Secrets Scan Report

Scan Information

• Repository: <repo_path>
• Scan ID: <scan_id>
• Date: <timestamp>
• 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	<count>
Candidates Detected	<count>
Confirmed Findings	<count>
False Positives Filtered	<count>

Findings by Severity

Severity	Count
High	<count>
Medium	<count>
Low	<count>

Findings by Secret Type

Secret Type	Count
<type>	<count>

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Findings

High Severity Findings

<For each high finding:>

<Finding Title>

• File: <file_path>
• Line: <line_number>
• Secret Type: <type>
• Description: <brief description>

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Medium Severity Findings

<For each medium finding, brief summary>

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Low Severity Findings

<For each low finding, brief summary>

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Recommendations

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

1. Immediate Actions (for high severity findings)
   • <specific action items>
2. Short-term Improvements
   • <recommendations for preventing future secret exposure>
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: <scan_dir>/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

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?? 所属: ghost-scan-secrets