False alarms can be effectively reduced in three ways:
- Customize scanning rules: create a security-review.md file in the project.claude/commands/ directory, set up ignore rules (e.g., to exclude specific files or code patterns) and priority filters
- Use the allowed_tools parameter to limit the scope of tool execution, e.g. to focus on analyzing git diff results.
- Regularly update the tool version (via the npm update command) to get the latest false positives filtering algorithm
Practice shows that the false alarm rate can be reduced by more than 60% after rule optimization. It is recommended to prioritize the setting of filtering rules for known false alarm patterns.
This answer comes from the articleClaude Code Security Review: a GitHub tool to automate code security vulnerability scanningThe
May not be reproduced without permission:AI productivity tools " How to optimize Claude Code Security Review to reduce false positives interfering with development productivity?
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