Offensive Reporting
This AI agent automates the creation of professional penetration test reports by structuring findings from captured evidence, drafting each finding as a numbered file, generating an executive summary after scoring, and performing a two-pass review for technical accuracy and CISO-level narrative. It outputs a retest plan and a JSON/CSV index for client tracking systems.
How to Install
git clone --depth 1 https://github.com/SnailSploit/Claude-Red.git && cp Claude-Red/Skills/utility/offensive-reporting ~/.claude/skills/SKILL.md -rPenetration Test Reporting — Professional Methodology
A great finding lost in a bad report is a wasted finding. Reports are the artifact the client pays for, the auditor reads, and the developer fixes from. Treat the report with the same rigor as the exploit.
Quick Workflow
- Capture evidence as you exploit — never reconstruct after the fact
- Draft each finding immediately while context is fresh; one finding = one numbered file
- Build the executive summary last, after all findings are scored
- Two-pass review: technical accuracy first, then read-as-CISO for narrative
- Hand off with a retest plan and a JSON/CSV index for the client's tracking system
Report Structure (Standard)
1. Executive Summary ← Last to write, first read
2. Engagement Overview
2.1 Scope
2.2 Methodology
2.3 Limitations / Assumptions
2.4 Timeline
2.5 Team
3. Risk Summary ← Heatmap, finding count by severity
4. Technical Findings ← One per finding, sorted by severity
5. Attack Narratives / Chains ← Critical chains called out separately
6. Strategic Recommendations ← Programmatic, not finding-by-finding
7. Appendices
A. Tools Used
B. Indicators of Compromise (for blue team)
C. Raw Evidence Pointers
D. Glossary
Executive Summary — The 90-Second Read
The executive summary is for the CISO, the GRC officer, and the board member. They read this and nothing else.
Structure (one page max):
- Engagement context — what was tested, when, by whom (1 sentence)
- Headline finding — the worst thing you found, in business terms (2–3 sentences)
- Risk verdict — overall posture in plain language (1 paragraph)
- Counts — number of findings by severity, in a small table
- Top 3 strategic recommendations — programmatic fixes, not "patch CVE-X"
Words to avoid in the executive summary:
payload, RCE, XSS, LDAP, SMB, kerberos, injection. Translate every one. ("An attacker could run arbitrary commands on the server" not "RCE via deserialization gadget chain.")
Words to include:
Business impact (customer data, regulatory exposure, operational disruption, financial loss). Anchor every finding to a business consequence.
Technical Finding Template
## Finding ID — Short Descriptive Title
**Severity:** Critical (CVSS 9.8 — vector below)
**Affected Scope:** <hosts/URLs/components, with version where relevant>
**Status:** Open / Fixed in retest / Accepted Risk
**CWE:** CWE-89 (SQL Injection)
**OWASP:** A03:2021 — Injection
### Summary
One paragraph. What is the finding, why does it matter, what's the worst case.
### Background
What technology is involved and why this class of bug exists. Two paragraphs max.
Skip if obvious (e.g. don't explain XSS to an XSS shop).
### Description
Detailed walkthrough of the issue. The root cause, not just the symptom.
### Reproduction Steps
1. Numbered, copy-paste ready.
2. Include the exact request/response, redacted.
3. A reader with no engagement context should reproduce in <15 minutes.
### Evidence
- `screenshots/finding-007/01-payload.png`
- `requests/finding-007/initial-poc.http`
- `evidence-log.csv` line 142 (timestamp 2025-04-12 14:33:07Z)
### Impact
Concrete. Quantified where possible.
- "Read access to the entire customer table (~2.3M records)"
- "Authenticate as any user; verified for sample ID 1, 2, 999, 1000000"
- "Cross-tenant access — verified by reading data from acquired-tenant ABC"
### Remediation
Specific, actionable, ordered by precedence:
1. **Fix the bug** — exact code change or config flag
2. **Defense in depth** — secondary control (WAF rule, input validation)
3. **Detection** — log line / SIEM rule that would have caught the exploit
### References
- CWE / OWASP / CAPEC
- Vendor advisory if known CVE
- Blog posts only if directly relevant
### Notes for Retest
What you'd do to verify the fix. Specific request, specific expected response.
Severity Scoring
CVSS v3.1 Discipline
CVSS is a tool, not a verdict. Score it, then sanity-check against business impact.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H = 9.8 Critical
For every metric, justify the choice in one sentence:
- AV:N — exposed to internet (port 443)
- AC:L — no special preconditions
- PR:N — no authentication needed
- UI:N — no user interaction
- S:U — does not cross security scope
- C:H I:H A:H — full read/write/availability impact on the database
If two reasonable people would score it differently, document why you chose what you chose.
When CVSS Lies
CVSS doesn't capture business context. A "Medium" CVSS XSS in the customer support chat panel that authenticated agents use to handle PII is more dangerous than an unauthenticated "High" SSRF on a metadata-less internal service. Use CVSS as the floor, not the ceiling.
In those cases, score CVSS honestly and then **add a "Business Impact Adjustment"
Details
| Category | AI/ML → ml |
| Source | SnailSploit/Claude-Red |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 2.4K |
| Est. per Skill | N/A (shared across 50 skills from this repo) |
| Difficulty | Advanced |
| Risk Level | N/A |
Related Skills
Works Well With
Skills from the same repository — often designed to work together