Report

NullPointer Studio Pentest Report Generator

Purpose

Read findings.json from the current pentest session and generate a complete, client-ready penetration test report as a styled PDF. The report follows the NullPointer Studio dark theme with healthcare-aware business risk language per finding.

Load refs/style.md for the full CSS specification and color palette before writing any HTML.

Tools Available

Workflow

Step 0 — Collect inputs

1. Determine the findings.json path:

   • If $ARGUMENTS provides a path, use it
   • Otherwise use ./findings.json (repo root)

2. Read findings.json — extract all entries where type == "finding" (skip diagram and note entries). For each finding, capture:

   • id, title, severity, target, description, evidence, tool_used
   • reproduction (command + steps) if present
   • remediation (diff / before / after / verification) if present
   • cve if present

3. Read session.json if it exists — extract:

   • target (base URL)
   • depth
   • start_time (format as date for report)
   • skill (used as engagement type)

4. Scan pocs/ for .http files — map each file to its finding by matching filename keywords against finding titles.

5. Call report(action="note", ...) with: finding count by severity, target, output path.

Step 1 — Deduplicate and classify findings

Group findings by severity. Within each group, deduplicate on normalized title (same title = same finding, keep the one with more evidence). Sort order for report:

CRITICAL → HIGH → MEDIUM → LOW → INFO

Compute stat box counts:

• Count findings in each severity bucket
• Total = sum of all

Step 2 — Write the generator script

Write a Python script report_generator.py to the repo root. The script must:

1. Import json, base64, html, pathlib.Path, datetime, weasyprint

2. Embed the NullPointer Studio CSS from refs/style.md verbatim as CSS_STR

3. Load the logo:

   LOGO_PATH = Path("/Users/riccardo.tencate/Desktop/agent-smith/templates/FullLogo_Transparent.png")
   with open(LOGO_PATH, "rb") as f:
       LOGO_SRC = "data:image/png;base64," + base64.b64encode(f.read()).decode()
   

4. Define SEV_META dict:

   SEV_META = {
       "critical": {"label": "CRITICAL", "color": "#ff4d6d", "bg": "rgba(255,77,109,0.12)", "border": "#ff4d6d"},
       "high":     {"label": "HIGH",     "color": "#ff8c42", "bg": "rgba(255,140,66,0.12)",  "border": "#ff8c42"},
       "medium":   {"label": "MEDIUM",   "color": "#ffd166", "bg": "rgba(255,209,102,0.1)",  "border": "#ffd166"},
       "low":      {"label": "LOW",      "color": "#5bf29b", "bg": "rgba(91,242,155,0.08)",  "border": "#5bf29b"},
       "info":     {"label": "INFO",     "color": "#7b78ff", "bg": "rgba(123,120,255,0.08)", "border": "#7b78ff"},
   }
   

5. Define helper functions:

   def esc(s): return html.escape(str(s))
   def badge(sev): ...   # colored inline badge span
   def code(text): ...   # <pre class="code-block"><code>...</code></pre>
   

6. Define finding_section(np_id, severity, title, owasp, asvs, endpoint, auth, confirmed, description, business_risk, evidence, steps, remediation) — see refs/style.md for the exact HTML structure.

7. Build the full HTML document (cover page → stat boxes → exec summary → scope → risk dashboard → findings → remediation table → clean controls) and write it via weasyprint.

Script skeleton:

#!/usr/bin/env python3
import json, base64, html as html_mod, datetime
from pathlib import Path
from weasyprint import HTML as WeasyprintHTML

BASE_DIR = Path(".")
OUTPUT   = BASE_DIR / "report_{target_slug}_{date}.pdf"

# ... helpers, CSS, content sections ...

if __name__ == "__main__":
    html_content = build_html()
    Path("report.html").write_text(html_content, encoding="utf-8")
    WeasyprintHTML(string=html_content, base_url=str(BASE_DIR)).write_pdf(str(OUTPUT))
    print(f"PDF → {OUTPUT}")

Step 3 — Populate report sections

Cover page

[Logo — 180px height]
CONFIDENTIAL  (red monospace badge)
Penetration Test Report  (28pt Chakra Petch bold)
{target domain}  (14pt green Chakra Petch)
───────────────────────────────
Client      | {client name}
Target      | {base URL}
Test type   | Web App Pentest + White-Box Code Review
Framework   | {detected framework if known}
Test date   | {date}
Report date | {today}
Prepared by | NullPointer Studio
Version     | 1.0

Stat boxes (one per severity)

Show counts for CRITICAL, HIGH, MEDIUM, LOW, INFO, and Total. Color each number with the severity accent color. Only include severity boxes that have at least 1 finding — always show Total.

Executive Summary

Write a 3–4 paragraph summary covering:

1. What was tested, what methodology, what environment
2. The most critical finding(s) — name them by NP-ID and title, explain the real impact in one sentence each
3. Medium/Low/Info summary in aggregate (count + theme)
4. What was found to be solid (clean controls) — 1–2 sentences

Do NOT use generic templates — derive every sentence from the actual findings in findings.json. Healthcare impact language where relevant.

Risk Dashboard table

Columns: ID | Severity | Title | OWASP | Status

Show all findings in severity order. Use badge(sev) for the severity cell. Status = "Confirmed" for all non-info findings, "Informational" for info.

Finding cards

For each finding, render a card using finding_section(...). Map findings.json fields as follows:

OWASP category mapping (use if not explicit in finding):

Remediation Summary table

Columns: ID | Severity | Title | Priority | Effort | Fix (one-line)

Assign priority based on severity:

• CRITICAL → P0 — Immediate
• HIGH → P0 — Immediate
• MEDIUM → P2 — Next sprint (or P1 — This sprint for the most impactful)
• LOW → P3 — Milestone or P4 — Backlog
• INFO → — (no priority)

Effort: Low (config change, 1-liner fix), Medium (refactor needed), High (architecture change).

Clean controls

If session.json or the findings list contains explicit "tested clean" notes, include a "Controls Tested — No Issues Found" table. If no clean controls are documented, omit this section.

Step 4 — Generate the PDF

python3 report_generator.py

If weasyprint is not installed: pip install weasyprint first.

After generation, print:

Report generated:
  PDF  → ./report_{target}_{date}.pdf
  HTML → ./report_{target}_{date}.html
  Findings: {N} total ({crit} critical, {high} high, {med} medium, {low} low, {info} info)

Rules

• Never invent findings — only include what is in findings.json
• Business risk is mandatory for every finding — derive from the actual finding; never write "could potentially" — write what an attacker concretely achieves
• NP-IDs must be sequential in severity order (NP-001 = most severe)
• INFO findings get a simplified card: Description + Business Risk + Recommendations only (no Evidence/Steps headers unless evidence is meaningful)
• Logo path is always /Users/riccardo.tencate/Desktop/agent-smith/templates/FullLogo_Transparent.png
• Output filename: report_{target_slug}_{YYYY-MM-DD}.pdf where target_slug = domain with dots replaced by underscores
• weasyprint is the only supported PDF engine — do not use pdfkit, xhtml2pdf, or headless Chrome
• Load refs/style.md before writing any HTML or CSS — never invent new colors or fonts