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The OWASP Top 10 for Agentic Applications is a 2026 risk framework, not a certification or a sign-off policy. To assess an agent, document its architecture, autonomy, tools and identities, prompts, memory, communications, risks, and human oversight. OWASP does not name a universal approver; a practical local model is for the accountable system or business owner to accept residual risk, with security reviewing the technical assessment.
What is the OWASP Top 10 for Agentic Applications?
OWASP describes its 2026 edition as a globally peer-reviewed framework for identifying critical security risks in autonomous and agentic AI systems. The OWASP resource page is dated December 9, 2025. OWASP says more than 100 experts, researchers, and practitioners contributed; that is a contributor count, not a measure of the framework’s effectiveness.
Use the Top 10 as a risk taxonomy and a starting point for identifying and mitigating security issues. It is not a certification, compliance attestation, or guarantee that a particular agent is secure. OWASP’s broader project also includes governance and practical security guidance, threat-and-mitigation material, and a reference application. Those resources complement the Top 10 but are not the same document.
What should you document in an agentic AI risk assessment?
The OWASP Secure Agent Playbook identifies assessment inputs and asks teams to map architecture, agent type, autonomy, tools, memory, communication, and oversight. The following checklist turns those prompts into an assessment record. Some fields—such as risk owners, evidence, and remediation—are useful local recordkeeping choices; the Playbook does not prescribe one universal report template.
#1 Best Overall
| Record area | What to capture | Useful evidence |
|---|---|---|
| System and agent inventory | System name, purpose, accountable owners, affected workflows, and whether the design uses a single agent, multiple agents, or a cluster. | Architecture documentation or relevant source code; identify the components and workflows in scope. |
| Autonomy and boundaries | Whether the agent acts autonomously, uses human-in-the-loop review, or is gated by approval; the actions it can take; and where approvals could be bypassed. | Workflow diagrams, configured approval gates, and the actions available at each stage. |
| Tools and access | Tool definitions; MCP or A2A configurations where used; permissions; service identities; credential scope; and which actions are read-only or write-capable. | Tool and integration configuration, permission definitions, and identity or credential settings. |
| Prompts and instructions | System prompts, agent instructions, and relevant sources of untrusted content that could influence behavior. | The applicable prompts and instructions, plus a description of how external or user-provided content enters the workflow. |
| Memory and state | Memory configuration, including vector databases or conversation history where applicable, and how state is persisted or shared. | Memory-system settings and the data flow for stored or shared state. |
| Communications and delegation | Inter-agent communication protocols and which agents or services can delegate work. | Communication and delegation configuration, including the agents or services involved. |
| Risk findings and evidence | For each applicable risk: affected component, scenario, existing controls, supporting evidence, gaps, an owner, and proposed remediation. | Link each finding in the record to the relevant configuration, workflow, or other supporting material your organization retains. |
| Oversight and approvals | Where human review occurs, what the reviewer sees, which actions require approval, how approvals are logged, and how emergency stop or revocation works if relevant. | Human oversight and approval workflows, including the records produced by the approval process. |
The Playbook explicitly names architecture documentation or source code; system prompts and instructions; tool definitions and MCP/A2A configurations; memory configuration; inter-agent communication protocols; and human oversight and approval workflows among its assessment inputs. Keep the record tied to the system actually being assessed: an integration, memory store, delegation path, or write-capable action should not disappear behind a high-level system description.
Which OWASP risk examples should the assessment consider?
OWASP’s announcement gives Agent Behavior Hijacking, Tool Misuse and Exploitation, and Identity and Privilege Abuse as examples. OWASP DevSecOps guidance names these categories and others with identifiers, including Agent Goal Hijack (ASI01), Tool Misuse and Exploitation (ASI02), Identity and Privilege Abuse (ASI03), Agentic Supply Chain Vulnerabilities (ASI04), Unexpected Code Execution (ASI05), and Human-Agent Trust Exploitation (ASI09). These point to scenarios such as manipulated goals, unsafe tool use, excessive or stolen authority, compromised components, unintended code execution, and misplaced trust in an agent’s account of its actions.
The names above come from OWASP’s announcement and DevSecOps guidance; do not treat this as the complete ordered Top 10. Consult the downloadable official framework for the full list before using all ten categories in a formal mapping.
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OWASP DevSecOps guidance recommends implementation practices that can be mapped to the system’s actual architecture. For example, give an agent its own identity—such as a service account, GitHub App, or bot user—instead of reusing a person’s credentials. That makes activity attributable and allows the agent’s access to be revoked independently.
Rank #3
- Use scoped, short-lived tokens and keep agents out of administrative roles.
- Separate read-only identities from identities that can make changes.
- Start tool permissions from deny and add explicit allow rules for required actions.
- Record the relevant identity, permission, token, and tool configuration as evidence for the assessment.
Permission prompts alone are not a security boundary against a manipulated agent. Treat these practices as implementation evidence and guidance, not as fields or controls that the Top 10 itself mandates in every system.
Who should approve an AI agent security assessment?
The reviewed OWASP assessment guidance includes human oversight and approval workflows as inputs, but it does not specify a universal signer or require a particular job title. It does not establish that a CISO, developer, product owner, or board member must sign.
A useful local governance arrangement is for the accountable system or business owner to accept the residual risk and operational use, while security reviews the technical findings and controls. Include privacy, legal, compliance, safety, or model-risk owners when the system’s data, deployment, or impact makes their review relevant. This is a governance recommendation, not an OWASP-mandated approval model.
Record the approver’s role, decision, date, assessment scope, unresolved risks, any conditions on use, and the next review trigger. The approval should make clear which system and workflow were assessed, rather than appearing to cover agent deployments or capabilities outside that scope.
Best Value
How should teams compare agent architectures?
Compare the design dimensions that affect exposure and control, rather than treating the Top 10 as a vendor ranking. OWASP’s architecture-mapping prompts and control guidance support examining:
- How much autonomy the agent has and which actions it can take.
- How broad its tool access is and whether tools can write or only read.
- Which identity and credential scopes it uses.
- How much untrusted content can influence its behavior.
- Whether memory persists or is shared across interactions or agents.
- How agents communicate and delegate work.
- Where human approvals occur, what reviewers can see, and whether a path can bypass approval.
These comparisons help explain why two systems using similar models may present different risks: their access, state, delegation, and approval boundaries can differ substantially.
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