AGENTS.md files help Codex and similar AI tools understand project-specific instructions, coding conventions, and organizational structures. They can reside anywhere within a Codex container, providing valuable context to AI agents. Like other project configuration files, these instructions are treated as trusted context by the agent. This trust model is by design, but it creates an interesting attack surface when a malicious dependency is able to write or modify these files at build time.
Mitigating Indirect AGENTS.md Injection Attacks in Agentic Environments | NVIDIA Technical BlogThis attack path highlights important considerations for the future of agent-assisted development. Extended supply chain risk: Traditional supply chain attacks focus on injecting malicious code directly. In agentic environments, a compromised dependency can also redirect the agent itself, extending familiar supply chain risks into a new dimension, such as injecting subtle delays that cause performance degradation or denial-of-service scenarios. Instruction following under adversarial conditions: When the agent followed injected configuration directives, including instructions to conceal its
Mitigating Indirect AGENTS.md Injection Attacks in Agentic Environments | NVIDIA Technical Blog…NVIDIA NemoClaw installs OpenClaw agents inside an NVIDIA OpenShell sandboxed environment with a privacy router, ensuring that sensitive recordings remain secure, while Nemotron 3 Nano Omni-powered sub-agents complete specialized tasks…
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…6 MIN READ ] Build AI Agents See all See all Apr 17, 2026 Build a More Secure, Always-On Local AI Agent with OpenClaw and NVIDIA NemoClaw Agents are evolving from question…
…6 MIN READ ] Build AI Agents See all See all Apr 17, 2026 Build a More Secure, Always-On Local AI Agent with OpenClaw and NVIDIA NemoClaw Agents are evolving from question…
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