bb-methodology
Skill5.5k starsChanged 5 months agoMITView on GitHub
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.
7 other projects use a version of this, 3 of them edited.
Trending
More talk lately.thin dataabout the whole repository
Most recently taken up by
- shuvonsec/claude-bug-bountyword for word, first seen Oct 8, 2026
- gl1tch0x1/SecAgenttheir own version, first seen Sep 29, 2026
- Gabson0x/bountyforgetheir own version, first seen Sep 16, 2026
- ajtazer/heckitedited, first seen Sep 11, 2026
- elementalsouls/Claude-BugHunteredited, first seen Jul 1, 2026
- awarexone/Agentic-Bug-Hunterword for word, first seen Jun 9, 2026
Who's talking about Awarexone/Agentic-Bug-Hunter
- vavkamil/awesome-bugbounty-tools“Add Agentic Bug Bounty Hunter to AI Agents”GitHub · Sep 2, 2026 · 2 reactions
- sudosubin/agents.nix“agent-skills.github.awarexone.agentic-bug-hunter: v6.0.0 → refs/tags/v6.0.0”GitHub · Oct 3, 2026
- djmahe4/cyber-tools-index“[WIP] Update tools_config.json with AI security tools from Medium list”GitHub · Oct 2, 2026
- sudosubin/agents.nix“agent-skills.github.awarexone.agentic-bug-hunter: init at 6.0.0”GitHub · Sep 25, 2026
- beyefendi/awesome-llm-security“Agentic Bug Hunter”GitHub · Sep 18, 2026
The biggest 5 of 11 mentions linking to the repository that our crawl found. Each line is their own headline.
See all 11
Talked about on GitHub (11 times).
On GitHub · 11
- Sep 2, 2026Add Agentic Bug Bounty Hunter to AI Agents — vavkamil/awesome-bugbounty-tools2 reactions
- Oct 3, 2026agent-skills.github.awarexone.agentic-bug-hunter: v6.0.0 → refs/tags/v6.0.0 — sudosubin/agents.nix0 reactions
- Oct 2, 2026[WIP] Update tools_config.json with AI security tools from Medium list — djmahe4/cyber-tools-index0 reactions
- Sep 25, 2026agent-skills.github.awarexone.agentic-bug-hunter: init at 6.0.0 — sudosubin/agents.nix0 reactions
- Sep 18, 2026Agentic Bug Hunter — beyefendi/awesome-llm-security0 reactions
6 more on GitHub
- Sep 6, 2026Enlaces rotos detectados en el README — YamilAyma/enlaces-para-desarrolladores0 reactions · 3 comments
- Sep 2, 2026Add Agentic Bug Bounty Hunter under Attack Surface — edoardottt/awesome-hacker-search-engines0 reactions · 1 comment
- Sep 2, 2026Add Related Projects section (Agentic Bug Bounty Hunter) — maurosoria/dirsearch0 reactions
- Sep 2, 2026Add Agentic Bug Bounty Hunter to GraphQL Injection tools — swisskyrepo/PayloadsAllTheThings0 reactions
- Sep 2, 2026Add Agentic Bug Bounty Hunter to Tools — nahamsec/Resources-for-Beginner-Bug-Bounty-Hunters0 reactions
- Aug 30, 2026Enlaces rotos detectados en el README — YamilAyma/enlaces-para-desarrolladores0 reactions
Other versions7 projects use a version of this.
Word for word · 2
- shuvonsec/claude-bug-bounty★ 5.5k100% same
- awarexone/Agentic-Bug-Hunter★ 5.5k100% same
Edited · 3
- elementalsouls/Claude-BugHunter★ 5.5k68% same
- ajtazer/heckit★ 268% same
- hhjkjkjk/Claude-skills★ 068% same
Wrote their own version · 2
- Gabson0x/bountyforge★ 431same name
- gl1tch0x1/SecAgent★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository21 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- bug-bountySkill
- agentic-app-auditSkill
- argusSkill
- bug-bountySkill
- cicd-securitySkill
- client-reverseSkill
- cloud-pentestSkill
- credential-attackSkill
- graphql-auditSkill
- llm-redteamSkill
- mcp-server-auditSkill
- meme-coin-auditSkill
- mobile-pentestSkill
- report-writingSkill
- security-arsenalSkill
- triage-validationSkill
- web2-reconSkill
- web2-vuln-classesSkill
- web3-auditSkill
The file
We split this skill into the rules it gives an agent
9 rules. 3 are common, 4 are distinctive, and 2 are very specific to this project.
3
Common
Most of the 5 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 20
Before touching any tool:
- Common: line 73
Supply chain: Check framework/library versions for known CVEs
- Distinctive: line 84
Use AI to expand hypotheses, not to declare verdicts.
- Distinctive: line 86
Decompose the feature: ask for actors, assets, entry points, state transitions, and trust boundaries.
- Distinctive: line 91
Turn ideas into requests: every AI suggestion must become a single reproducible HTTP experiment.
- Distinctive: line 92
Kill weak signals fast: if AI cannot point to a concrete request, response diff, or cross-account delta, the idea stays as a hypothesis.
- Very specific: line 262
No error? Time-based (SLEEP(10), .
- Very specific: line 263
No time diff? OOB (curl attacker.com, interactsh) -- watch for DNS callback
- Common: line 358
Every 20 minutes ask yourself: "Am I making progress?"
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Bug Bounty Methodology: Workflow + Mindset
Master orchestrator for hunting sessions. Combines the 5-phase non-linear workflow with the critical thinking framework that separates top 1% hunters from the rest.
PART 1: MINDSET (How to Think)
Core Principle
Hunting is not "find a bug" -- it is "prove an attack scenario." Think like an attacker with a specific goal, not a scanner looking for patterns.
Daily Discipline: Define, Select, Execute
Before touching any tool:
- Define: "Today I target [feature/domain] to achieve [CIA impact]"
- Select: Choose 1-2 vuln classes (IDOR, Race Condition, etc.)
- Execute: Focus ONLY on selected techniques. No wandering.
5 Ultimate Goals (Pick One Per Session)
- Confidentiality -- steal data the attacker shouldn't see
- Integrity -- modify data the attacker shouldn't change
- Availability -- disrupt service (app-level DoS only)
- Account Takeover -- control another user's account
- RCE -- execute commands on the server
4 Thinking Domains
1. Critical Thinking (deep analysis)
Question trust boundaries:
- Frontend control disabled? Send request directly via proxy
user_role=usercookie? Change toadminprice=1000in POST? Change to1<script>blocked? Try<img onerror=...>
Reverse-engineer developer psychology:
- Feature A has auth checks -> Similar feature B (newly added) probably doesn't
- Complex flows (coupon + points + refund) -> Edge cases have bugs
/api/v2/userexists -> Does/api/v1/userstill work with weaker auth?
What-If experiments:
- Skip checkout -> hit
/checkout/successdirectly - Skip 2FA -> navigate to
/dashboard - Send coupon request 10x simultaneously -> Race condition?
- Replace
guid=f8a2...withid=100on sibling endpoint -> IDOR?
2. Multi-Perspective (multiple angles)
| Perspective | What to check |
| Horizontal (same role) | User A's token + User B's ID -> IDOR |
| Vertical (different role) | Regular user -> /admin/deleteUser |
| Data flow (proxy view) | Hidden params in JSON: debug=false, discount_rate |
| Time/State | Race conditions, post-delete session reuse |
| Client environment | Mobile UA -> legacy API with weaker auth |
| Business impact | "What's the $ damage if this breaks?" |
3. Tactical Thinking (pattern detection)
- Naming anomaly:
userIdeverywhere but suddenlyuser_id-> different dev, weaker security - Error diff: Same 403 but different JSON structure -> different backend systems
- 200 but wrong body length/content:
200 OKwith tiny response or "just a moment" text → WAF soft block, not a real response. Runbypass_403.shto confirm and get baseline diff. - Environment diff: Prod vs Dev/Staging -> debug headers, CSP disabled
- Version diff: JS file before/after update -> new endpoints, removed params
- Supply chain: Check framework/library versions for known CVEs
- Third-party integration: Stripe/Auth0/Intercom -> webhook signature missing?
4. Strategic Thinking (big picture)
- Asymmetry: Defender must patch ALL holes. You only need ONE.
- Intuition engineering: Log why something "feels wrong." Verify later. Update mental DB.
- Unknown management: Can't understand something? Add to "investigate later" list. Just-in-Time Learning.
5. AI-Assisted Thinking (model as a second analyst)
Use AI to expand hypotheses, not to declare verdicts. The model is a fast adversarial planner; the browser, proxy, and live requests are the proof layer.
- Decompose the feature: ask for actors, assets, entry points, state transitions, and trust boundaries.
- Generate sibling paths: versioned endpoints, mobile routes, legacy APIs, alternate roles, and admin-only variants.
- Build a role matrix: anonymous, user A, user B, stale session, fresh session, admin, service account.
- Ask for dev shortcuts: "Where would a tired developer skip a check or reuse a helper?"
- Ask for chains: "If this bug is real, what bug B and C sit next to it?"
- Turn ideas into requests: every AI suggestion must become a single reproducible HTTP experiment.
- Kill weak signals fast: if AI cannot point to a concrete request, response diff, or cross-account delta, the idea stays as a hypothesis.
High-signal prompts:
- "Given this endpoint and feature, list the 10 most likely trust-boundary mistakes."
- "What sibling endpoints, methods, or roles should I test next?"
- "Which bug class would a rushed implementation likely miss here?"
- "What does the smallest proof request look like?"
- "What would make this become a real report instead of a scanner hit?"
Amateur vs Pro: 7-Phase Comparison
| Phase | Amateur | Pro |
| Recon | Main domain only | Shadow IT, dev environments, all assets |
| Discovery | Look for errors | Look for design contradictions, business logic flaws |
| Exploit | Give up when blocked | Build filter-bypass payloads |
| Escalation | Report the phenomenon only | Chain to real harm (session steal, ATO) |
| Feasibility | Include unrealistic conditions | Minimize attack prerequisites |
| Reporting | State facts only | Quantify business risk |
| Retest | Check if old PoC fails | Analyze fix method, find incomplete patches |
Two Approach Routes
- Route A (Feature-based): "This feature is complex" -> deep-dive its input handling -> find vuln
- Route B (Vuln-based): "I want IDOR" -> find endpoints with sequential IDs -> test access control
Anti-Patterns (Stop Doing These)
- Program hopping: Stick with one target minimum 2 weeks / 30 hours
- Tool-only hunting: Automation finds duplicates. Manual testing finds unique bugs.
- Rabbit hole: Max 45 min per parameter. Set a timer. If stuck, sleep on it.
- No goal: "Just looking around" = wasted time. Always Define first.
PART 2: WORKFLOW (What to Do)
The 5-Phase Non-Linear Flow
+-------------------------------------------------+
| |
| +----------+ +----------+ +----------+ |
| | 1. RECON |---+| 2. MAP |---+| 3. FIND | |
| +----------+ +-----+----+ +-----+-----+ |
| ^ | | |
| | v v |
| | +----------+ +----------+ |
| +----------| 4. PROVE |---+| 5. REPORT| |
| +----------+ +----------+ |
| |
| Non-linear: stuck at any phase -> go back |
| New API found at phase 3 -> return to phase 2 |
| WAF blocks at phase 4 -> origin IP from phase 1 |
+-------------------------------------------------+THIS IS NOT LINEAR. Move freely between phases. When stuck, return to a previous phase.
Phase 0: SESSION START (Every Time)
Before touching any tool, answer these:
- Define: "Today I target [feature/domain] to achieve [C/I/A/ATO/RCE]"
- Select: Choose 1-2 vuln classes (IDOR, XSS, SSRF, etc.)
- Execute: Focus ONLY on selected techniques
- Identity: Anonymous or authenticated? If the bugs you're hunting need a
session (IDOR, BOLA, privilege escalation, auth bypass, mass-assignment),
load auth once at session start — see
docs/auth-sessions.md. Then every downstream tool (httpx, katana, ffuf, nuclei, dalfox, PoC verifiers) sends those headers automatically and audit log entries are stamped with a stablesession_idhash.
Route selection -- Wide or Deep?
| Signal | Wide (recon sweep) | Deep (focused testing) |
| New program, first day | X | |
Wildcard scope *.target.com | X | |
| Main webapp, been here >3 days | X | |
| Scope update (new domain added) | X | |
| Found interesting subdomain | X | |
| Hunting IDOR / BOLA / auth bugs | X (auth-aware) |
Phase 1: RECON
Goal: Maximize attack surface. Find what others missed.
Wide approach (initial sweep):
Subdomain enum -> DNS resolution -> HTTP probing -> Port scan -> Tech detectDeep approach (targeted):
Google Dorks -> JS file download -> Hidden param discovery -> API mapping| What you find | Next action |
| Live subdomains with tech stack | Phase 2 (Mapping) |
| Known software (WordPress, Jira) | Check CVEs + defaults immediately |
| Cloud resources (S3, Firebase) | Test permissions (read/write/list) |
| 403 or 200 + block page on endpoint | bughunter/tools/bypass_403.sh <url> auto-detects soft blocks (200+block-body). Verdict: bypassed/needs_review/blocked. If all blocked after 5 min, skip |
| Nothing after 5 min on a host | Skip, try next host (5-minute rule) |
Command: /recon target.com
After every recon (mandatory):
python3 bughunter/tools/lead_board.py ingest target.com
python3 bughunter/tools/lead_board.py show target.com
python3 bughunter/tools/lead_board.py next target.com
# Route in plain language: "GraphQL endpoint → skills/graphql-audit"
# touch status when you start / kill / report a lead(hunt.py runs ingest + EOL automatically unless --skip-leads.)
Phase 2: MAPPING & ANALYSIS
Goal: Understand the app like its developer does.
Checklist:
- Map all endpoints (Burp/Caido sitemap + JS analysis)
- Identify auth model (cookie, JWT, OAuth, SAML?)
- Find business-critical flows (payment, registration, password reset, data export)
- Download and analyze JS files for hidden routes, secrets, logic
- Identify roles and permissions (user, admin, API keys)
- Note "weird" behaviors (anomalies in naming, errors, timing)
| What you find | Next action |
| JS files with interesting code | Taint analysis (Sink -> Source) |
| OAuth/SAML authentication | OAuth/SAML checklist |
| API with ID parameters | Phase 3, target IDOR |
| Complex business logic (payment, coupon) | Phase 3, target BizLogic |
| postMessage listeners | DOM analysis, postMessage-tracker |
Phase 3: VULNERABILITY DISCOVERY
Goal: Find the bug. Use Error-based first, then Blind-based.
Decision flow based on what you're testing:
What input are you testing?
+-- ID parameter (user_id, order_id)
| -> IDOR checklist
+-- Search/filter/sort field
| -> SQLi, NoSQLi probing
+-- URL input / webhook / PDF gen
| -> SSRF checklist
+-- Text field reflected in page
| -> XSS (DOM or reflected)
+-- File upload
| -> SVG XSS, web shell, path traversal
+-- Price/quantity/coupon
| -> Business logic, race conditions
+-- Login / 2FA / password reset
| -> Auth bypass
+-- Profile update API
| -> Mass Assignment
+-- Template / wiki editor
| -> SSTI
+-- Nothing obvious
-> Fuzz with ffuf, try Error-based probingError vs Blind decision:
- Try Error-based first (send
',",{{7*7}},${7*7}) -- watch for 500 errors, stack traces - No error? Time-based (
SLEEP(10),; sleep 10;) -- watch response time - No time diff? OOB (
curl attacker.com, interactsh) -- watch for DNS callback - Still nothing? Boolean (
AND 1=1vsAND 1=0) -- watch content-length diff
| What you find | Next action |
| Low-impact behavior (redirect, self-XSS, cookie injection) | Chain it -- find a connector gadget |
| Confirmed vuln (XSS, IDOR, SQLi) | Phase 4 (Prove and Escalate) |
| Blocked by WAF/CSP/403 or soft-block 200 | /bypass-403 <url> → check verdict (not just status) → bughunter/tools/waf_encoder.py "<payload>" → if upload: bughunter/tools/multipart_mutator.py → 5 min, kill |
| Known software vuln (CVE) | 1-day speed workflow |
| Nothing after 20 min on this endpoint | Rotate (20-minute rule) |
Phase 4: PROVE & ESCALATE
Goal: Prove maximum business impact. Turn Low into Critical.
Escalation decision:
What did you find?
+-- XSS
| +-- Can steal cookie/token? -> Session hijack -> ATO
| +-- Cookie is HttpOnly? -> Force email change via XHR -> ATO
| +-- Self-XSS only? -> Find CSRF to trigger it
+-- IDOR
| +-- Can read PII? -> Automate scraping, show scale
| +-- Can change password/email? -> Direct ATO
| +-- UUID only? -> Find UUID leak source, then retry
+-- SSRF
| +-- DNS only? -> DON'T REPORT. Try cloud metadata
| +-- Can reach 169.254.169.254? -> Extract keys -> RCE
| +-- Internal port scan? -> Find Redis/K8s -> RCE
+-- SQLi
| +-- Error-based? -> Extract data (passwords, tokens)
| +-- Can INTO OUTFILE? -> Web shell -> RCE
| +-- Blind? -> Boolean/Time extraction
+-- Open Redirect
| +-- OAuth flow? -> Token theft -> ATO
| +-- javascript: scheme? -> XSS
+-- Blocked by defense
| -> Bypass (WAF/CSP/proxy/sanitizer/2FA)
+-- Low-impact, can't escalate alone
-> Find connector gadget for chainAfter proving impact, check:
- Can attack work with 0-1 clicks? (minimize prerequisites)
- Does it affect all users or specific role?
- What's the business $ impact?
Phase 5: VALIDATE & REPORT
Goal: Get paid. Make triager's job easy.
Pre-report gate:
Run /validate (7-Question Gate)
+-- All 7 pass? -> Write report
+-- Any fail? -> KILL the finding. Don't waste time.
+-- Borderline? -> Run /triage for quick go/no-goReport:
Run /report
+-- Platform-specific format (H1/Bugcrowd/Intigriti/Immunefi)
+-- Title: [Bug Class] in [Endpoint] allows [role] to [impact]
+-- Impact-first summary (sentence 1 = what attacker CAN do)
+-- Exact HTTP requests in Steps to Reproduce
+-- Under 600 words
+-- CVSS 3.1 score that MATCHES actual impactAfter submission:
- While waiting for triage: try to escalate further (A->B signal method)
- If fix deployed: re-test for bypass (incomplete patch = new bug)
- Record finding with
/rememberfor hunt memory
PART 3: NAVIGATION & TIMING
Non-Linear Navigation Quick Reference
| I'm stuck because... | Go to... |
| Can't find any subdomains | Phase 1: Try different recon sources, Google Dorks |
| Found subdomain but don't know what to test | Phase 2: Map the app, download JS, understand auth |
| Testing but nothing works | Phase 3: Switch vuln class (20-min rotation rule) |
| Found a bug but impact is low | Phase 4: Escalation paths or gadget chaining |
| WAF/CSP/403 blocking my payload | /bypass-403 → fingerprint WAF → waf_encoder.py variants → kill if 5 min spent (403 even after /bypass-403 + WAF fingerprint + waf_encoder.py variants) |
| Been stuck for 45 min on one param | STOP. Rabbit hole. Move to next endpoint. |
| New API endpoint discovered during testing | Return to Phase 2: map it before attacking |
| Found one bug | A->B signal: same dev made more mistakes. Hunt 20 min for siblings. |
20-Minute Rotation Clock
Every 20 minutes ask yourself: "Am I making progress?"
- Yes -> Continue
- No -> Rotate to next: endpoint -> subdomain -> vuln class -> target
- Been on same target 2+ weeks with no findings? -> Consider switching program
Tool Routing by Phase
| Phase | Tools | Why this order |
| Recon: Subdomains | subfinder -> amass -> puredns -> httpx | Passive first (no detection) -> resolve DNS -> probe HTTP + tech stack |
| Recon: URLs | gau + waymore -> katana -> uro | Archive (forgotten endpoints) -> active crawl (JS-rendered) -> deduplicate |
| Recon: JS | jsluice + mantra + trufflehog --only-verified | Extract URLs/secrets -> find API keys -> verify keys actually work |
| Recon: Ports | naabu (wide) -> rustscan (deep) | Fast top-1000 sweep -> full 65535 on interesting targets |
| Recon: Scan | nuclei -tags cve -> nuclei -tags takeover | Known CVEs first -> then takeover (act immediately) |
| After recon (ALWAYS) | python3 bughunter/tools/lead_board.py ingest <target> → show → next | Route every signal to a hunt-* skill; never lose a lead. touch when you start/kill/report |
| After recon: EOL | python3 bughunter/tools/eol_check.py --tech "php=7.4,nginx=1.18" | Flag EOL products from technologies.txt fingerprints |
| Mapping: Params | arjun + paramspider + ParamMiner / bughunter/tools/param_discovery.sh | Brute-force hidden params + mine archives + cache headers |
| Mapping: GraphQL | bash bughunter/tools/graphql_audit.sh <url> | Introspection → fingerprint → batching → IDOR → injection |
| Mapping: CI/CD | bash bughunter/tools/cicd_scanner.sh owner/repo | Workflow injection / secret exfil / runner poisoning |
| Mapping: JS code | Download -> jsluice -> VS Code/Cursor grep | Extract -> static analysis -> AI-assisted taint analysis |
| Mapping: Dorks | Manual Google Dorks | Custom per-target queries find what automation misses |
| Discovery: Fuzz | ffuf -ac + cewl custom wordlist | Auto-calibrate filtering + target-specific words beat generic lists |
| Discovery: XSS | kxss -> dalfox | Filter (which params reflect?) -> scan (only reflective params) |
| Discovery: SQLi | ghauri | Modern blind SQLi on ID-like parameters |
| Discovery: SSRF | interactsh-client | Self-hosted OOB listener for blind SSRF/XXE/RCE |
| Discovery: WAF | wafw00f → bughunter/tools/bypass_403.sh → bughunter/tools/waf_encoder.py → waf_response_analyzer.py | Fingerprint → soft-block aware bypass → encoded variants → score response |
| Exploit: 403 | bughunter/tools/bypass_403.sh / byp4xx | Soft-block (200+block body) aware; verdict: bypassed/needs_review/blocked |
| Exploit: Upload | bughunter/tools/multipart_mutator.py --file shell --field f | Parser-confusion multipart variants |
| Exploit: Takeover | bughunter/tools/takeover_scanner.sh / subzy | CNAME against vulnerable services |
| Exploit: Cloud | bughunter/tools/cloud_recon.sh + aws CLI | Scan bucket permissions -> extract metadata credentials |
| Exploit: Secrets | bughunter/tools/secrets_hunter.sh / trufflehog --only-verified | Only verified working keys (no false positives) |
| Orchestrate | python3 bughunter/tools/hunt.py --target T | Recon → lead ingest → EOL → scan (add --graphql / --cve-hunt as needed) |
Session End Checklist
lead_board.py show <target>— any high-priority leads stillnew/ stale?- Save all Burp/Caido project files
- Record any "weird but not yet exploitable" behaviors (future gadgets)
- Update notes with failed attempts (don't re-test with same techniques)
- Log findings with
/remember touchevery lead you killed or reported
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
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