Security Scanning Guide

Overview

This guide explains the automated security scanning procedures used in the Synaptic Canvas marketplace. Security scanning helps identify potential vulnerabilities, coding issues, and policy violations before they reach users.

Purpose

Automated security scanning serves several critical functions:

Early Detection: Identify security issues during development
Consistent Standards: Apply uniform security checks across all packages
Risk Reduction: Prevent vulnerable code from reaching users
Compliance: Ensure packages meet marketplace security requirements
Transparency: Provide visibility into security practices

The Security Scanner

The security scanner is implemented in scripts/security-scan.py and performs six categories of checks:

Secrets Detection
Script Quality
Python Safety
Package Documentation
License Files
Dependency Audit

Quick Reference

# Full security scan
./scripts/security-scan.py

# Quick scan (skip slow checks)
./scripts/security-scan.py --quick

# JSON output for CI/CD
./scripts/security-scan.py --json

# Scan single package
./scripts/security-scan.py --package sc-delay-tasks

Check Categories

1. Secrets Detection

Purpose: Identify hardcoded credentials, API keys, and other sensitive data

What It Checks:

Hardcoded passwords (password = "...")
API keys (api_key = "...")
Secret tokens (secret = "...", token = "...")
AWS credentials (AWS_KEY, AWS_SECRET)
GitHub tokens (GITHUB_TOKEN)
Private keys (private_key, BEGIN PRIVATE KEY)
Credentials in markdown documentation

Why It Matters:

Hardcoded secrets are a critical security vulnerability. If committed to a repository:

Credentials are visible to anyone with access
They remain in git history even if deleted
Automated scanners can find and exploit them
Rotating compromised credentials is difficult and expensive

Common Violations:

# BAD: Hardcoded API key
api_key = "sk_live_abc123xyz789"

# BAD: Password in configuration
db_password = "MySecretPassword123"

# GOOD: Use environment variables
api_key = os.environ.get('API_KEY')
db_password = os.environ['DB_PASSWORD']

# BAD: Token in script
GITHUB_TOKEN="ghp_abc123xyz789"

# GOOD: Read from secure source
GITHUB_TOKEN="${GITHUB_TOKEN:-$(security find-generic-password -s github-token -w)}"

How to Fix:

Never commit secrets: Use environment variables or secure vaults
Use .gitignore: Exclude config files with secrets
Rotate exposed credentials: If you accidentally commit a secret, rotate it immediately
Use secret managers: AWS Secrets Manager, Azure Key Vault, etc.

False Positives:

The scanner may flag:

Example code showing the pattern (not actual secrets)
Test fixtures with dummy credentials
Documentation explaining secret handling

To address false positives:

Make examples obviously fake: password = "YOUR_PASSWORD_HERE"
Add comments: # Example only, not a real credential
Use clearly fake values: api_key = "test_key_not_real"

2. Script Quality

Purpose: Ensure shell scripts follow best practices and are maintainable

What It Checks:

Scripts are executable (chmod +x)
Shellcheck validation (if available)
Shebang line present (#!/usr/bin/env bash)
Error handling enabled (set -e or set -euo pipefail)

Why It Matters:

Quality shell scripts:

Fail fast when errors occur (prevent cascading failures)
Are portable across systems (proper shebang)
Are discoverable and runnable (executable permission)
Follow community best practices (shellcheck)

Shellcheck Integration:

If shellcheck is installed, the scanner runs it on all .sh files:

# Install shellcheck
brew install shellcheck  # macOS
apt-get install shellcheck  # Ubuntu

Shellcheck catches common issues:

Unquoted variables
Incorrect conditionals
Unsafe word splitting
Command substitution issues

Best Practices:

#!/usr/bin/env bash
# Good: Portable shebang, strict error handling

set -euo pipefail  # Exit on error, undefined vars, pipe failures

# Quote variables to prevent word splitting
file_name="my file.txt"
cat "$file_name"  # GOOD
cat $file_name    # BAD - breaks with spaces

# Use [[ ]] for conditionals (bash)
if [[ -f "$file_name" ]]; then  # GOOD
if [ -f $file_name ]; then      # OK but less robust

# Handle errors explicitly
if ! command; then
    echo "Command failed"
    exit 1
fi

Common Issues:

# Missing shebang
# IMPACT: Script may run with wrong shell
# FIX: Add #!/usr/bin/env bash at top

# Not executable
# IMPACT: Must run as "bash script.sh" instead of "./script.sh"
# FIX: chmod +x script.sh

# No error handling
# IMPACT: Script continues after failures
# FIX: Add "set -e" or "set -euo pipefail"

3. Python Safety

Purpose: Detect unsafe Python patterns that could lead to security vulnerabilities

What It Checks:

eval() calls - arbitrary code execution
exec() calls - arbitrary code execution
shell=True in subprocess - shell injection risk
pickle.loads() - arbitrary code execution via deserialization

Why It Matters:

These patterns can allow attackers to:

Execute arbitrary code on your system
Read/modify sensitive files
Escalate privileges
Create backdoors

Unsafe Patterns:

# 1. eval() - NEVER USE
user_input = "print('hello')"
eval(user_input)  # DANGER: Could be "__import__('os').system('rm -rf /')"

# 2. exec() - NEVER USE
code = request.get('code')
exec(code)  # DANGER: Arbitrary code execution

# 3. shell=True - AVOID
import subprocess
file = user_input
subprocess.call(f"cat {file}", shell=True)  # DANGER: Shell injection

# 4. pickle.loads() - AVOID
import pickle
data = pickle.loads(untrusted_data)  # DANGER: Can execute code during load

Safe Alternatives:

# Instead of eval() for math
from ast import literal_eval
result = literal_eval("1 + 2")  # Safe: Only evaluates literals

# Instead of exec() for dynamic behavior
# Use: dispatch tables, getattr(), or plugin systems
handlers = {
    'action1': handle_action1,
    'action2': handle_action2
}
handlers[user_choice]()  # Safe: Controlled options

# Instead of shell=True
import subprocess
# Use list arguments (no shell)
subprocess.run(['cat', file])  # Safe: No shell injection

# Instead of pickle
import json
data = json.loads(untrusted_json)  # Safer: Data only, no code

When These Patterns Are Acceptable:

The scanner may flag legitimate uses in:

Development/debug scripts (not production)
Controlled environments with trusted input only
Legacy code being refactored

If you must use these patterns:

Document why it's necessary
Validate and sanitize all input
Run in isolated environment
Add extra security layers (sandboxing, permissions)
Plan migration to safer alternatives

4. Package Documentation

Purpose: Ensure all packages have complete, accurate documentation

What It Checks:

README.md exists in each package
README mentions security
LICENSE file present
manifest.yaml exists and is valid YAML
CHANGELOG.md exists (recommended)

Why It Matters:

Complete documentation:

Helps users understand package purpose and usage
Provides security information and best practices
Establishes legal terms (license)
Tracks changes and versioning (changelog)
Meets marketplace requirements

Required Files:

packages/
  your-package/
    README.md        # REQUIRED: Package description, usage
    LICENSE          # REQUIRED: Legal terms
    manifest.yaml    # REQUIRED: Package metadata
    CHANGELOG.md     # RECOMMENDED: Version history

README.md Requirements:

Must include:

Package name and brief description
Installation instructions
Usage examples
Security mention (link to SECURITY.md or security section)
License information

Example:

# my-package

Brief description of what it does.

## Installation

\`\`\`bash
python3 tools/sc-install.py install my-package
\`\`\`

## Usage

Examples here...

## Security

See [SECURITY.md](../../SECURITY.md) for security practices.

## License

MIT

manifest.yaml Requirements:

Must be valid YAML with required fields:

name: my-package
version: 1.0.0
description: What it does
author: your-handle
tags: [relevant, tags]

artifacts:
  commands:
    - commands/my-command.md
  skills:
    - skills/my-skill/SKILL.md

Common Issues:

Missing README.md
→ Create README with installation and usage

README exists but no security mention
→ Add security section or link to SECURITY.md

LICENSE missing
→ Copy LICENSE from another package or repo root

manifest.yaml invalid YAML
→ Check syntax with: python3 -m yaml manifest.yaml

CHANGELOG.md missing (warning only)
→ Create CHANGELOG to track version history

5. License Files

Purpose: Ensure all packages have proper legal licensing

What It Checks:

Each package has LICENSE file
LICENSE files are not empty
Repository root has LICENSE

Why It Matters:

License files:

Define legal terms for package use
Protect maintainers from liability
Clarify user rights and obligations
Meet marketplace and legal requirements
Enable open source distribution

License Requirements:

All Synaptic Canvas packages should use MIT License for consistency:

MIT License

Copyright (c) 2025 Your Name

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

[... full MIT license text ...]

Best Practices:

Consistent Licensing: Use same license across all packages
Copy LICENSE: Each package should have its own LICENSE file
Update Copyright: Use current year and correct author
Include Full Text: Don't abbreviate or truncate license
Match README: LICENSE mentioned in README should match actual file

6. Dependency Audit

Purpose: Identify vulnerable or outdated dependencies

What It Checks:

npm dependencies (if package.json exists)
Python dependencies (if requirements.txt exists)
Git URLs using insecure protocols
Known vulnerable package versions

Why It Matters:

Vulnerable dependencies can:

Introduce security holes into your packages
Expose user systems to attacks
Violate security policies
Damage reputation and trust

npm Audit:

If Node.js packages exist, runs npm audit:

cd project-root
npm audit

# Example output:
# High severity vulnerability in lodash < 4.17.12
# Run npm audit fix to resolve

Python Dependencies:

Checks for known vulnerable packages:

pyyaml < 5.4 (YAML parsing vulnerabilities)
requests < 2.20.0 (Security issues)
urllib3 < 1.26.5 (Multiple CVEs)

How to Fix:

# Node.js: Auto-fix vulnerabilities
npm audit fix

# Python: Update to safe versions
pip3 install --upgrade pyyaml requests urllib3

# Verify fixes
npm audit  # Should show 0 vulnerabilities
pip3 check  # Should show no issues

Insecure Git URLs:

# BAD: Insecure git:// protocol
dependencies:
  - git://github.com/user/repo.git

# GOOD: Secure https:// protocol
dependencies:
  - https://github.com/user/repo.git

Severity Levels:

HIGH: Critical vulnerabilities, known exploits, immediate fix required
MEDIUM: Moderate risk, should fix soon
LOW: Minor issues, fix when convenient

Running Security Scans

Local Development

Run before committing code:

# Full scan
./scripts/security-scan.py

# Quick scan (faster, skips dependency audit)
./scripts/security-scan.py --quick

# Scan specific package
./scripts/security-scan.py --package your-package

Continuous Integration

Integrate into CI/CD pipeline:

# .github/workflows/security.yml
name: Security Scan

on: [push, pull_request]

jobs:
  security:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Run security scan
        run: ./scripts/security-scan.py --json > scan-results.json
      - name: Check results
        run: |
          if [ $? -ne 0 ]; then
            echo "Security scan failed"
            exit 1
          fi
      - name: Upload results
        uses: actions/upload-artifact@v3
        with:
          name: security-scan-results
          path: scan-results.json

Pre-Commit Hooks

Run automatically on commit:

# .git/hooks/pre-commit
#!/bin/bash
echo "Running security scan..."
./scripts/security-scan.py --quick
if [ $? -ne 0 ]; then
    echo "Security scan failed. Commit aborted."
    exit 1
fi

Make executable:

chmod +x .git/hooks/pre-commit

Scheduled Scans

Run weekly to catch new vulnerabilities:

# .github/workflows/weekly-security.yml
name: Weekly Security Scan

on:
  schedule:
    - cron: '0 0 * * 0'  # Every Sunday at midnight

jobs:
  security:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Run full security scan
        run: ./scripts/security-scan.py

Interpreting Results

Exit Codes

0 - All checks passed
1 - Warnings found (non-critical issues)
2 - Failures found (critical issues requiring attention)

Output Format

Text Output (default):

═══════════════════════════════════════════════════════════
Security Scan Report - 2025-12-04T12:34:56Z
═══════════════════════════════════════════════════════════

✅ Secrets Detection: PASSED (0 potential secrets found)
✅ Script Quality: PASSED (all 3 scripts valid)
✅ Python Safety: PASSED (no unsafe patterns found)
✅ Package Documentation: PASSED (all 4 packages have required docs)
✅ License Files: PASSED (all packages have LICENSE)
⚠️  Dependency Audit: WARNING (2 medium severity warnings)
   [MEDIUM] Check version of requests (known vulnerabilities in old versions)

─────────────────────────────────────────────────────────

OVERALL STATUS: ⚠️  PASSED (with warnings)
Total Issues Found: 2
Scan Date: 2025-12-04T12:34:56Z

JSON Output:

{
  "scan_date": "2025-12-04T12:34:56Z",
  "overall_status": "WARNING",
  "issues_found": 2,
  "checks": {
    "secrets_detection": "PASSED",
    "script_quality": "PASSED",
    "python_safety": "PASSED",
    "package_documentation": "PASSED",
    "license_files": "PASSED",
    "dependency_audit": "WARNING"
  },
  "scan_configuration": {
    "quick_mode": false,
    "single_package": null,
    "repo_root": "/path/to/repo"
  }
}

Status Indicators

PASSED ✅: No issues found
WARNING ⚠️: Non-critical issues that should be addressed
FAILED ❌: Critical issues requiring immediate attention
SKIPPED ⊘: Check was skipped (e.g., quick mode)

Issue Severity

HIGH: Critical security risk, fix immediately
MEDIUM: Moderate risk, plan fix soon
LOW: Minor issue, fix when convenient

Troubleshooting

Common Issues

Issue: "shellcheck: command not found"

# Scanner works without shellcheck, but install for better checks
brew install shellcheck  # macOS
apt-get install shellcheck  # Ubuntu

Issue: "npm: command not found"

# Dependency audit skipped if npm not installed
# Install Node.js to enable npm audit
brew install node  # macOS

Issue: "Permission denied: ./scripts/security-scan.py"

# Make script executable
chmod +x scripts/security-scan.py

Issue: "Package not found: my-package"

# Verify package exists
ls packages/my-package

# Check package name spelling
./scripts/security-scan.py --package sc-delay-tasks  # Correct name

False Positives

If scan flags legitimate code:

Verify it's actually safe: Double-check the flagged code
Add comments: Explain why pattern is acceptable
Refactor if possible: Use safer alternatives
Document exception: Note in SECURITY.md why it's necessary

Example:

# This eval() is safe because input is sanitized and validated
# against whitelist before evaluation. Used only for math expressions
# in controlled development environment.
if is_safe_math_expression(user_input):
    result = eval(user_input)

Best Practices

For Package Authors

Run Before Committing: Always scan locally before pushing
Fix Issues Promptly: Don't accumulate security debt
Document Exceptions: Explain any flagged patterns
Keep Dependencies Updated: Regular dependency audits
Review Scan Results: Understand each finding

For Reviewers

Require Clean Scans: PRs should pass security scan
Question Exceptions: Verify documented exceptions are legitimate
Check Fixes: Ensure issues were actually resolved
Consider Context: Some warnings acceptable in specific contexts

For CI/CD

Fail Fast: Block deployments on security failures
Store Results: Archive scan results for audit trail
Notify Team: Alert on new security issues
Trend Analysis: Track security metrics over time

Automation Schedule

This section details when and how security scans are performed. Automated security scanning is a key component of our security commitment, helping identify vulnerabilities early and maintain package quality.

Scan Types

Full Security Scan

What It Includes:

Secrets detection
Script quality checks
Python safety analysis
Package documentation verification
License file validation
Complete dependency audit

Duration: ~2-5 minutes depending on repository size

Command: ./scripts/security-scan.py

Quick Scan

What It Includes:

Secrets detection
Script quality checks
Python safety analysis
Package documentation verification
License file validation

Excludes: Dependency audit (time-consuming)

Duration: ~30-60 seconds

Command: ./scripts/security-scan.py --quick

Scan Schedule

1. On Every Release (Automated)

Trigger: Git tag creation or version bump

Type: Full security scan

Purpose: Ensure no security issues in released versions

Process:

Version bump or tag detected
Automated CI/CD pipeline triggered
Full security scan executed
Results recorded in artifacts
Release blocked if critical issues found

Pass Criteria:

No HIGH severity issues
Zero hardcoded secrets
All packages have required documentation
All license files present

Failure Action:

Release blocked
Maintainer notified
Issues must be fixed before retry

2. Weekly Scheduled Scans (Automated)

Schedule: Every Sunday at 00:00 UTC

Type: Full security scan

Purpose: Catch newly discovered vulnerabilities in dependencies

Process:

GitHub Actions cron trigger
Full security scan on main branch
Results compared to previous week
Report generated and archived
Notifications sent if new issues found

Why Weekly:

New CVEs published regularly
Dependencies may become vulnerable over time
Catch configuration drift
Maintain security baseline

Notification:

GitHub Issues created for new HIGH severity
Summary in weekly repository digest
Archived in repository Actions tab

3. On Pull Requests (Automated)

Trigger: PR opened or updated

Type: Quick scan + targeted full scan on changed files

Purpose: Prevent security regressions

Process:

PR created or updated
Quick scan runs immediately
Changed packages get full scan
Results posted as PR comment
Checks must pass for merge

Checked:

Only changed files and packages
No new secrets introduced
Script quality maintained
Documentation updated appropriately

Pass Criteria:

Quick scan passes
No new HIGH severity issues
All checks green

Developer Experience:

Fast feedback (< 2 minutes)
Clear actionable results
Blockers explained with remediation

4. Manual On-Demand Scans

Trigger: Developer runs script locally

Type: Full or quick (developer choice)

Purpose: Pre-commit validation, troubleshooting

Process:

# Full scan
./scripts/security-scan.py

# Quick scan
./scripts/security-scan.py --quick

# Single package
./scripts/security-scan.py --package sc-delay-tasks

# JSON output
./scripts/security-scan.py --json > results.json

When to Run:

Before committing changes
After dependency updates
When troubleshooting issues
Before opening PR

Best Practice: Run quick scan pre-commit, full scan pre-PR

5. Post-Incident Scans

Trigger: Security incident or vulnerability report

Type: Comprehensive audit (full scan + manual review)

Purpose: Verify fix completeness and identify related issues

Process:

Incident reported or detected
Immediate targeted scan
Fix developed and applied
Full scan to verify fix
Extended manual review
Additional targeted scans

Scope:

All packages (not just affected)
Historical commits if needed
Related code patterns
Documentation accuracy

What Is Checked (Summary by Scan Type)

Secrets Detection

Frequency: Every scan (full and quick)

What We Look For:

Hardcoded passwords
API keys and tokens
AWS/cloud credentials
Private keys
Database connection strings
OAuth secrets

Tools:

Pattern matching (regex)
Common secret formats
Configuration file scanning

Impact: HIGH severity, immediate fix required

Script Quality

Frequency: Every scan (full and quick)

What We Check:

Executable permissions
Shebang lines present
Error handling (set -e)
Shellcheck validation (if available)

Tools:

Shellcheck
Custom validation scripts
Permission checks

Impact: MEDIUM severity, fix before release

Python Safety

Frequency: Every scan (full and quick)

What We Check:

eval() and exec() calls
shell=True in subprocess
pickle.loads() usage
Unsafe deserialization

Tools:

Pattern matching
AST analysis (future)

Impact: HIGH severity, immediate fix required

Package Documentation

Frequency: Every scan (full and quick)

What We Verify:

README.md exists
Security section in README
LICENSE file present
manifest.yaml valid
CHANGELOG.md exists (recommended)

Tools:

File existence checks
YAML validation
Content validation

Impact: HIGH for missing LICENSE, MEDIUM for others

License Files

Frequency: Every scan (full and quick)

What We Check:

LICENSE in each package
LICENSE not empty
Repository root LICENSE

Tools:

File existence checks
Size validation

Impact: HIGH severity, required for distribution

Dependency Audit

Frequency: Full scans only (weekly, release, post-incident)

What We Check:

npm vulnerabilities
Python package vulnerabilities
Outdated dependencies
Insecure git URLs

Tools:

npm audit
Known vulnerability databases
Version checking

Impact: Varies by severity (HIGH to LOW)

How Results Are Published

For Automated Scans

Location: GitHub Actions Artifacts

Format: JSON + text report

Retention: 90 days

Access:

# Via GitHub CLI
gh run list --workflow=security-scan.yml
gh run view RUN_ID
gh run download RUN_ID

For PR Scans

Location: PR comments

Format: Formatted text with status emojis

Content:

Summary of checks
Failed checks with details
Remediation guidance
Links to documentation

Example:

Security Scan Results

Secrets Detection: PASSED
Script Quality: PASSED
Python Safety: FAILED (2 issues)
   - eval() call in packages/example/script.py:42

Please fix the issues above before merging.

For Release Scans

Location:

GitHub Release notes
CI/CD logs
Archived artifacts

Format:

Summary in release notes
Full report in artifacts

Example Release Note:

## Security

All security scans passed
- 0 secrets detected
- 0 unsafe code patterns
- All documentation current
- All dependencies secure

View full scan results in CI artifacts.

For Weekly Scans

Location:

GitHub Issues (if problems found)
Repository Actions tab
Archived artifacts

Format:

Issue created for new problems
Weekly summary report

Example Issue:

Title: [Security] Weekly Scan Found 2 New Issues

Weekly security scan on 2025-12-04 found:

1. HIGH: New npm vulnerability in lodash < 4.17.12
   - Package: lodash
   - Severity: High
   - Fix: Update to 4.17.12+

2. MEDIUM: Shellcheck warning in scripts/example.sh
   - Line 42: Unquoted variable
   - Fix: Add quotes around $variable

See full report: [link to artifacts]

Scan History and Metrics

Historical Data

Storage: GitHub Actions artifacts and Issues

Tracked Metrics:

Total scans run
Pass/fail rate
Issues found by type
Issues fixed
Mean time to fix

Analysis: Monthly security reports

Example Historical Scan Data

Date	Scan Type	Status	Issues Found
2025-12-04	Release	PASSED	0
2025-12-03	PR	PASSED	2 (LOW)
2025-12-01	Weekly	PASSED	0
2025-11-30	Manual	PASSED	1 (MEDIUM)
2025-11-28	Release	PASSED	0

Trend Analysis

Monitored Trends:

Issue frequency over time
Types of issues most common
Time to fix by severity
Scan pass rate
Dependency vulnerability rate

Goals:

Maintain 95%+ pass rate
< 24 hour fix for critical
< 1 week fix for high
Zero hardcoded secrets
100% documentation coverage

Integration with CI/CD

GitHub Actions Workflow

name: Security Scan

on:
  push:
    branches: [main]
  pull_request:
  schedule:
    - cron: '0 0 * * 0'  # Weekly on Sunday
  release:
    types: [created]

jobs:
  security-scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Run security scan
        run: |
          chmod +x scripts/security-scan.py
          ./scripts/security-scan.py --json > scan-results.json

      - name: Check results
        run: |
          if [ $? -eq 2 ]; then
            echo "Critical security issues found"
            exit 1
          fi

      - name: Upload results
        uses: actions/upload-artifact@v3
        if: always()
        with:
          name: security-scan-results
          path: scan-results.json

      - name: Comment on PR
        if: github.event_name == 'pull_request'
        uses: actions/github-script@v6
        with:
          script: |
            const fs = require('fs');
            const results = JSON.parse(fs.readFileSync('scan-results.json'));
            // Post comment with results

Pre-Commit Hook

#!/bin/bash
# .git/hooks/pre-commit

echo "Running quick security scan..."
./scripts/security-scan.py --quick

if [ $? -ne 0 ]; then
    echo ""
    echo "Security scan failed. Commit aborted."
    echo "Fix the issues above or run with --no-verify to skip (not recommended)"
    exit 1
fi

echo "Security scan passed"

Compliance and Auditing

Audit Trail

All security scans create an audit trail:

Recorded Information:

Scan timestamp
Scan type (full/quick)
Triggering event
Results summary
Issues found
Actions taken

Retention: 90 days in Actions, longer in Issues

Access: Repository maintainers and auditors

Compliance Reports

Frequency: Monthly

Content:

All scans performed
Issues found and resolved
Outstanding issues
Trend analysis
Compliance status

Distribution: Repository security documentation

Future Enhancements

Planned Improvements

Q1 2025:

SAST (Static Application Security Testing) integration
Dependency graph analysis
Automated dependency updates
Enhanced reporting dashboard

Q2 2025:

Container scanning (if Docker used)
Infrastructure as Code scanning
License compliance checking
SBOM generation

Q3 2025:

Security scorecard integration
Continuous monitoring
Threat modeling automation
Security metrics API

Additional Resources

SECURITY.md - Overall security policy
PUBLISHER-VERIFICATION.md - Publisher verification process
Shellcheck Documentation
OWASP Secure Coding Practices

Questions

For questions about security scanning:

Review this guide thoroughly
Check scan output for specific guidance
See SECURITY.md for general security policy
Open GitHub Issue for unresolved questions

FilesExpand file tree

SECURITY-SCANNING-GUIDE.md

Latest commit

History

SECURITY-SCANNING-GUIDE.md

File metadata and controls

Security Scanning Guide

Overview

Purpose

The Security Scanner

Quick Reference

Check Categories

1. Secrets Detection

2. Script Quality

3. Python Safety

4. Package Documentation

5. License Files

6. Dependency Audit

Running Security Scans

Local Development

Continuous Integration

Pre-Commit Hooks

Scheduled Scans

Interpreting Results

Exit Codes

Output Format

Status Indicators

Issue Severity

Troubleshooting

Common Issues

False Positives

Best Practices

For Package Authors

For Reviewers

For CI/CD

Automation Schedule

Scan Types

Full Security Scan

Quick Scan

Scan Schedule

1. On Every Release (Automated)

2. Weekly Scheduled Scans (Automated)

3. On Pull Requests (Automated)

4. Manual On-Demand Scans

5. Post-Incident Scans

What Is Checked (Summary by Scan Type)

Secrets Detection

Script Quality

Python Safety

Package Documentation

License Files

Dependency Audit

How Results Are Published

For Automated Scans

For PR Scans

For Release Scans

For Weekly Scans

Scan History and Metrics

Historical Data

Example Historical Scan Data

Trend Analysis

Integration with CI/CD

GitHub Actions Workflow

Pre-Commit Hook

Compliance and Auditing

Audit Trail

Compliance Reports

Future Enhancements

Planned Improvements

Additional Resources

Questions