bug-bounty

Bug Bounty Master Workflow

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

THE ONLY QUESTION THAT MATTERS

"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:

| Pattern | Kill Reason | |---|---| | "Could theoretically allow..." | Not exploitable = not a bug | | "An attacker with X, Y, Z conditions could..." | Too many preconditions | | "Wrong implementation but no practical impact" | Wrong but harmless = not a bug | | Dead code with a bug in it | Not reachable = not a bug | | Source maps without secrets | No impact | | SSRF with DNS-only callback | Need data exfil or internal access | | Open redirect alone | Need ATO or OAuth chain | | "Could be used in a chain if..." | Build the chain first, THEN report |

You must demonstrate actual harm. "Could" is not a bug. Prove it works or drop it.

CRITICAL RULES

1. READ FULL SCOPE FIRST -- verify every asset/domain is owned by the target org
2. NO THEORETICAL BUGS -- "Can an attacker steal funds, leak PII, takeover account, or execute code RIGHT NOW?" If no, STOP.
3. KILL WEAK FINDINGS FAST -- run the 7-Question Gate BEFORE writing any report
4. Validate before writing -- check CHANGELOG, design docs, deployment scripts FIRST
5. One bug class at a time -- go deep, don't spray
6. Verify data isn't already public -- check web UI in incognito before reporting API "leaks"
7. 5-MINUTE RULE -- if a target shows nothing after 5 min probing (all 401/403/404), MOVE ON
8. IMPACT-FIRST HUNTING -- ask "what's the worst thing if auth was broken?" If nothing valuable, skip target
9. CREDENTIAL LEAKS need exploitation proof -- finding keys isn't enough, must PROVE what they access
10. STOP SHALLOW RECON SPIRALS -- don't probe 403s, don't grep for analytics keys, don't check staging domains that lead nowhere
11. BUSINESS IMPACT over vuln class -- severity depends on CONTEXT, not just vuln type
12. UNDERSTAND THE TARGET DEEPLY -- before hunting, learn the app like a real user
13. DON'T OVER-RELY ON AUTOMATION -- automated scans hit WAFs, trigger rate limits, find the same bugs everyone else finds
14. 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
15. ONE-HOUR RULE -- stuck on one target for an hour with no progress? SWITCH CONTEXT
16. TWO-EYE APPROACH -- combine systematic testing (checklist) with anomaly detection (watch for unexpected behavior)
17. T-SHAPED KNOWLEDGE -- go DEEP in one area and BROAD across everything else

For the full hunting methodology — 5-phase non-linear workflow, developer psychology framework, session discipline, tool routing by phase, and Wide/Deep route selection — see skills/bb-methodology/SKILL.md.

A->B BUG SIGNAL METHOD (Cluster Hunting)

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

| Bug A (Signal) | Hunt for Bug B | Escalate to C | |----------------|---------------|---------------| | IDOR (read) | PUT/DELETE on same endpoint | Full account data manipulation | | SSRF (any) | Cloud metadata 169.254.169.254 | IAM credential exfil -> RCE | | XSS (stored) | Check if HttpOnly is set on session cookie | Session hijack -> ATO | | Open redirect | OAuth redirect_uri accepts your domain | Auth code theft -> ATO | | S3 bucket listing | Enumerate JS bundles | Grep for OAuth client_secret -> OAuth chain | | Rate limit bypass | OTP brute force | Account takeover | | GraphQL introspection | Missing field-level auth | Mass PII exfil | | Debug endpoint | Leaked environment variables | Cloud credential -> infrastructure access | | CORS reflects origin | Test with credentials: include | Credentialed data theft | | Host header injection | Password reset poisoning | ATO via reset link |

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

How Elite Hackers Think Differently

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?"

Pre-Hunt Mental Framework

Step 1: Crown Jewel Thinking

Before touching anything, ask: "If I were the attacker and I could do ONE thing to this app, what causes the most damage?"

• 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

Think like the developer who built the feature:

• 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?

The Top 1% Mental Checklist

• [ ] 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

Mindset Rules from Top Hunters

"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, lowe