# Making secret scanning more trustworthy: Reducing false positives at scale

> **Platform:** [SPIDITS AI](https://spidits.com/) — Real-Time AI News & Market Intelligence  
> **Published:** 2026-06-11T16:00:00.000Z  
> **Category:** PRODUCT_LAUNCH  
> **Impact Score:** 140/100  
> **Primary Source:** [GitHub Blog](https://github.blog/security/making-secret-scanning-more-trustworthy-reducing-false-positives-at-scale)  
> **Canonical Citation:** [https://spidits.com/timeline/making-secret-scanning-more-trustworthy-reducing-false-positives-at-scale](https://spidits.com/timeline/making-secret-scanning-more-trustworthy-reducing-false-positives-at-scale)

## Executive Summary
Alerts are more trustworthy and actionable when noise is reduced. See how we improved the verification step with context-aware LLM reasoning. The post Making...

## Referenced Coverage & Sources
- **[GitHub Blog](https://github.blog/security/making-secret-scanning-more-trustworthy-reducing-false-positives-at-scale)**: Making secret scanning more trustworthy: Reducing false positives at scale — _Alerts are more trustworthy and actionable when noise is reduced. See how we improved the verification step with context-aware LLM reasoning. The post Making..._

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