Agent Skills [Beta]

A collection of skills for AI coding agents. Skills are packaged instructions and scripts that extend agent capabilities. This should be considered beta-level software; it's primarily generated by transforming open-source Semgrep rules into skill format.

Skills follow the Agent Skills format.

Installation

npx skills add semgrep/skills

Available Skills

code-security

Comprehensive code security guidelines from Semgrep Engineering covering OWASP Top 10, infrastructure security, and secure coding best practices across 15+ languages.

Use when:

• Writing new code
• Reviewing code for security vulnerabilities
• Asking about secure coding practices
• Configuring cloud infrastructure (Terraform, Kubernetes, Docker)

Categories covered:

Impact	Category	Description
Critical	SQL Injection	Parameterized queries, ORM safety
Critical	Command Injection	Shell command safety, input validation
Critical	Cross-Site Scripting (XSS)	Output encoding, DOM safety
Critical	XML External Entity (XXE)	XML parser configuration
Critical	Path Traversal	File path validation
Critical	Insecure Deserialization	Safe deserialization patterns
Critical	Code Injection	Eval safety, template injection
Critical	Hardcoded Secrets	Environment variables, secret management
Critical	Memory Safety	Buffer overflows, use-after-free (C/C++)
High	Insecure Cryptography	Strong hashing (SHA-256+), encryption (AES)
High	Insecure Transport	HTTPS, certificate validation, TLS
High	Server-Side Request Forgery	URL validation, allowlists
High	JWT Authentication	Signature verification, algorithm safety
High	Cross-Site Request Forgery	CSRF tokens, SameSite cookies
High	Prototype Pollution	Object key validation (JavaScript)
High	Unsafe Functions	Dangerous function alternatives
High	Terraform AWS	S3, IAM, EC2, RDS security
High	Terraform Azure	Storage, App Service, Key Vault
High	Terraform GCP	GCS, GCE, GKE, IAM
High	Kubernetes	Pod security, RBAC, secrets
High	Docker	Non-root containers, image pinning
High	GitHub Actions	Script injection, action pinning
Medium	Regex DoS	Catastrophic backtracking prevention
Medium	Race Conditions	TOCTOU, secure temp files
Medium	Code Correctness	Common bugs, type errors
Low	Best Practices	Code quality patterns
Low	Performance	Efficiency anti-patterns
Low	Maintainability	Code organization

Languages: Python, JavaScript/TypeScript, Java, Go, Ruby, PHP, C/C++, C#, Scala, Kotlin, Rust, HCL (Terraform), YAML (Kubernetes)

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llm-security

Security guidelines for LLM applications based on the OWASP Top 10 for Large Language Model Applications 2025.

Use when:

• Building LLM-powered applications
• Implementing RAG systems
• Securing AI/ML pipelines
• Reviewing code that interacts with language models

Categories covered:

Impact	Category	Description
Critical	Prompt Injection	Input validation, content segregation, output filtering
Critical	Sensitive Information Disclosure	PII detection, permission-aware RAG
Critical	Supply Chain	Model verification, safetensors, ML-BOM
Critical	Data and Model Poisoning	Training data validation, anomaly detection
Critical	Improper Output Handling	Context-aware encoding, parameterized queries
High	Excessive Agency	Least privilege, human-in-the-loop
High	System Prompt Leakage	External guardrails, no secrets in prompts
High	Vector and Embedding Weaknesses	Permission-aware retrieval, tenant isolation
High	Misinformation	RAG, fact verification, confidence scoring
High	Unbounded Consumption	Rate limiting, budget controls

Frameworks: OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF

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semgrep

Run Semgrep static analysis scans and create custom detection rules for security vulnerabilities and bug patterns.

Use when:

• Running security scans with Semgrep
• Creating custom Semgrep rules
• Detecting specific vulnerability patterns
• Setting up Semgrep in CI/CD pipelines

Capabilities:

Feature	Description
Quick Scans	Run semgrep --config auto or use curated rulesets
Rulesets	security-audit, owasp-top-ten, cwe-top-25, trailofbits
Custom Rules	Pattern matching and taint mode for data flow analysis
Test-Driven	Write test cases first with ruleid: and ok: annotations
CI/CD	GitHub Actions integration with diff-aware scanning

Rule Creation Workflow:

1. Analyze the vulnerability pattern
2. Create test cases first (test-driven development)
3. Analyze AST structure with semgrep --dump-ast
4. Write the rule (taint mode for injection, pattern matching for syntax)
5. Iterate until 100% tests pass
6. Optimize patterns

When to use taint mode: SQL injection, command injection, XSS, path traversal, SSRF - any vulnerability where untrusted data flows to a dangerous sink.

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Usage

Skills are automatically available once installed. The agent will use them when relevant tasks are detected.

Examples:

Review this React component for security issues

Help me implement input validation for my LLM chat endpoint

Create a Semgrep rule to detect hardcoded API keys in Python

Development

Building Skills

make install     # Install dependencies
make validate    # Validate all skills
make build       # Build AGENTS.md for all skills
make zip         # Create distribution packages
make             # All of the above

Single Skill Operations

make validate-skill SKILL=code-security
make build-skill SKILL=llm-security

Skill Structure

Each skill contains:

• SKILL.md - Instructions for the agent
• rules/ - Individual rule files (for skills with rules)
• scripts/ - Helper scripts for automation (optional)
• references/ - Supporting documentation (optional)

Acknowledgments

Originally created by @DrewDennison at Semgrep. This work was heavily inspired by Vercel's React Best Practices.