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Detect source code attacks with Datadog Code Threat Detection

Blog post from Datadog

Post Details
Company
Date Published
Author
Kassen Qian, Daniel Blazquez, Christoph Hamsen
Word Count
764
Language
English
Hacker News Points
-
Summary

Datadog Code Threat Detection is an innovative tool designed to identify and mitigate source code attacks on GitHub pull requests (PRs) by evaluating them for suspicious behaviors such as obfuscated code, dependency abuse, credential exfiltration attempts, and CI/CD workflow tampering. Leveraging AI-assisted analysis, it examines a PR's full diff alongside repository metadata and dependency context, offering visibility into code changes that exploit trusted development workflows. This detection capability extends beyond traditional vulnerability scanning, addressing a critical part of the software supply chain that attackers increasingly target. Integrated with Datadog’s Workflow Automation, Code Threat Detection generates security signals in the Datadog Signals Explorer, allowing security and engineering teams to investigate, escalate, or remediate threats using existing tools and workflows. This approach ensures comprehensive protection from source code attacks before code reaches the production environment, enhancing the security of automated developer workflows and AI coding assistants.