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Project Glasswing: Evaluating LLMs for Infrastructure Security

Project Glasswing: Evaluating LLMs for Infrastructure Security
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๐Ÿ›ก๏ธRead original on Cloudflare Blog

๐Ÿ’กLearn how Cloudflare stress-tested security LLMs on live production code to identify real-world deployment risks.

โšก 30-Second TL;DR

What Changed

Deployed Mythos and other security LLMs directly into live production infrastructure codebases.

Why It Matters

This research provides a blueprint for security teams looking to integrate LLMs into CI/CD pipelines. It highlights the necessity of rigorous real-world testing over synthetic benchmarks for infrastructure security.

What To Do Next

Review the Cloudflare report to identify the specific failure modes of LLMs in code analysis before deploying your own security agents.

Who should care:Developers & AI Engineers

Key Points

  • โ€ขDeployed Mythos and other security LLMs directly into live production infrastructure codebases.
  • โ€ขEvaluated model efficacy in identifying security vulnerabilities within complex, large-scale systems.
  • โ€ขIdentified critical gaps in model performance that must be addressed before scaling security automation.
  • โ€ขProvided a framework for testing LLM reliability in high-stakes infrastructure environments.
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Original source: Cloudflare Blog โ†—