Detect sensitive data leakage in OpenClaw logs using Python.
npx skills add https://github.com/cq2000419/privacy-guard --skill privacy-guard-cq2000419
Please help me install this Agent Skill. Skill: Privacy Guard - 敏感信息外泄检测 Source: https://github.com/cq2000419/privacy-guard/tree/main Command: npx skills add https://github.com/cq2000419/privacy-guard --skill privacy-guard-cq2000419
This Skill automates the detection of sensitive information leakage in OpenClaw logs, helping to identify potential security risks and maintain data privacy.
Use the 'scan' command to initiate a scan of OpenClaw logs.
High-intent search queries and answers about installing and using this skill.
You can automate sensitive data leakage detection in OpenClaw logs by using the scan command, which evaluates log entries against critical, high, and suspicious data patterns to identify potential security risks.
The three-level detection mechanism categorizes potential sensitive information leaks into CRITICAL, HIGH, and suspicious data patterns, allowing you to prioritize security risks based on their severity level.
Yes, smart error tolerance prevents false alarms during log analysis by automatically filtering out common non-sensitive patterns such as timestamps, UUIDs, and JSON data from the detection results.
Yes, you need Python and its associated libraries installed in your environment to execute the automated detection scripts and handle OpenClaw log file processing for sensitive data.
Interactive learning improves detection accuracy by allowing you to manually confirm whether flagged items are safe or risky, enabling the system to auto-evolve its detection patterns based on your feedback.
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