripts)
- See §4 for the jq commands
### 2.4 Pre-screenshot checklist
Before clicking Capture:
```
[ ] Network tab Headers panel is collapsed or out of frame
[ ] Burp's Request panel is hidden behind the divider drag
[ ] No "Copy as cURL" output is visible on screen
[ ] DevTools Application → Storage → Cookies tab is closed
[ ] Browser URL bar doesn't show a session token in query string (rare but possible)
```
After capturing:
```
[ ] Open the screenshot at full resolution before saving
[ ] Search for the session cookie name substring in any visible text — if present, redact
[ ] Search for the literal first 6 chars of your cookie value — if present, redact
[ ] Compare to the previous PoC screenshot in the same engagement — same redaction discipline
```
---
## 3. PII Black-Bar Protocol
When a PoC necessarily exposes another user's data (e.g., demonstrating IDOR by showing the victim's email in an attacker-session response), redact the actual PII even in private attachments.
### 3.1 What to mask (other-user data)
- First name, last name (full or partial)
- Email address (mask the local part; can leave domain if non-identifying)
- Phone number (mask the last 7 digits, optionally leave country code)
- Physical address (mask everything below city)
- Date of birth (mask the year, optionally the month)
- Government IDs (SSN, passport — mask everything)
- Profile photos / face images (black-bar the face entirely)
- Account IDs that the user could correlate to public profiles
### 3.2 What to leave visible (proves the bug, not the user)
- The fact that the field was returned (the JSON key name)
- The shape / type of the field (`"first_name": "<REDACTED>"`)
- Your own (attacker session's) UID / email — this proves cross-account
- The endpoint URL and request method
- The trace ID
### 3.3 Worked example — IDOR PoC body
**Bad (leaks victim's full PII):**
```json
{"data":{"contact":{"first_name":"Nadene","last_name":"Afton","email":"nadene.afton@example.com","phone":"+1-555-867-5309"}}}
```
**Good (proves the bug, masks the PII):**
```json
{"data":{"contact":{"first_name":"<REDACTED — real first name>","last_name":"<REDACTED — real last name>","email":"<REDACTED>@example.com","phone":"<REDACTED>"}}}
```
In screenshot form, black-bar each value with a rectangle annotation labeled "REAL PII REDACTED" if there's space.
### 3.4 In the report body
Reference the redactEnd-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.