Navigating Security Tradeoffs for Enterprise AI Agents
🔒 Unit 42 examines the security tradeoffs of agentic AI, spotlighting the early 2026 Clawdbot surge and pervasive vulnerabilities such as exposed gateways, plaintext credentials, and overbroad permissions. The piece identifies two primary threat paths: malicious model files and compromised Model Context Protocol (MCP) servers, and explains how compromised agents can act as powerful insider threats. Practical guidance includes scanning and sandboxing models, preferring trusted remote MCPs or auditing local MCP code, enforcing strict least-privilege tool access, implementing prompt-injection guardrails, and maintaining detailed logging and policy reviews.
