<ul><li>API tokens are at risk of exposure through application logs, browser consoles, source code repositories, and error monitoring tools.</li><li>Building a real-time API token leak detection and response system involves scanning log streams, detecting tokens using regex and ML scoring, sending alerts, auto-revoking leaked tokens, maintaining a dashboard, and sending events to various platforms.</li><li>The system can be integrated with Slack, Microsoft Teams, SIEM platforms, and other tools for monitoring and responding to token leaks promptly.</li><li>Implementing this system using Python can enhance security practices and help in safeguarding organizations against financial and reputational damage from data leaks.</li></ul>

Building a Real-Time API Token Leak Detection and Response System Using Python

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