ASI01-ASI10: Breaking Down Every Agentic Security Risk

Released in December 2025, the OWASP Top 10 for Agentic Applications proposes a security taxonomy for autonomous AI systems, emphasizing risks that extend beyond conventional LLM threats, including persistent-memory poisoning, unmonitored tool execution, sensitive-data exposure, weak authentication, audit deficiencies, shadow AI, configuration sprawl, insufficient real-time monitoring, insecure data integrations, third-party supply-chain vulnerabilities, and inadequate production infrastructure. It describes agentic systems as especially challenging because they can act autonomously, retain information across sessions, access files and APIs, and coordinate with other agents, potentially allowing failures or compromises to propagate quickly. The framework recommends prioritizing agents according to autonomy, data sensitivity, tool privileges, and user reach, while applying controls such as least-privilege access, per-user authentication, memory isolation, input validation, comprehensive immutable logging, inventory management, vulnerability scanning, and continuous behavioral monitoring. The text presents MintMCP’s MCP Gateway and LLM Proxy as an integrated governance and security solution intended to centralize agent management, enforce guardrails, monitor tool and file access, support compliance reporting, and help organizations move experimental or unsanctioned AI deployments into managed enterprise environments.

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