report-writing
The report-writing Claude Code skill provides structured templates and validation rules for writing high-quality bug bounty reports on platforms like HackerOne, Bugcrowd, and Intigriti. Use this skill after confirming a vulnerability exists and before submitting to enforce impact-first writing, eliminate speculative language ("could potentially"), follow title and impact statement formulas, apply CVSS 3.1 scoring, and complete pre-submit verification. The skill includes concrete examples of good versus bad report sections and decision guides for severity classification.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter /tmp/report-writing && cp -r /tmp/report-writing/skills/report-writing ~/.claude/skills/report-writingSKILL.md
# REPORT WRITING
Impact-first. Human tone. No theoretical language. Triagers are people.
---
## THE MOST IMPORTANT RULE
> **Never use "could potentially" or "could be used to" or "may allow".**
> Either it does the thing or it doesn't. If you haven't proved it, don't claim it.
```
BAD: "This vulnerability could potentially allow an attacker to access user data."
GOOD: "An attacker can access any user's order history by changing the user_id
parameter to the target user's ID. I confirmed this using two test accounts:
attacker@test.com (ID 123) successfully retrieved victim@test.com (ID 456)
orders, including their shipping address and payment method last 4 digits."
```
---
## TITLE FORMULA
```
[Bug Class] in [Exact Endpoint/Feature] allows [attacker role] to [impact] [victim scope]
```
**Good titles (specific, impact-first):**
```
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 (vague, useless to triager):**
```
IDOR vulnerability found
Broken access control
XSS in user input
Security issue in API
Unauthorized access to user data
```
---
## HACKERONE REPORT TEMPLATE
```markdown
## Summary
[One paragraph: what the bug is, where it is, what an attacker can do. Be specific.
Include: endpoint, method, parameter, data exposed, required access level.]
Example: "The `/api/users/{user_id}/orders` endpoint does not verify that the
authenticated user owns the requested user_id. An attacker can enumerate any
user's order history, including PII (email, address, phone) and purchase history,
by incrementing the user_id parameter. No privileges beyond a standard free
account are required."
## Vulnerability Details
**Vulnerability Type:** IDOR / Broken Object Level Authorization
**CVSS 3.1 Score:** 6.5 (Medium) — AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
**Affected Endpoint:** GET /api/users/{user_id}/orders
## Steps to Reproduce
**Environment:**
- Attacker account: attacker@test.com, user_id = 123
- Victim account: victim@test.com, user_id = 456
- Target: https://target.com
**Steps:**
1. Log in as attacker@test.com, obtain Bearer token
2. Send the following request:
```
GET /api/users/456/orders HTTP/1.1
Host: target.com
Authorization: Bearer ATTACKER_TOKEN_HERE
```
3. Observe response:
```json
{
"orders": [
{"id": 789, "items": [...], "email": "victim@test.com", "address": "123 Main St..."}
]
}
```
The response contains victim's full order history and PII despite being requested
by a different user.
## Impact
An authenticated attacker can enumerate all user orders by iterating user_id values.
This exposes: full name, email, shipping address, purchase history, and payment
method (last 4). With ~100K users, this represents a mass PII breach affecting
all registered users. Exploitation requires only a free account and takes minutes
with a simple loop.
## Recommended Fix
Add server-side ownership verification:
```python
if order.user_id != current_user.id:
raise Forbidden()
```
## Supporting Materials
[Screenshot showing attacker's session returning victim's order data]
[Video walkthrough if available]
```
---
## BUGCROWD REPORT TEMPLATE
```markdown
# [IDOR] User order history accessible without authorization via /api/users/{id}/orders
**VRT Category:** Broken Access Control > IDOR > P2
## Description
[Same impact-first paragraph as HackerOne summary]
## Steps to Reproduce
[Same structured steps — exact HTTP requests, exact responses]
## Proof of Concept
[Screenshot/video showing the actual impact]
## Expected vs Actual Behavior
**Expected:** 403 Forbidden when user_id does not match authenticated user
**Actual:** 200 OK with victim's full order data
## Severity Justification
P2 (High) — Direct read access to other users' PII. Affects all user accounts.
No user interaction required. Exploitable by any authenticated user.
Automated enumeration could exfil all [N] user records in minutes.
## Remediation
Add ownership verification: `if order.user_id != current_user.id: raise 403`
```
---
## INTIGRITI REPORT TEMPLATE
```markdown
# [Bug Class]: [Exact Impact] in [Endpoint/Feature]
## Description
[Impact-first paragraph. Start with what an attacker can do, not with how you found it.
Include: endpoint, method, parameter, data exposed, required privileges.]
## Steps to Reproduce
**Environment:**
- Attacker: email=attacker@test.com (standard account, no special role)
- Victim: email=victim@test.com
- Tested: [date]
**Reproduction steps:**
1. [Login as attacker / visit URL / send request]
2. Send the following HTTP request:
\```http
METHOD /endpoint HTTP/1.1
Host: target.com
Authorization: Bearer ATTACKER_TOKEN
Content-Type: application/json
{"param": "victim_id_here"}
\```
3. Observe response contains victim's private data:
\```json
{"email": "victim@test.com", "address": "123 Main St", ...}
\```
## Impact
[Specific, quantified impact. What data, how many users, what can attacker do.]
CVSS 3.1 Score: X.X ([Severity]) — AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
## Remediation
[1-3 sentence concrete fix. Include code if helpful.]
## Attachments
[Screenshot or Loom video showing the impact — Intigriti triagers prefer video for complex bugs]
```
**Intigriti-specific notes:**
- Title format: `[Bug Class]: [One-line impact]` (no formula required, but keep it specific)
- Severity is set by you: Critical/High/Medium/Low/Exceptional
- CVSS 3.1 is standard (CVSS 4.0 also accepted on newer programs)
- PoC video is valued much more than screenshot alone — record with Loom
- Safe harbor: Intigriti enforces it, be comfortable going slightly aggressive witEnd-to-end Android APK red-team pipeline — automated APK acquisition (Play Store + apkpure + apkmirror fallback), jadx decompilation, secret/URL/JWT/Firebase grep, pinned-cert extraction, exported-component enumeration, Frida runtime instrumentation templates, intent-injection probes. Built from an authorized external red-team engagement where 7 APKs were pulled manually, 4 download attempts truncated, and a hardcoded JWT + 30 internal API endpoints were recovered from one of the apps. Use when target has a mobile app catalogue (Play Store developer page), when you find an APK URL hosted on a web server, or when post-recon mentions "mobile app" in scope.
Run autonomous hunt loop on a target — scope check → recon → rank surface → hunt → validate → report with configurable checkpoints. Usage: /autopilot target.com [--paranoid|--normal|--yolo]
Local-tooling companion to the bug-bounty orchestrator — carries the SAME complete bug-bounty workflow, but reach for THIS variant when you also need to resolve where tools, wordlists, and clones are installed on the local machine (jhaddix, SecLists, trufflehog, ffuf, dalfox, ghauri); for pure orchestration/routing use the bug-bounty skill. Workflow it covers — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use when you need the local install path of a tool / wordlist / clone for a hunt, or as the full-workflow variant when operating from this local toolkit; for general routing use the bug-bounty skill. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Use at the START of any bug bounty hunting session, when switching targets, or when feeling lost about what to do next. Master orchestrator that combines the 5-phase non-linear hunting workflow with the critical thinking framework (developer psychology, anomaly detection, What-If experiments). Routes to all other skills based on current hunting phase. Also use when asking "what should I do next" or "where am I in the process.
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Bugcrowd-specific reporting tactics complementing report-writing: VRT category search-and-fallback strategy when no exact match exists, manual severity override when VRT defaults underrate impact, severity-request paragraph as first body section, OOS-clause rebuttal templates (rate limiting on auth-flow endpoints, debug-info framing, user-enumeration with sensitive PII, theoretical-issue counter), chained-finding cross-reference patterns, target selection for QA-vs-prod programs, researcher-side hygiene (Bugcrowdninja email alias, account state restoration, friendly-tester posture). Use when filing a Bugcrowd submission, when VRT default seems wrong, when triager closes as OOS or downgrades severity, when chaining linked submissions, or when scope distinguishes production from QA. Pairs with report-writing and triage-validation.
Build an exploit chain — given bug A, finds B and C to combine for higher severity and payout. Knows common chain patterns: IDOR→ATO, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth. Usage: /chain
Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.