redteam-report-template skill
Client-facing red-team deliverable format — codifies the Subject / Observations / Description / Impact / Recommendation / PoC structure used for external red-team engagements (not bug-bounty platform reports). Different audience, different tone, different cadence. Built from an authorized engagement deliverable where 14 findings were packaged into a 52KB MD + 2.2MB DOCX with 16 embedded screenshots. Use when the engagement is "external red team for an enterprise client" (not H1/Bugcrowd/Intigriti), when generating the final report, when the client has specified a custom report format, or when packaging findings into DOCX/PDF.
Is the redteam-report-template skill safe?
Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-09-28.
No findings.
Install the redteam-report-template skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/elementalsouls/Claude-BugHunter.git /tmp/Claude-BugHunter mkdir -p ~/.claude/skills cp -r /tmp/Claude-BugHunter/skills/redteam-report-template ~/.claude/skills/redteam-report-template
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
When to use
Use this skill for client-deliverable reports:
- External red-team engagements with a signed SOW
- Pentest reports going to a CISO / IT-Sec team (not a triager)
- Findings that will be reviewed by both technical and non-technical stakeholders
- Reports that need DOCX/PDF output (not just markdown / platform UI)
Do NOT use for:
- Bug-bounty platform submissions (use report-writing / bugcrowd-reporting instead)
- Quick proof-of-concept memos
- Internal team writeups
The 6-section format per finding
This is the canonical structure each finding follows:
## Finding F##: <descriptive title>
**Severity:** Critical / High / Medium / Low / Informational
**Status:** Confirmed / Patched mid-engagement / Suspected (1 signal)
**CVSS 3.1:** <score> (<vector>)
**Affected Asset:** <URL / IP / app name>
### 1. Subject
<One-line statement of the issue. Plain English, no jargon.>
### 2. Observations
<Bulleted list of what was observed during testing. Concrete facts only — no interpretation yet.>
- <Observation 1>
- <Observation 2>
- ...
### 3. Description
<Technical explanation of the vulnerability. 2-4 paragraphs. Reader should understand WHY the observations indicate a vulnerability, what the underlying flaw is.>
### 4. Impact
<What an attacker could achieve. Concrete attacker outcomes, NOT generic CIA triad statements. Tie to the client's business — money, data, reputation, regulatory exposure.>
### 5. Recommendation
<Specific, actionable remediation. Vendor patch, configuration change, code-level fix. Avoid "implement security best practices" — say what specifically.>
### 6. Proof of Concept (PoC)
<Steps to reproduce, numbered. Include the exact HTTP requests, payloads, tools used.>
**Step 1:** <action>**Step 2:** <action>**Screenshot:**
Severity & status disciplines
Severity table (client-facing — different from CVSS-only)
Status field (red-team-specific)
This is the field that distinguishes red-team deliverables from bug-bounty reports. Use one of:
- Confirmed — reproduced multiple times, with full PoC
- Confirmed; patched mid-engagement — was reproducible, client patched during the test window (still ship the finding — see mid-engagement-ir-detection)
- Confirmed; partially reproducible — works but needs specific conditions
- Suspected (1 signal) — single indicator, not confirmed (rare — usually drop)
- Out-of-band — finding from passive recon, not actively tested
Mistakes to avoid (from authorized-engagement)
1. Don't retract findings that stopped reproducing
If a finding was confirmed and then stopped working, that is almost always a CLIENT PATCH, not a finding-was-false. The correct response is "Confirmed; patched mid-engagement" with timestamps showing when it broke. See mid-engagement-ir-detection.
2. Don't hedge in the Impact section
Bad: "An attacker could potentially be able to access user data, which may lead to..." Good: "An attacker reads any user's profile data. Demonstrated on test user victim@target.com at 14:22 IST."
3. Don't generic-CIA the impact
Bad: "Loss of confidentiality and integrity of customer data" Good: "Read access to 247,000 customer records including PAN cards, addresses, GST numbers. India DPDPA Section 33 mandates 72-hour breach disclosure to DPB."
4. Don't list every recon finding as a finding
Recon notes (subdomains found, ports open, technologies fingerprinted) belong in a separate Recon / Attack Surface appendix, not the findings list. A finding must have an attacker-attainable outcome.
5. Don't bury the PoC
Each finding MUST have reproducible steps. The PoC section is what proves the finding to a skeptical reader. If you can't write the PoC clearly, the finding probably isn't ready to ship.
Document-level structure
1. Executive Summary (1 page, non-technical)
- Engagement overview (dates, scope)
- Risk posture summary (heat-map: <X critical, Y high, Z medium...>)
- Top 3 strategic recommendations
- Comparison to industry baseline (optional)
2. Engagement Details
- Scope (in-scope, out-of-scope, exclusions)
- Methodology (recon → exploit → reporting; or align with PTES / OSSTMM)
- Tools used
- Timeline (start / end / key milestones)
- Team
3. Risk Summary Table
| F# | Title | Severity | Status |
|----|-------|----------|--------|
| F01 | ... | Critical | Confirmed |
...
4. Findings (one per ## section, in severity order — Critical first)
5. Attack Surface / Recon Appendix
- Subdomains discovered
- Open ports / services
- Technology fingerprints
- APKs found
- Credentials in breach corpora (count + sample only — redact)
- Identity-fabric map (IdP, MFA posture)
6. Indicators of Compromise (IoCs)
- Source IPs used during testing (so SOC can correlate)
- User-Agent strings
- Test accounts created
- Files uploaded (with cleanup status)
7. Cleanup Statement
- Confirmation that all test artifacts (accounts, uploads, persistDOCX generation pipeline (markdown → docx with embedded images)
# Prerequisite: pandoc installed
brew install pandoc
# Convert
pandoc REPORT_FINAL.md \
-o REPORT_FINAL.docx \
--resource-path=engagement_log/poc \
--reference-doc=~/.claude/skills/redteam-report-template/templates/reference.docx \
--toc \
--toc-depth=2 \
--highlight-style=tango
# Verify image count
python3 -c "
from docx import Document
d = Document('REPORT_FINAL.docx')
imgs = [r for r in d.part.rels.values() if 'image' in r.target_ref]
print(f'Embedded images: {len(imgs)}')
print(f'Paragraphs: {len(d.paragraphs)}')
print(f'Headings: {sum(1 for p in d.paragraphs if p.style.name.startswith(\"Heading\"))}')
"Image filename convention
screenshots/F<NN>_<descriptive>.png
Examples:
F01_locked_accounts.png
F02a_saml_landing.png
F02b_saml_ca_block_page.png
F03_sqli_timing_chart.png
F15_saml_metadata.pngVariants get letter suffixes (F02a, F02b). Always zero-pad finding number.
Writing tone — for client deliverables
Always:
- Use past tense for observations ("The endpoint returned a 200 status code")
- Use present tense for descriptions of the flaw ("The application does not validate...")
- Use imperative for recommendations ("Apply patch ... by ...")
- Number reproduction steps; never "first... then... also..."
Never:
- "Could potentially" — prove it or drop it
- "It might be possible" — same
- "We recommend implementing security best practices" — say which one specifically
- "The application is vulnerable to..." without saying what specifically
Audience translation — same finding, different framing
Example: hardcoded JWT in APK
The same finding's Impact paragraph should cover both ends — start with the business outcome, then drop into technical detail.
Findings that are sometimes wrongly excluded
Red-team deliverables should include — not just bug-bounty payable bugs:
- Information disclosure that helps attack mapping (CodeIgniter debug toolbar leaking routes, version banners on appliances) — Medium
- User enumeration (Microsoft OneDrive 302 vs 404 differential) — Medium
- Pre-existing security state observations (247 accounts already locked by external attacker; weak password policies) — Informational with stakeholder relevance
- Defensive observations (SOC patched our SQLi within 30 min — evidence of working detection) — Informational/positive
- Sister-app pattern issues (same code template across 7 apps) — Medium (multiplied blast radius)
Bug bounty would reject most of these. Red-team deliverables embrace them — the client paid for the assessment to know.
Mid-engagement events to document
Beyond findings themselves, the deliverable should include:
- Detected SOC responses (timestamps when defenses kicked in)
- Concurrent external attacker activity (if any was observed)
- Findings the client patched during the engagement (with PoC pre-patch as evidence)
- Tooling failures (e.g., MCP timeout, CAPTCHA not solvable) — these affect what was/wasn't testable
Each gives the client context about their real-world detection capability, which often matters more than the findings themselves.
Template library (where to put canned text)
Maintain reusable boilerplate in:
~/.claude/skills/redteam-report-template/templates/
executive_summary.md # Reusable exec summary skeleton
methodology.md # Standard methodology section
cleanup_statement.md # Standard cleanup language
reference.docx # Pandoc style template (fonts, headings, colors)
cover.docx # Cover page templateDon't write these from scratch each engagement; clone and customize.
Quality checks before delivery
Pre-delivery checklist:
- [ ] Every finding has all 6 sections populated (no "TBD")
- [ ] Every finding has at least one screenshot or HTTP-level evidence
- [ ] Every PoC includes redactions for client PII (mask emails, phone numbers, IDs)
- [ ] Every screenshot is referenced in the MD with a relative path that resolves
- [ ] DOCX render check — image count matches MD reference count
- [ ] Severity ordering: Critical findings first, then High, etc.
- [ ] Executive summary is updated to match final findings (count, themes)
- [ ] Cleanup statement explicitly says what was created and what was removed
- [ ] IoC section enables the SOC to reconstruct what they saw
- [ ] Spell-check (especially client company name, product names)
- [ ] All tool versions noted in methodology
- [ ] Status field set correctly on every finding (especially patched-mid-engagement)
Bridge to neighboring skills
- report-writing — bug-bounty platform reports (different format, different audience)
- redteam-mindset — informs what counts as a finding worth shipping
- mid-engagement-ir-detection — informs the "patched mid-engagement" status pattern
- evidence-hygiene — informs screenshot redaction discipline
- m365-entra-attack, enterprise-vpn-attack, etc. — each provides finding-templates specific to its attack surface
Anti-patterns
- DO NOT write a 50-page report for 3 findings — pad-by-page erodes credibility
- DO NOT use the same severity for everything — calibrate
- DO NOT copy-paste OWASP top-10 boilerplate into Description sections
- DO NOT include findings without PoCs — they read as speculative
- DO NOT skip the Recommendation section's specificity — "patch and review" doesn't help
- DO NOT mix bug-bounty CVSS scoring with red-team severity unthinkingly — context differs (e.g., a Medium on a CVSS basis can be Critical for the client if it touches a regulated dataset)
More skills from elementalsouls/Claude-BugHunter
- Aapk-redteam-pipelineEnd-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.
- Fbb-local-toolkitLocal-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
- Abb-methodologyUse 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."
- Fbug-bountyComplete 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
- Abugcrowd-reportingBugcrowd-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.
- Acloud-iam-deepCloud 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.
- Centerprise-vpn-attackExternal SSL VPN / remote-access appliance attack matrix — Cisco ASA/AnyConnect, Fortinet FortiGate/FortiOS, Citrix NetScaler/ADC, Palo Alto GlobalProtect, Pulse Secure / Ivanti Connect Secure, SonicWall, F5 Big-IP. Covers version fingerprinting, CVE matrix (2018-2026), AAA backend identification, default credentials, configuration-disclosure paths, pre-auth RCE/SSRF/path-traversal exploits where applicable. Built from authorized-engagement Cisco ASA testing plus 2024-2026 enterprise VPN CVE landscape. Use whenever the target's perimeter exposes any SSL VPN appliance or remote-access gateway — these are the most common initial-access points in 2024-2026 actor TTPs.
- Aevidence-hygieneEvidence-capture and PoC-redaction discipline for bug-bounty submissions: cookie redaction protocol (which fields to mask, Preview annotation / Burp panel hiding / DevTools workflow), PII black-bar discipline (what to mask in other-user data — names, emails, phones, faces — vs what is safe to leave — usernames, trace IDs, request bodies), HAR file sanitization (jq filters for Cookie/Set-Cookie/Authorization headers), Burp Repeater/Intruder screenshot hygiene (hide request body, show only Results table for rate-limit attacks), Chrome DevTools Console PoC patterns (credentials include so cookies are not echoed, labeled console.log), screenshot capture order, filename conventions, post-submission rotation hygiene. Use BEFORE any PoC screenshot, BEFORE attaching a HAR, or whenever preparing evidence with session cookies or other-user PII. Pairs with bugcrowd-reporting and report-writing.
- Ahunt-api-misconfigHunt API security misconfiguration — mass assignment, prototype pollution, HTTP verb tampering. Mass assignment: send {is_admin:true, role:admin, verified:true} on profile/account/reset endpoints — server blindly applies. JWT signature/crypto forging (alg:none, key confusion, kid/jku) is owned by hunt-jwt-crypto; this skill covers only non-crypto JWT handling. Prototype pollution: __proto__ injection in JSON merge / Object.assign / lodash _.merge → polluted prototype reaches sink (RCE in Node, XSS in browser). HTTP verb: GET-bypass-CSRF, X-HTTP-Method-Override, TRACE enabled. Detection: API responses with extra fields, JWTs in headers (decode at jwt.io). CORS misconfiguration (reflect-any-origin, null origin, subdomain-regex bypass, postMessage) is owned by hunt-cors. Use when hunting API misconfigs, mass-assignment, prototype pollution (JWT crypto → hunt-jwt-crypto).
- Ahunt-aspnetHunt ASP.NET-specific surface — ViewState deserialization (signed-only vs encrypted), machineKey recovery, dual-parser MAC-bypass anti-pattern, request-validator bypass, trace.axd/elmah.axd disclosure, load-balanced ViewState cross-node failures, SafeControl enumeration via reflection, customErrors mode=Off stack-trace leaks, classic Webforms .aspx/.asmx/.svc surface. Built for ASP.NET Webforms + WCF + SharePoint farms.
- Ahunt-atoHunt account takeover taxonomy — 9 distinct paths to ATO, plus chains. Paths: (1) password reset flaws (host-header injection redirects token, predictable/numeric token, Referer leak, no-expiry/reuse), (2) email change without re-auth, (3) OAuth account-link CSRF, (4) MFA bypass (per hunt-mfa-bypass), (5) session fixation, (6) JWT manipulation (forge token to another identity; crypto details → hunt-jwt-crypto), (7) password change without step-up (chain with login timing/length oracle), (8) social-recovery / security-question brute-force, (9) SSO subdomain takeover at OAuth redirect_uri. Chains: cookie theft + password oracle + no step-up = persistent ATO; lax redirect_uri = auth-code theft; dangling-CNAME takeover at redirect_uri = ATO. Validate: demonstrate real takeover of test account B from attacker A's session; OOB/Collaborator confirm blind token-leak steps. Use when hunting ATO chains, testing password reset / email change / MFA / OAuth / session / JWT, or chaining primitives toward Critical.
- Ahunt-auth-bypassHunting skill for auth bypass vulnerabilities. Built from 12 public bug bounty reports across SAML XSW / parser-differential (GitHub Enterprise CVE-2025-25291/25292), SAML signature stripping (Uber, Rocket.Chat, samlify CVE-2025-47949), SAML domain enforcement bypass via control characters (HackerOne 2024), partner-portal cross-IdP assertion reuse (Slack), WordPress XMLRPC bypassing SSO (Uber), JWT alg-confusion HS256/RS256 (Jitsi), JWT signature-validation skip (Linktree, Newspack), and token-audience confusion (Argo CD CVE-2023-22482). For standalone JWT signature/crypto forging (alg:none, key confusion, kid/jku) see hunt-jwt-crypto; this skill covers JWT only inside SSO/SAML/token-trust bypass chains. SAML assertion-layer attacks (XSW, comment injection, signature stripping, XXE-in-assertion) are owned by hunt-saml; this skill owns the broader cross-protocol auth-bypass taxonomy. Use when hunting auth bypass — see the Legacy-Protocol Matrix for branded-UI vs legacy-endpoint patterns.