Awesome-omni-skills security-scanning-security-sast

SAST Security Plugin workflow skill. Use this skill when the user needs 'Static Application Security Testing (SAST) for code vulnerability and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/security-scanning-security-sast" ~/.claude/skills/diegosouzapw-awesome-omni-skills-security-scanning-security-sast && rm -rf "$T"
manifest: skills/security-scanning-security-sast/SKILL.md
source content

SAST Security Plugin

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/security-scanning-security-sast
from
https://github.com/sickn33/antigravity-awesome-skills
into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json
plus
ORIGIN.md
as the provenance anchor for review.

SAST Security Plugin Static Application Security Testing (SAST) for comprehensive code vulnerability detection across multiple languages, frameworks, and security patterns.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Capabilities, Safety, SAST Tool Selection, Vulnerability Patterns, Framework Security, Multi-Language Scanner Implementation.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

  • You only need runtime testing or penetration testing
  • You cannot access the source code or build outputs
  • The environment forbids third-party scanning tools
  • Use when the request clearly matches the imported source intent: 'Static Application Security Testing (SAST) for code vulnerability.
  • Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
  • Use when provenance needs to stay visible in the answer, PR, or review packet.

Operating Table

SituationStart hereWhy it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
SKILL.md
Starts with the smallest copied file that materially changes execution
Supporting context
SKILL.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

  1. Identify the languages, frameworks, and scope to scan.
  2. Select SAST tools and configure rules for the codebase.
  3. Run scans in CI or locally with reproducible settings.
  4. Triage findings, prioritize by severity, and propose fixes.
  5. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
  6. Read the overview and provenance files before loading any copied upstream support files.
  7. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.

Imported Workflow Notes

Imported: Instructions

  1. Identify the languages, frameworks, and scope to scan.
  2. Select SAST tools and configure rules for the codebase.
  3. Run scans in CI or locally with reproducible settings.
  4. Triage findings, prioritize by severity, and propose fixes.

Imported: Capabilities

  • Multi-language SAST: Python, JavaScript/TypeScript, Java, Ruby, PHP, Go, Rust
  • Tool integration: Bandit, Semgrep, ESLint Security, SonarQube, CodeQL, PMD, SpotBugs, Brakeman, gosec, cargo-clippy
  • Vulnerability patterns: SQL injection, XSS, hardcoded secrets, path traversal, IDOR, CSRF, insecure deserialization
  • Framework analysis: Django, Flask, React, Express, Spring Boot, Rails, Laravel
  • Custom rule authoring: Semgrep pattern development for organization-specific security policies

Examples

Example 1: Ask for the upstream workflow directly

Use @security-scanning-security-sast to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @security-scanning-security-sast against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @security-scanning-security-sast for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @security-scanning-security-sast using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

  • Run early and often - Pre-commit hooks and CI/CD
  • Combine multiple tools - Different tools catch different vulnerabilities
  • Tune false positives - Configure exclusions and thresholds
  • Prioritize findings - Focus on CRITICAL/HIGH first
  • Framework-aware scanning - Use specific rulesets
  • Custom rules - Organization-specific patterns
  • Developer training - Secure coding practices

Imported Operating Notes

Imported: Best Practices

  1. Run early and often - Pre-commit hooks and CI/CD
  2. Combine multiple tools - Different tools catch different vulnerabilities
  3. Tune false positives - Configure exclusions and thresholds
  4. Prioritize findings - Focus on CRITICAL/HIGH first
  5. Framework-aware scanning - Use specific rulesets
  6. Custom rules - Organization-specific patterns
  7. Developer training - Secure coding practices
  8. Incremental remediation - Fix gradually
  9. Baseline management - Track known issues
  10. Regular updates - Keep tools current

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/security-scanning-security-sast
, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open
metadata.json
,
ORIGIN.md
, and the most relevant copied upstream files. Load only the files that materially change the answer, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md
, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

  • @00-andruia-consultant-v2
    - Use when the work is better handled by that native specialization after this imported skill establishes context.
  • @10-andruia-skill-smith-v2
    - Use when the work is better handled by that native specialization after this imported skill establishes context.
  • @20-andruia-niche-intelligence-v2
    - Use when the work is better handled by that native specialization after this imported skill establishes context.
  • @2d-games
    - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Resource familyWhat it gives the reviewerExample path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
assets/n/a

Imported Reference Notes

Imported: Safety

  • Avoid uploading proprietary code to external services without approval.
  • Require review before enabling auto-fix or blocking releases.

Imported: SAST Tool Selection

Python: Bandit

# Installation & scan
pip install bandit
bandit -r . -f json -o bandit-report.json
bandit -r . -ll -ii -f json  # High/Critical only

Configuration:

.bandit

exclude_dirs: ['/tests/', '/venv/', '/.tox/', '/build/']
tests: [B201, B301, B302, B303, B304, B305, B307, B308, B312, B323, B324, B501, B502, B506, B602, B608]
skips: [B101]

JavaScript/TypeScript: ESLint Security

npm install --save-dev eslint @eslint/plugin-security eslint-plugin-no-secrets
eslint . --ext .js,.jsx,.ts,.tsx --format json > eslint-security.json

Configuration:

.eslintrc-security.json

{
  "plugins": ["@eslint/plugin-security", "eslint-plugin-no-secrets"],
  "extends": ["plugin:security/recommended"],
  "rules": {
    "security/detect-object-injection": "error",
    "security/detect-non-literal-fs-filename": "error",
    "security/detect-eval-with-expression": "error",
    "security/detect-pseudo-random-prng": "error",
    "no-secrets/no-secrets": "error"
  }
}

Multi-Language: Semgrep

pip install semgrep
semgrep --config=auto --json --output=semgrep-report.json
semgrep --config=p/security-audit --json
semgrep --config=p/owasp-top-ten --json
semgrep ci --config=auto  # CI mode

Custom Rules:

.semgrep.yml

rules:
  - id: sql-injection-format-string
    pattern: cursor.execute("... %s ..." % $VAR)
    message: SQL injection via string formatting
    severity: ERROR
    languages: [python]
    metadata:
      cwe: "CWE-89"
      owasp: "A03:2021-Injection"

  - id: dangerous-innerHTML
    pattern: $ELEM.innerHTML = $VAR
    message: XSS via innerHTML assignment
    severity: ERROR
    languages: [javascript, typescript]
    metadata:
      cwe: "CWE-79"

  - id: hardcoded-aws-credentials
    patterns:
      - pattern: $KEY = "AKIA..."
      - metavariable-regex:
          metavariable: $KEY
          regex: "(aws_access_key_id|AWS_ACCESS_KEY_ID)"
    message: Hardcoded AWS credentials detected
    severity: ERROR
    languages: [python, javascript, java]

  - id: path-traversal-open
    patterns:
      - pattern: open($PATH, ...)
      - pattern-not: open(os.path.join(SAFE_DIR, ...), ...)
      - metavariable-pattern:
          metavariable: $PATH
          patterns:
            - pattern: $REQ.get(...)
    message: Path traversal via user input
    severity: ERROR
    languages: [python]

  - id: command-injection
    patterns:
      - pattern-either:
          - pattern: os.system($CMD)
          - pattern: subprocess.call($CMD, shell=True)
      - metavariable-pattern:
          metavariable: $CMD
          patterns:
            - pattern-either:
                - pattern: $X + $Y
                - pattern: f"...{$VAR}..."
    message: Command injection via shell=True
    severity: ERROR
    languages: [python]

Other Language Tools

Java:

mvn spotbugs:check
Ruby:
brakeman -o report.json -f json
Go:
gosec -fmt=json -out=gosec.json ./...
Rust:
cargo clippy -- -W clippy::unwrap_used

Imported: Vulnerability Patterns

SQL Injection

VULNERABLE: String formatting/concatenation with user input in SQL queries

SECURE:

# Parameterized queries
cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))
User.objects.filter(id=user_id)  # ORM

Cross-Site Scripting (XSS)

VULNERABLE: Direct HTML manipulation with unsanitized user input (innerHTML, outerHTML, document.write)

SECURE:

// Use textContent for plain text
element.textContent = userInput;

// React auto-escapes
<div>{userInput}</div>

// Sanitize when HTML required
import DOMPurify from 'dompurify';
element.innerHTML = DOMPurify.sanitize(userInput);

Hardcoded Secrets

VULNERABLE: Hardcoded API keys, passwords, tokens in source code

SECURE:

import os
API_KEY = os.environ.get('API_KEY')
PASSWORD = os.getenv('DB_PASSWORD')

Path Traversal

VULNERABLE: Opening files using unsanitized user input

SECURE:

import os
ALLOWED_DIR = '/var/www/uploads'
file_name = request.args.get('file')
file_path = os.path.join(ALLOWED_DIR, file_name)
file_path = os.path.realpath(file_path)
if not file_path.startswith(os.path.realpath(ALLOWED_DIR)):
    raise ValueError("Invalid file path")
with open(file_path, 'r') as f:
    content = f.read()

Insecure Deserialization

VULNERABLE: pickle.loads(), yaml.load() with untrusted data

SECURE:

import json
data = json.loads(user_input)  # SECURE
import yaml
config = yaml.safe_load(user_input)  # SECURE

Command Injection

VULNERABLE: os.system() or subprocess with shell=True and user input

SECURE:

subprocess.run(['ping', '-c', '4', user_input])  # Array args
import shlex
safe_input = shlex.quote(user_input)  # Input validation

Insecure Random

VULNERABLE: random module for security-critical operations

SECURE:

import secrets
token = secrets.token_hex(16)
session_id = secrets.token_urlsafe(32)

Imported: Framework Security

Django

VULNERABLE: @csrf_exempt, DEBUG=True, weak SECRET_KEY, missing security middleware

SECURE:

# settings.py
DEBUG = False
SECRET_KEY = os.environ.get('DJANGO_SECRET_KEY')

MIDDLEWARE = [
    'django.middleware.security.SecurityMiddleware',
    'django.middleware.csrf.CsrfViewMiddleware',
    'django.middleware.clickjacking.XFrameOptionsMiddleware',
]

SECURE_SSL_REDIRECT = True
SESSION_COOKIE_SECURE = True
CSRF_COOKIE_SECURE = True
X_FRAME_OPTIONS = 'DENY'

Flask

VULNERABLE: debug=True, weak secret_key, CORS wildcard

SECURE:

import os
from flask_talisman import Talisman

app.secret_key = os.environ.get('FLASK_SECRET_KEY')
Talisman(app, force_https=True)
CORS(app, origins=['https://example.com'])

Express.js

VULNERABLE: Missing helmet, CORS wildcard, no rate limiting

SECURE:

const helmet = require('helmet');
const rateLimit = require('express-rate-limit');

app.use(helmet());
app.use(cors({ origin: 'https://example.com' }));
app.use(rateLimit({ windowMs: 15 * 60 * 1000, max: 100 }));

Imported: Multi-Language Scanner Implementation

import json
import subprocess
from pathlib import Path
from typing import Dict, List, Any
from dataclasses import dataclass
from datetime import datetime

@dataclass
class SASTFinding:
    tool: str
    severity: str
    category: str
    title: str
    description: str
    file_path: str
    line_number: int
    cwe: str
    owasp: str
    confidence: str

class MultiLanguageSASTScanner:
    def __init__(self, project_path: str):
        self.project_path = Path(project_path)
        self.findings: List[SASTFinding] = []

    def detect_languages(self) -> List[str]:
        """Auto-detect languages"""
        languages = []
        indicators = {
            'python': ['*.py', 'requirements.txt'],
            'javascript': ['*.js', 'package.json'],
            'typescript': ['*.ts', 'tsconfig.json'],
            'java': ['*.java', 'pom.xml'],
            'ruby': ['*.rb', 'Gemfile'],
            'go': ['*.go', 'go.mod'],
            'rust': ['*.rs', 'Cargo.toml'],
        }
        for lang, patterns in indicators.items():
            for pattern in patterns:
                if list(self.project_path.glob(f'**/{pattern}')):
                    languages.append(lang)
                    break
        return languages

    def run_comprehensive_sast(self) -> Dict[str, Any]:
        """Execute all applicable SAST tools"""
        languages = self.detect_languages()

        scan_results = {
            'timestamp': datetime.now().isoformat(),
            'languages': languages,
            'tools_executed': [],
            'findings': []
        }

        self.run_semgrep_scan()
        scan_results['tools_executed'].append('semgrep')

        if 'python' in languages:
            self.run_bandit_scan()
            scan_results['tools_executed'].append('bandit')
        if 'javascript' in languages or 'typescript' in languages:
            self.run_eslint_security_scan()
            scan_results['tools_executed'].append('eslint-security')

        scan_results['findings'] = [vars(f) for f in self.findings]
        scan_results['summary'] = self.generate_summary()
        return scan_results

    def run_semgrep_scan(self):
        """Run Semgrep"""
        for ruleset in ['auto', 'p/security-audit', 'p/owasp-top-ten']:
            try:
                result = subprocess.run([
                    'semgrep', '--config', ruleset, '--json', '--quiet',
                    str(self.project_path)
                ], capture_output=True, text=True, timeout=300)

                if result.stdout:
                    data = json.loads(result.stdout)
                    for f in data.get('results', []):
                        self.findings.append(SASTFinding(
                            tool='semgrep',
                            severity=f.get('extra', {}).get('severity', 'MEDIUM').upper(),
                            category='sast',
                            title=f.get('check_id', ''),
                            description=f.get('extra', {}).get('message', ''),
                            file_path=f.get('path', ''),
                            line_number=f.get('start', {}).get('line', 0),
                            cwe=f.get('extra', {}).get('metadata', {}).get('cwe', ''),
                            owasp=f.get('extra', {}).get('metadata', {}).get('owasp', ''),
                            confidence=f.get('extra', {}).get('metadata', {}).get('confidence', 'MEDIUM')
                        ))
            except Exception as e:
                print(f"Semgrep {ruleset} failed: {e}")

    def generate_summary(self) -> Dict[str, Any]:
        """Generate statistics"""
        severity_counts = {'CRITICAL': 0, 'HIGH': 0, 'MEDIUM': 0, 'LOW': 0}
        for f in self.findings:
            severity_counts[f.severity] = severity_counts.get(f.severity, 0) + 1

        return {
            'total_findings': len(self.findings),
            'severity_breakdown': severity_counts,
            'risk_score': self.calculate_risk_score(severity_counts)
        }

    def calculate_risk_score(self, severity_counts: Dict[str, int]) -> int:
        """Risk score 0-100"""
        weights = {'CRITICAL': 10, 'HIGH': 7, 'MEDIUM': 4, 'LOW': 1}
        total = sum(weights[s] * c for s, c in severity_counts.items())
        return min(100, int((total / 50) * 100))

Imported: CI/CD Integration

GitHub Actions

name: SAST Scan
on:
  pull_request:
    branches: [main]

jobs:
  sast:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-python@v4
        with:
          python-version: '3.11'

      - name: Install tools
        run: |
          pip install bandit semgrep
          npm install -g eslint @eslint/plugin-security

      - name: Run scans
        run: |
          bandit -r . -f json -o bandit.json || true
          semgrep --config=auto --json --output=semgrep.json || true

      - name: Upload reports
        uses: actions/upload-artifact@v3
        with:
          name: sast-reports
          path: |
            bandit.json
            semgrep.json

GitLab CI

sast:
  stage: test
  image: python:3.11
  script:
    - pip install bandit semgrep
    - bandit -r . -f json -o bandit.json || true
    - semgrep --config=auto --json --output=semgrep.json || true
  artifacts:
    reports:
      sast: bandit.json

Imported: Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.