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security-scan

Scan your Claude Code configuration (.claude/ directory) for security vulnerabilities, misconfigurations, and injection risks using AgentShield. Checks CLAUDE.md, settings.json, MCP servers, hooks, and agent definitions. Use when auditing a .claude/ directory — CLAUDE.md, settings.json, MCP servers, hooks, or agent definitions.

O que é security-scan?

security-scan is a Claude Code agent skill that scan your Claude Code configuration (.claude/ directory) for security vulnerabilities, misconfigurations, and injection risks using AgentShield. Checks CLAUDE.md, settings.json, MCP servers, hooks, and agent definitions. Use when auditing a .claude/ directory — CLAUDE.md, settings.json, MCP servers, hooks, or agent definitions.

Funciona comClaude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/security-scan

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Documentação

Security Scan Skill

Audit your Claude Code configuration for security issues using AgentShield.

When to Activate

  • Setting up a new Claude Code project
  • After modifying .claude/settings.json, CLAUDE.md, or MCP configs
  • Before committing configuration changes
  • When onboarding to a new repository with existing Claude Code configs
  • Periodic security hygiene checks

What It Scans

FileChecks
CLAUDE.mdHardcoded secrets, auto-run instructions, prompt injection patterns
settings.jsonOverly permissive allow lists, missing deny lists, dangerous bypass flags
mcp.jsonRisky MCP servers, hardcoded env secrets, npx supply chain risks
hooks/Command injection via interpolation, data exfiltration, silent error suppression
agents/*.mdUnrestricted tool access, prompt injection surface, missing model specs

Prerequisites

AgentShield must be installed. Check and install if needed:

# Check if installed
npx ecc-agentshield --version

# Install globally (recommended)
npm install -g ecc-agentshield

# Or run directly via npx (no install needed)
npx ecc-agentshield scan .

Usage

Basic Scan

Run against the current project's .claude/ directory:

# Scan current project
npx ecc-agentshield scan

# Scan a specific path
npx ecc-agentshield scan --path /path/to/.claude

# Scan with minimum severity filter
npx ecc-agentshield scan --min-severity medium

Output Formats

# Terminal output (default) — colored report with grade
npx ecc-agentshield scan

# JSON — for CI/CD integration
npx ecc-agentshield scan --format json

# Markdown — for documentation
npx ecc-agentshield scan --format markdown

# HTML — self-contained dark-theme report
npx ecc-agentshield scan --format html > security-report.html

Auto-Fix

Apply safe fixes automatically (only fixes marked as auto-fixable):

npx ecc-agentshield scan --fix

This will:

  • Replace hardcoded secrets with environment variable references
  • Tighten wildcard permissions to scoped alternatives
  • Never modify manual-only suggestions

Opus 4.6 Deep Analysis

Run the adversarial three-agent pipeline for deeper analysis:

# Requires ANTHROPIC_API_KEY
export ANTHROPIC_API_KEY=your-key
npx ecc-agentshield scan --opus --stream

This runs:

  1. Attacker (Red Team) — finds attack vectors
  2. Defender (Blue Team) — recommends hardening
  3. Auditor (Final Verdict) — synthesizes both perspectives

Initialize Secure Config

Scaffold a new secure .claude/ configuration from scratch:

npx ecc-agentshield init

Creates:

  • settings.json with scoped permissions and deny list
  • CLAUDE.md with security best practices
  • mcp.json placeholder

GitHub Action

Add to your CI pipeline:

- uses: affaan-m/agentshield@v1
  with:
    path: '.'
    min-severity: 'medium'
    fail-on-findings: true

Severity Levels

GradeScoreMeaning
A90-100Secure configuration
B75-89Minor issues
C60-74Needs attention
D40-59Significant risks
F0-39Critical vulnerabilities

Interpreting Results

Critical Findings (fix immediately)

  • Hardcoded API keys or tokens in config files
  • Bash(*) in the allow list (unrestricted shell access)
  • Command injection in hooks via ${file} interpolation
  • Shell-running MCP servers

High Findings (fix before production)

  • Auto-run instructions in CLAUDE.md (prompt injection vector)
  • Missing deny lists in permissions
  • Agents with unnecessary Bash access

Medium Findings (recommended)

  • Silent error suppression in hooks (2>/dev/null, || true)
  • Missing PreToolUse security hooks
  • npx -y auto-install in MCP server configs

Info Findings (awareness)

  • Missing descriptions on MCP servers
  • Prohibitive instructions correctly flagged as good practice

Links

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

api-connector-builder

Build a new API connector or provider by matching the target repo

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