Type: url

Original: https://github.blog/ai-and-ml/github-copilot/how-githubs-agentic-security-principles-make-our-ai-agents-as-secure-as-possible/

Status: generated

Summary

GitHub’s account of the security guidelines behind its hosted AI agents, written from the premise that the more agentic a product is the greater the chance and impact of it going off its guardrails, losing alignment or being manipulated. It names three risk classes — data exfiltration, impersonation and action attribution, and prompt injection — and six rules applied across GitHub’s hosted agentic products: make all context visible and strip hidden Unicode or HTML directives; firewall the agent’s network access; withhold sensitive information such as CI secrets and revoke tokens after a session; prevent irreversible state changes without a human in the loop; attribute actions to both initiator and agent; and gather context only from users with write access.

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