Topic starter
25/10/2026 11:08 am
TL;DR: The OWASP GenAI Security Project’s first Top 10 for Agentic Applications reframes agents as autonomous principals with tools, memory, and authority to act, so the risk surface now includes goal hijack, tool misuse, privilege abuse, supply-chain tampering, and rogue behaviour, according to Jozu. Traditional IAM and DLP controls do not fully cover runtime decisions or lifecycle containment.
Editorial analysis by NHI Mgmt Group, based on content published by Jozu: “The OWASP Top 10 for Agentic Applications 2026: What It Means for Teams Running Agents in Production”.
Key questions
Q: What breaks when AI agents inherit loose human authority?
A: Loose human authority turns agent security into an amplification problem.
Q: Why do agentic applications need more than prompt filtering?
A: Prompt filtering only addresses one attack path, but agentic risk also includes supply-chain tampering, over-privileged tools, memory poisoning, and rogue runtime behaviour.
Q: How should teams handle approvals for high-risk agent actions?
A: Treat approval as part of the authorisation decision for one specific action, not as a reusable privilege.
Practitioner guidance
- Map each agent to a named authority boundary Document which tools, data sets, execution environments, and delegated identities each agent can reach, then remove anything that is not required for the task.
- Separate tool approval from model permission Treat tool invocation as its own control point, with per-tool and per-action authorization instead of broad access inherited from the host application.
- Verify every agentic artifact before it reaches runtime Require signature, provenance, and security checks for models, MCP servers, agent definitions, and skills before they are allowed into production.
Bottom line: Agentic applications create a governance problem that starts with delegated authority and ends with blast-radius control, not with prompt quality alone.
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