SCA Vulnerability Scan Report

Scan Information

• Repository: <repo_path>
• Scan ID: <scan_id>
• Date: <timestamp>
• Scanner: Wraith (OSV-Scanner) + Ghost AI Exploitability Analysis

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Executive Summary

<2-3 paragraphs summarizing:

• Number of lockfiles scanned and total dependencies analyzed
• High severity findings that require immediate action
• Overall security posture (clean, concerning, critical)
• False positive reduction achieved by AI analysis>

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Statistics

Metric	Count
Lockfiles Scanned	<count>
Packages Scanned	<count>
Vulnerabilities Detected	<count> (raw scanner output)
Candidates Analyzed	<count>
Confirmed Findings	<count> (exploitable)
False Positives Filtered	<count>
False Positive Rate	<percentage>%

Findings by Severity

Severity	Count	Recommended Timeline
High	<count>	Within 1 week
Medium	<count>	Within 1 month
Low	<count>	Plan for next quarter

Findings by Ecosystem

Ecosystem	Findings	Total Packages
Go	<count>	<count>
npm	<count>	<count>
PyPI	<count>	<count>
RubyGems	<count>	<count>
Cargo	<count>	<count>

Findings by Lockfile

Lockfile	Findings	Packages	Status
go.mod	<count>	<count>	<clean/vulnerable>
frontend/package-lock.json	<count>	<count>	<clean/vulnerable>
requirements.txt	<count>	<count>	<clean/vulnerable>

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High Severity Findings

<For each HIGH finding:>

<Package Name> @ <Version> - <Vulnerability ID>

• Location: <lockfile-path>
• CVEs: <CVE-IDs>
• CVSS Score: <score>
• Summary: <1-line vulnerability summary>
• Exploitability: <Why this is exploitable in this codebase>
• Impact: <What an attacker could achieve>
• Remediation: Upgrade to <package>@<fixed-version>

Exploit Path:

User Input → <entry point> → <vulnerable function> → <impact>

Detailed Analysis: See [<scan_dir>/findings/<finding-id>.md](<scan_dir>/findings/<finding-id>.md)

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Medium Severity Findings

<For each MEDIUM finding, similar format but may be more condensed>

<Package Name> @ <Version> - <Vulnerability ID>

• Location: <lockfile-path>
• CVEs: <CVE-IDs>
• CVSS Score: <score>
• Summary: <1-line summary>
• Remediation: Upgrade to <package>@<fixed-version>

Detailed Analysis: See [<scan_dir>/findings/<finding-id>.md](<scan_dir>/findings/<finding-id>.md)

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Low Severity Findings

<For LOW findings, use condensed table format>

Package	Version	Vuln ID	CVE	CVSS	Remediation
<package>	<version>	<vuln_id>	<cve>	<score>	Upgrade to <fixed_version>
<package>	<version>	<vuln_id>	<cve>	<score>	Upgrade to <fixed_version>

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False Positives Filtered

The AI analysis successfully filtered <count> false positives that were not exploitable:

Not Used in Codebase (<count>)

• <package>@<version> - <vuln_id>: Package imported but vulnerable function not called
• <package>@<version> - <vuln_id>: Only safe submodules used, vulnerable code not reached
• <package>@<version> - <vuln_id>: Transitive dependency never directly imported

Test Dependencies Only (<count>)

• <package>@<version> - <vuln_id>: Only used in test files (test/), not in production
• <package>@<version> - <vuln_id>: Listed in devDependencies, excluded from production build
• <package>@<version> - <vuln_id>: Test-only usage, not deployed

Mitigated (<count>)

• <package>@<version> - <vuln_id>: Effective input validation wrapper in place
• <package>@<version> - <vuln_id>: WAF rules block exploit attempts
• <package>@<version> - <vuln_id>: Custom fork with backported patch

Version Overrides (<count>)

• <package>@<version> - <vuln_id>: Actually using patched version via replace directive
• <package>@<version> - <vuln_id>: Fixed via package.json resolutions
• <package>@<version> - <vuln_id>: Internal fork with security patches

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Remediation Plan

High Priority Actions (High Severity)

<For each HIGH finding, provide specific upgrade instructions>

1. <Package> @ <Version> - <Vuln ID>

• Action: Upgrade to <package>@<fixed-version>
• Testing Required:
  • <functionality area 1 that uses this package>
  • <functionality area 2>
  • <integration/e2e tests>
• Estimated Effort: <hours/days>
• Command:

# npm npm install <package>@<version> npm audit

# Python (poetry) poetry add <package>@<version> poetry lock

# Python (pip) pip install <package>==<version> pip freeze > requirements.txt

# Ruby bundle update <package>

# Rust cargo update <package>

### Medium Priority Actions (Medium Severity)

<Similar format for MEDIUM findings>

### Low Priority Actions (Low Severity)

<Condensed list or table format>

- **<package>@<version>**: Upgrade to <fixed_version>
- **<package>@<version>**: Upgrade to <fixed_version>

### Long-Term Security Improvements

1. **Automated Dependency Scanning**
   - Integrate wraith into CI/CD pipeline
   - Fail builds on High severity vulnerabilities
   - Run weekly scans on main/production branches
   - Set up automated alerts for new vulnerabilities

2. **Dependency Update Policy**
   - Enable automated dependency updates (Dependabot, Renovate Bot)
   - Establish regular security patch windows (e.g., monthly)
   - Pin major versions, auto-update patches
   - Review and approve dependency additions

3. **Secure Development Practices**
   - Review security track record before adding new dependencies
   - Prefer well-maintained packages with active security response
   - Minimize dependency footprint (fewer dependencies = smaller attack surface)
   - Use Software Bill of Materials (SBOM) for transparency

4. **Runtime Protection**
   - Deploy Web Application Firewall (WAF) for internet-facing services
   - Implement network segmentation for backend services
   - Use input validation middleware
   - Monitor for exploitation attempts in logs

5. **Vulnerability Response Process**
   - Establish SLA for patching by severity (High: 7 days, Medium: 30 days, Low: 90 days)
   - Maintain security contact/team for vulnerability reports
   - Document incident response procedures
   - Conduct post-incident reviews

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## Detailed Findings

For comprehensive exploitability analysis of each finding, see individual finding files:

<scan_dir>/findings/ ├── <finding-1>.md ├── <finding-2>.md └── ...

Each finding includes:
- Detailed exploitability assessment
- Attack vector analysis
- Code context and data flow
- Specific remediation steps
- CVE references and links

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## Methodology

### Phase 1: Vulnerability Detection
- **Tool**: Wraith (wrapper around Google's OSV-Scanner)
- **Database**: OSV (Open Source Vulnerabilities) - 500,000+ vulnerabilities
- **Coverage**: All major ecosystems (Go, npm, PyPI, RubyGems, Cargo, Maven, Packagist)
- **Process**: Scans lockfiles against OSV database for known vulnerabilities

### Phase 2: Exploitability Analysis
Each detected vulnerability was analyzed by an AI agent evaluating:

1. **Usage Analysis**: Is the vulnerable package/function actually used in the codebase?
2. **Data Flow Analysis**: Can user input reach the vulnerable code?
3. **Context Analysis**: Is this production code or test/dev only?
4. **Mitigation Detection**: Are there protective measures in place (wrappers, validation, WAF)?
5. **Severity Adjustment**: Contextual CVSS scoring based on actual exploitability

**Decision Criteria**: A vulnerability is confirmed as exploitable ONLY if:
- The vulnerable function is actually called (not just package imported)
- User input can reach the vulnerable code
- No effective mitigations are in place
- The code is in production (not test-only)

### Phase 3: False Positive Filtering
Common false positive patterns automatically filtered:

- **Not Used**: Vulnerable functions not imported or called
- **Test/Dev Only**: Dependencies not included in production builds
- **Mitigated**: Wrappers, validation, or WAF rules that prevent exploitation
- **Version Overrides**: Patched forks or resolutions despite lockfile version

**Result**: Achieved <percentage>% false positive reduction, providing high-confidence, actionable findings.

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## Appendix: Raw Scan Data

- **Raw Wraith Output**: `<scan_dir>/scan-*.json`
- **Candidates List**: `<scan_dir>/candidates.json`
- **Lockfiles Analyzed**: `<scan_dir>/lockfiles.json`

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