Endor Labs launches AURI: free security layer for AI coding agents
Endor Labs launched AURI, a free security intelligence layer for AI coding agents that scans code and dependencies, blocks malware, and helps fix bugs. AURI’s developer-facing Skills plugin, MCP integration, and CLI are now free, embedding guardrails into agentic workflows to catch vulnerabilities, exposed secrets, and malicious packages early in the SDLC ([Endor Labs AURI](https://www.endorlabs.com/learn/introducing-auri-security-intelligence-for-ai-coding-agents-and-developers)). This shifts security left for both humans and AI agents operating across editors and CI. The move comes as teams confront AI-generated “insecure defaults” that slip into code and infra, underscoring the need for default-safe patterns and automated checks ([DevOps.com on insecure defaults](https://devops.com/when-ai-gets-it-wrong-the-insecure-defaults-lurking-in-your-code/)). Practitioners are also arguing for an “agentic firewall” to enforce IAM, data loss prevention, and deterministic guardrails around agent actions ([HackerNoon on agentic firewall](https://hackernoon.com/the-end-of-god-mode-why-enterprise-ai-needs-an-agentic-firewall?source=rss)). On the ops side, AI incidents don’t behave like traditional ITOps events, driving new incident models and autonomous remediation platforms ([The New Stack on AI incidents](https://thenewstack.io/ai-incident-management-evolution/), [Codenotary preview](https://devops.com/codenotary-previews-ai-platform-to-autonomously-detect-and-remediate-it-issues/)) and governance frameworks for AI-era pipelines ([Sonar framework](https://devops.com/sonar-unfurls-framework-for-managing-devops-workflows-in-the-age-of-ai/)).