Secrets Scan Report

Scan Information

Repository:

Scan ID:

Date:

Scanner: Poltergeist + Ghost AI Analysis

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Executive Summary

<1-2 paragraph summary of the scan results, highlighting the most critical findings and overall security posture>

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Statistics

| Metric | Count | |--------|-------| | Files Scanned | | | Candidates Detected | | | Confirmed Findings | | | False Positives Filtered | |

Findings by Severity

| Severity | Count | |----------|-------| | High | | | Medium | | | Low | |

Findings by Secret Type

| Secret Type | Count | |-------------|-------| | | |

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Findings

High Severity Findings

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File: ``

Line:

Secret Type:

Description:

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Medium Severity Findings

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Low Severity Findings

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Recommendations

Based on the scan results, we recommend the following actions:

1. Immediate Actions (for high severity findings) -

2. Short-term Improvements -

3. Long-term Security Practices - Implement pre-commit hooks to prevent secret commits - Use a secrets manager for all credentials - Regular security scanning in CI/CD pipeline

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Finding Details

For detailed information about each finding, see the individual finding files in: `/findings/`

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Methodology

This scan was performed using: 1. Poltergeist Scanner: Fast regex-based secret detection with 100+ built-in rules 2. AI Analysis: Each candidate was analyzed by an AI agent to filter false positives 3. Context Evaluation: Candidates in test code or using environment variables were filtered

Analysis Criteria

Real secret vs placeholder detection

Hardcoded vs environment-loaded values

Production vs test code paths

Evidence of exposure in version control

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*Report generated by Ghost Security Secrets Scanner*