Sast Semgrep logo

Sast Semgrep

Organization
AgentSecOps
sast-semgrep

Static application security testing (SAST) using Semgrep for vulnerability detection, security code review, and secure coding guidance with OWASP and CWE framework mapping. Use when: (1) Scanning code for security vulnerabilities across multiple languages, (2) Performing security code reviews with pattern-based detection, (3) Integrating SAST checks into CI/CD pipelines, (4) Providing remediation guidance with OWASP Top 10 and CWE mappings, (5) Creating custom security rules for organization-specific patterns, (6) Analyzing dependencies for known vulnerabilities.

Overview

PublisherAgentSecOps
RepositorySecOpsAgentKit
Skill namesast-semgrep
Stars
225
Forks
44
Bundled files
8
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AgentSecOps on GitHub. Read the source before you install it.

Installation

Install the Sast Semgrep AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AgentSecOps/SecOpsAgentKit/tree/main/skills/appsec/sast-semgrep
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgentSecOps/SecOpsAgentKit.git /tmp/SecOpsAgentKit
mkdir -p .claude/skills
cp -r /tmp/SecOpsAgentKit/skills/appsec/sast-semgrep .claude/skills/sast-semgrep
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sast Semgrep in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sast Semgrep on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sast Semgrep is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SAST with Semgrep

Overview

Perform comprehensive static application security testing using Semgrep, a fast, open-source static analysis tool. This skill provides automated vulnerability detection, security code review workflows, and remediation guidance mapped to OWASP Top 10 and CWE standards.

Quick Start

Scan a codebase for security vulnerabilities:

bash
semgrep --config=auto --severity=ERROR --severity=WARNING /path/to/code

Run with OWASP Top 10 ruleset:

bash
semgrep --config="p/owasp-top-ten" /path/to/code

Core Workflows

Workflow 1: Initial Security Scan

  1. Identify the primary languages in the codebase
  2. Run scripts/semgrep_scan.py with appropriate rulesets
  3. Parse findings and categorize by severity (CRITICAL, HIGH, MEDIUM, LOW)
  4. Map findings to OWASP Top 10 and CWE categories
  5. Generate prioritized remediation report

Workflow 2: Security Code Review

  1. For pull requests or commits, run targeted scans on changed files
  2. Use semgrep --diff to scan only modified code
  3. Flag high-severity findings as blocking issues
  4. Provide inline remediation guidance from references/remediation_guide.md
  5. Link findings to secure coding patterns

Workflow 3: Custom Rule Development

  1. Identify organization-specific security patterns to detect
  2. Create custom Semgrep rules in YAML format using assets/rule_template.yaml
  3. Test rules against known vulnerable code samples
  4. Integrate custom rules into CI/CD pipeline
  5. Document rules in references/custom_rules.md

Workflow 4: CI/CD Integration

  1. Add Semgrep to CI/CD pipeline using assets/ci_config_examples/
  2. Configure baseline scanning for pull requests
  3. Set severity thresholds (fail on CRITICAL/HIGH)
  4. Generate SARIF output for security dashboards
  5. Track metrics: vulnerabilities found, fix rate, false positives

Security Considerations

  • Sensitive Data Handling: Semgrep scans code locally; ensure scan results don't leak secrets or proprietary code patterns. Use --max-lines-per-finding to limit output.

  • Access Control: Semgrep scans require read access to source code. Restrict scan result access to authorized security and development teams.

  • Audit Logging: Log all scan executions with timestamps, user, commit hash, and findings count for compliance auditing.

  • Compliance: SAST scanning supports SOC2, PCI-DSS, and GDPR compliance requirements. Maintain scan history and remediation tracking.

  • Safe Defaults: Use --config=auto for balanced detection. For security-critical applications, use --config="p/security-audit" for comprehensive coverage.

Language Support

Semgrep supports 30+ languages including:

  • Web: JavaScript, TypeScript, Python, Ruby, PHP, Java, C#, Go
  • Mobile: Swift, Kotlin, Java (Android)
  • Infrastructure: Terraform, Dockerfile, YAML, JSON
  • Other: C, C++, Rust, Scala, Solidity

Bundled Resources

Scripts

  • scripts/semgrep_scan.py - Full-featured scanning with OWASP/CWE mapping and reporting
  • scripts/baseline_scan.sh - Quick baseline scan for CI/CD
  • scripts/diff_scan.sh - Scan only changed files (for PRs)

References

  • references/owasp_cwe_mapping.md - OWASP Top 10 to CWE mapping with Semgrep rules
  • references/remediation_guide.md - Vulnerability remediation patterns by category
  • references/rule_library.md - Curated list of useful Semgrep rulesets

Assets

  • assets/rule_template.yaml - Template for creating custom Semgrep rules
  • assets/ci_config_examples/ - CI/CD integration examples (GitHub Actions, GitLab CI)
  • assets/semgrep_config.yaml - Recommended Semgrep configuration

Common Patterns

Pattern 1: Daily Security Baseline Scan

bash
# Run comprehensive scan and generate report
scripts/semgrep_scan.py --config security-audit \
  --output results.json \
  --format json \
  --severity HIGH CRITICAL

Pattern 2: Pull Request Security Gate

bash
# Scan only changed files, fail on HIGH/CRITICAL
scripts/diff_scan.sh --fail-on high \
  --base-branch main \
  --output sarif

Pattern 3: Vulnerability Research

bash
# Search for specific vulnerability patterns
semgrep --config "r/javascript.lang.security.audit.xss" \
  --json /path/to/code | jq '.results'

Pattern 4: Custom Rule Validation

bash
# Test custom rule against vulnerable samples
semgrep --config assets/custom_rules.yaml \
  --test tests/vulnerable_samples/

Integration Points

CI/CD Integration

  • GitHub Actions: Use semgrep/semgrep-action@v1 with SARIF upload
  • GitLab CI: Run as security scanning job with artifact reports
  • Jenkins: Execute as build step with quality gate integration
  • pre-commit hooks: Run lightweight scans on staged files

See assets/ci_config_examples/ for ready-to-use configurations.

Security Tool Integration

  • SIEM/SOAR: Export findings in JSON/SARIF for ingestion
  • Vulnerability Management: Integrate with Jira, DefectDojo, or ThreadFix
  • IDE Integration: Use Semgrep IDE plugins for real-time detection
  • Secret Scanning: Combine with tools like trufflehog, gitleaks

SDLC Integration

  • Requirements Phase: Define security requirements and custom rules
  • Development: IDE plugins provide real-time feedback
  • Code Review: Automated security review in PR workflow
  • Testing: Integrate with security testing framework
  • Deployment: Final security gate before production

Severity Classification

Semgrep findings are classified by severity:

  • CRITICAL: Exploitable vulnerabilities (SQLi, RCE, Auth bypass)
  • HIGH: Significant security risks (XSS, CSRF, sensitive data exposure)
  • MEDIUM: Security weaknesses (weak crypto, missing validation)
  • LOW: Code quality issues with security implications
  • INFO: Security best practice recommendations

Performance Optimization

For large codebases:

bash
# Use --jobs for parallel scanning
semgrep --config auto --jobs 4

# Exclude vendor/test code
semgrep --config auto --exclude "vendor/" --exclude "test/"

# Use lightweight rulesets for faster feedback
semgrep --config "p/owasp-top-ten" --exclude-rule "generic.*"

Troubleshooting

Issue: Too Many False Positives

Solution:

  • Use --exclude-rule to disable noisy rules
  • Create .semgrepignore file to exclude false positive patterns
  • Tune rules using --severity filtering
  • Add # nosemgrep comments for confirmed false positives (with justification)

Issue: Scan Taking Too Long

Solution:

  • Use --exclude for vendor/generated code
  • Increase --jobs for parallel processing
  • Use targeted rulesets instead of --config=auto
  • Run incremental scans with --diff

Issue: Missing Vulnerabilities

Solution:

  • Use comprehensive rulesets: p/security-audit or p/owasp-top-ten
  • Consult references/rule_library.md for specialized rules
  • Create custom rules for organization-specific patterns
  • Combine with dynamic analysis (DAST) and dependency scanning

Advanced Usage

Creating Custom Rules

See references/rule_library.md for guidance on writing effective Semgrep rules. Use assets/rule_template.yaml as a starting point.

Example rule structure:

yaml
rules:
  - id: custom-sql-injection
    patterns:
      - pattern: execute($QUERY)
      - pattern-inside: |
          $QUERY = $USER_INPUT + ...
    message: Potential SQL injection from user input concatenation
    severity: ERROR
    languages: [python]
    metadata:
      cwe: "CWE-89"
      owasp: "A03:2021-Injection"

OWASP Top 10 Coverage

This skill provides detection for all OWASP Top 10 2021 categories. See references/owasp_cwe_mapping.md for complete coverage matrix.

Best Practices

  1. Baseline First: Establish security baseline before enforcing gates
  2. Progressive Rollout: Start with HIGH/CRITICAL, expand to MEDIUM over time
  3. Developer Training: Educate team on common vulnerabilities and fixes
  4. Rule Maintenance: Regularly update rulesets and tune for your stack
  5. Metrics Tracking: Monitor vulnerability trends, MTTR, and false positive rate
  6. Defense in Depth: Combine with DAST, SCA, and manual code review

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sast Semgrep AI skill do?

Static application security testing (SAST) using Semgrep for vulnerability detection, security code review, and secure coding guidance with OWASP and CWE framework mapping. Use when: (1) Scanning code for security vulnerabilities across multiple languages, (2) Performing security code reviews with pattern-based detection, (3) Integrating SAST checks into CI/CD pipelines, (4) Providing remediation guidance with OWASP Top 10 and CWE mappings, (5) Creating custom security rules for organization-specific patterns, (6) Analyzing dependencies for known vulnerabilities.

Why use Sast Semgrep on TypingMind?

Because you install it once and use it with any model. Sast Semgrep is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sast Semgrep in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgentSecOps/SecOpsAgentKit/tree/main/skills/appsec/sast-semgrep. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sast Semgrep?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sast Semgrep?

As many as you like. As long as a model supports skills, you can use Sast Semgrep with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sast Semgrep AI skill free?

It is published on GitHub by AgentSecOps. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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