Each OWASP agentic threat maps to a control you can test

The OWASP Top 10 for Agentic Applications names ten risks. Each one maps to controls a team can put in place and test today.
Published

October 16, 2026

Last checked

October 16, 2026

Reading time

4 min

Security teams judge any agent platform against the threat lists they already use. For agents, the list is the OWASP Top 10 for Agentic Applications, published in December 2025, which names ten risks specific to AI agents.1 Every one of the ten maps to controls a team can put in place and test now.

Every risk on the list has a control

The table maps each risk to the controls that address it in an AI control plane.

Ten agentic risks from OWASP, with the controls that address each in the author’s mapping1
Agentic risk What it looks like Controls
ASI01 Agent Goal Hijack Hidden instructions in content, documents or tool results redirect the agent’s goal Input and tool-result screening at the gateway
Allow-listed tools per agent
Approvals bound to the exact action
ASI02 Tool Misuse A legitimate tool is used in a harmful way Per-agent tool allow-lists
Schema validation
Rate, spend and exposure limits
ASI03 Identity & Privilege Abuse Leaked or inherited credentials let an agent act beyond its scope One identity per agent
Short-lived, task-scoped tokens
Delegation that narrows
Real-time revocation
ASI04 Agentic Supply Chain Vulnerabilities Poisoned tools, MCP servers, plugins or models enter at runtime Only registered, signed and version-pinned MCP servers are callable
A private registry of trusted servers
An agent bill of materials2
ASI05 Unexpected Code Execution Natural-language paths trigger code or commands Sandboxed execution
Code and shell tools only at an explicit tier
Limits on outbound connections
ASI06 Memory & Context Poisoning Poisoned memory or context shapes later decisions Context only from governed sources (master data, catalog, lineage)
Provenance checks
Session integrity monitoring
ASI07 Insecure Inter-Agent Communication Spoofed or altered messages between agents Signed agent cards
Mutual authentication
A2A traffic through the gateway
No privilege from self-asserted roles
ASI08 Cascading Failures Errors spread through automated pipelines Circuit breakers
Cumulative exposure limits across agents and sessions
Propose-only on stale data
ASI09 Human-Agent Trust Exploitation Confident, polished output leads people to approve harmful actions Approvals bound to the exact action and showing the facts behind it
Approver drills
Limits that guard against consent fatigue
ASI10 Rogue Agents Agents act outside their mandate or hide what they do Registry and scanners
Honeytokens and decoy tools
Behavioral monitoring
The kill switch

Several controls appear in more than one row, and they are the place to start. Approvals bound to the exact action defend against goal hijack and against people trusting a confident draft. One identity per agent, with delegation that narrows at each hop, closes off privilege abuse and limits what a spoofed message between agents can do. Exposure limits that add up across agents and sessions contain both tool misuse and cascading failures.

The threat lists keep growing. Microsoft’s AI Red Team added seven agentic failure modes to its taxonomy in June 2026, among them agentic supply chain compromise, inter-agent trust escalation, session context contamination and MCP and plugin abuse.3 MITRE ATLAS has added agent-specific techniques since December 2025, such as AI Agent Tool Credential Harvesting and Publish Poisoned AI Agent Tool.4 Tagging red-team scenarios with these names lets a team’s results map to the vocabulary other teams use.

What to do next

  1. Developer. Allow-list the tools each agent may call, validate every call against the tool’s schema, and accept only registered, signed and version-pinned MCP servers.
  2. AI Engineer. Bind each approval to the exact action and show the approver the facts behind it, so a polished draft can’t carry a harmful change through.
  3. CISO. Name an owner for what enters the agent registry and another for what approvers are shown, because no gateway closes either risk alone, and tag red-team scenarios with the risk names in the table.

Go deeper

Section 5 of The AI Control Plane Handbook covers identity for agents, runtime controls, cryptography and human takeover after the kill switch. Slide 17 of the executive deck puts the ten risks and their controls on one page.

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Read the full handbook and the executive deck online.

Endnotes

1.
OWASP GenAI Security Project, “OWASP Top 10 for Agentic Applications: The benchmark for agentic security in the age of autonomous AI,” December 9, 2025. https://genai.owasp.org/2025/12/09/owasp-top-10-for-agentic-applications-the-benchmark-for-agentic-security-in-the-age-of-autonomous-ai/
2.
Tom Martin, Daniel Sack, Djon Kleine, Niels Degrande, and Nicolas de Bellefonds, “Put AI agents to work faster using MCP,” Boston Consulting Group, August 1, 2025. https://web-assets.bcg.com/pdf-src/prod-live/put-ai-to-work-faster-using-model-context-protocol.pdf
3.
Microsoft AI Red Team, “Updating the taxonomy of failure modes in agentic AI systems: What a year of red teaming taught us,” Microsoft Security Blog, June 4, 2026. https://www.microsoft.com/en-us/security/blog/2026/06/04/updating-taxonomy-failure-modes-agentic-ai-systems-year-red-teaming-taught-us/
4.
MITRE, ATLAS data release notes (CHANGELOG), versions 5.2.0 (December 24, 2025) to 2026.06 (June 30, 2026). https://github.com/mitre-atlas/atlas-data/blob/main/CHANGELOG.md

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