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security-analyzer — Categories.community

v1.0.0
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About this Skill

Ideal for Cybersecurity Agents requiring advanced vulnerability assessment and remediation planning capabilities using Python and CVE data Security analyzer skill for Claude Code

Cornjebus Cornjebus
[0]
[0]
Updated: 3/5/2026

Quality Score

Top 5%
37
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add Cornjebus/security-analyzer

Agent Capability Analysis

The security-analyzer MCP Server by Cornjebus is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion.

Ideal Agent Persona

Ideal for Cybersecurity Agents requiring advanced vulnerability assessment and remediation planning capabilities using Python and CVE data

Core Value

Empowers agents to analyze environments for vulnerabilities, fetch current CVE and exploit data, and generate phased remediation plans with TDD validation using scripts like discover_env.py and fetch_vulns.py, outputting to JSON files like inventory.json and scan_results.json

Capabilities Granted for security-analyzer MCP Server

Automating environment discovery for vulnerability assessment
Generating remediation plans based on current CVE data
Validating security scan results with TDD

! Prerequisites & Limits

  • Requires Python environment
  • Needs filesystem access for script execution and output
  • Dependent on external CVE and exploit data sources
Project
SKILL.md
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package.json
240 B
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Security Analyzer

Analyze environments for vulnerabilities, fetch current CVE/exploit data, and generate phased remediation plans with TDD validation.

Quick Start

When the user requests a security scan:

  1. Run environment discovery: python .claude/skills/security-analyzer/scripts/discover_env.py .
  2. Save output to inventory.json
  3. Run vulnerability scan: python .claude/skills/security-analyzer/scripts/fetch_vulns.py inventory.json
  4. Save output to scan_results.json
  5. Generate reports: python .claude/skills/security-analyzer/scripts/generate_report.py scan_results.json inventory.json

Workflow

Phase 1: Environment Discovery

Scan working directory for:

  • Dependencies: package.json, requirements.txt, Gemfile, go.mod, Cargo.toml, pom.xml
  • Containers: Dockerfile, docker-compose.yml, kubernetes/*.yaml
  • Cloud IaC: terraform/*.tf, cloudformation/*.yaml, *.bicep
  • Secrets: .env* files (flag exposure risk, never log values)

Run the discovery script:

bash
1python .claude/skills/security-analyzer/scripts/discover_env.py /path/to/project > inventory.json

Phase 2: Vulnerability Intelligence

Fetch current threat data using the vulnerability scanner:

bash
1python .claude/skills/security-analyzer/scripts/fetch_vulns.py inventory.json > scan_results.json
SourcePriorityUse For
CISA KEV1Actively exploited vulns (use WebSearch)
NVD2CVE details + CVSS scores (use WebSearch)
GitHub Advisories3Package-specific vulns (use WebSearch)
OSV.dev4Open source vulns (API in script)

For CISA KEV and additional context, supplement with:

WebSearch: "CVE-XXXX-YYYY CISA KEV exploit"

Phase 3: Risk Scoring

The scanner calculates risk scores using:

Risk = (CVSS * 0.3) + (Exploitability * 0.3) + (Criticality * 0.2) + (Exposure * 0.2)

Exploitability: 10=CISA KEV, 7=public exploit, 3=theoretical
Criticality: 10=auth/payment, 5=core business, 2=logging
Exposure: 10=internet-facing, 5=internal, 2=air-gapped

Phase 4: Phased Remediation

Generate reports with fix commands and validation tests:

bash
1python .claude/skills/security-analyzer/scripts/generate_report.py scan_results.json inventory.json

Each finding includes:

  1. Vulnerability details + risk score
  2. Actual fix code/patch (not just recommendations)
  3. Pre-fix test (proves vuln exists)
  4. Remediation unit tests (tests the fix code)
  5. Post-fix validation (proves vuln resolved)

Phase 5: Reports

Output two reports:

  • security-report-technical.md — Full details for engineers
  • security-report-executive.md — Summary for leadership

See references/report-templates.md for output structure.

TDD Pattern

For each vulnerability, generate three test types:

python
1def test_vuln_exists(): 2 """PASS before fix, FAIL after""" 3 assert is_vulnerable("component") == True 4 5def test_fix_works(): 6 """Unit test for remediation code""" 7 result = apply_fix(vulnerable_config) 8 assert result.is_secure() 9 10def test_vuln_resolved(): 11 """FAIL before fix, PASS after""" 12 assert is_vulnerable("component") == False

Fix Types by Finding

FindingOutput
Dependency CVEVersion bump command + lockfile update
Container issueDockerfile patch
IaC misconfigurationTerraform/K8s fix
Code vulnerabilitySource patch + test
Secret exposureRotation commands + .gitignore update

Example Interaction

User: "Run a security scan on this project"

Claude:

  1. Discovers 47 npm dependencies, 3 Dockerfiles, 2 Terraform configs
  2. Fetches current CVE data from OSV.dev
  3. Identifies 12 vulnerabilities (2 critical, 4 high, 6 medium)
  4. Generates phased remediation plan with:
    • Actual fix commands (npm install lodash@4.17.21)
    • Code patches for IaC misconfigurations
    • TDD tests proving each fix works
  5. Outputs technical and executive reports

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