Is the OWASP Top 10 for Agentic Applications a replacement for the LLM Top 10?

No. The agentic version covers the threat model specific to multi-step agent behavior. The LLM Top 10 covers the threat model for single-call generative AI use. Most enterprises need both because they run both deployment patterns.

Does a model provider's safety layer cover any of these?

Model safety layers can reduce the probability of harmful output for some classes of prompts. They are probabilistic. The gateway controls above are deterministic and policy-based. The two layers are defense in depth; neither replaces the other.

How do these controls interact with NIST AI RMF?

NIST AI RMF's GOVERN, MAP, MEASURE, MANAGE functions are at the program level. The OWASP categories sit at the technical control level. The gateway audit fields feed evidence into MEASURE and MANAGE.

What is the latency cost of evaluating these controls per request?

Production deployments run the full evaluation under 50 ms. LLM inference takes 500 ms to 5 seconds. The control overhead is invisible relative to the model's response time.

Does the gateway control apply to agent-to-agent traffic over MCP, A2A, or proprietary protocols?

Any agent-to-agent traffic that runs over HTTP can be enforced at the gateway. The gateway terminates the protocol, evaluates the request, and re-establishes the connection. Local-process IPC channels are outside the HTTP enforcement boundary and require a separate control.

Mapping the OWASP Top 10 for Agentic Applications 2026 to Control Points a Policy Gateway Enforces

OWASP GenAI published the Top 10 for Agentic Applications 2026 as a framework distinct from the existing LLM Top 10. The agentic version reorders the threat model around tool invocation, plan corruption, and identity propagation across multi-step decisions. The "agentic skills" intermediate behavior layer is added as a new vulnerable component, sitting between the model and the tools it calls. CISOs and platform leads asking how to justify spend on AI security infrastructure to a board will find the framework useful as a reference because it gives names and categories that align with how engineering organizations already think about the agent stack.

I want to walk through each of the 10 categories, the specific control point a policy gateway at the AI request boundary enforces for that category, and the audit fields the control writes. The mapping below is what an architecture review can hand to a sourcing team as a control inventory.

AAA01: Prompt Injection in the Agent Plan

The agent plan is the model's internal reasoning chain before tool invocation. A prompt injection that corrupts the plan can cause the agent to call tools the operator never authorized.

Gateway control: prompt classification on the request path. Every prompt is parsed for adversarial patterns, role-shift markers, and injected instructions. The classification result is attached to the request as a policy input. Plans that depend on tools tagged sensitive require a clean classification.

Audit fields: prompt_classification, injection_signal_strength, plan_token_sequence_hash.

AAA02: Tool Misuse and Unauthorized Tool Invocation

An agent with permission to call ten tools may chain them in ways the operator never modeled. A read-then-write chain that the human user could not perform directly may be reachable through tool composition.

Gateway control: per-tool authorization at the request layer. Each tool invocation request is evaluated against the agent identity, the user identity the agent acts on behalf of, and the policy that governs the tool. Chained calls inherit the constraints of the most restrictive policy in the chain.

Audit fields: tools_invoked, tool_authorization_decision, delegated_from, chain_root_request_id.

AAA03: Identity Spoofing and Authority Hijacking

The agent acts on behalf of an upstream principal. If the agent's call to a downstream tool does not carry the upstream identity, the downstream tool authorizes against the agent's identity. The agent's standing privileges become the user's effective privileges.

Gateway control: identity propagation enforcement. The gateway requires every agent-to-tool request to carry a verifiable identity assertion for both the agent and the human or upstream agent it acts for. Requests without dual identity are blocked at the boundary.

Audit fields: agent_identity, acts_on_behalf_of, identity_assertion_signature, propagation_check_result.

AAA04: Excessive Agency

An agent with permission to call any tool in its catalog can take actions that exceed the human user's authority. The framework calls this excessive agency. The control point is the per-request scope check.

Gateway control: scope reduction at the request layer. The gateway intersects the agent's policy with the upstream user's policy and the agent session's declared scope. The effective permission set is the intersection, not the union.

Audit fields: agent_policy_scope, user_policy_scope, session_declared_scope, effective_scope_intersection.

AAA05: Data Exfiltration via Tool Output Channels

An agent can read sensitive data from one tool and write it to another tool that exposes it externally. Email-send tools, document-share tools, and webhook tools are the common exfil channels in real incidents.

Gateway control: response classification and egress policy. The response from any tool call is classified before it returns to the agent. Classified data tagged as restricted is bound to a policy that prevents the agent from passing it to egress-capable tools in the same session.

Audit fields: tool_response_classification, egress_policy_decision, restricted_data_propagation_block.

AAA06: Cascading Failure Across Multi-Agent Workflows

A multi-agent workflow shares state across agents. A corruption or compromise in one agent's plan propagates to the others. The framework specifically calls out the case where an attacker compromises a subagent and uses the parent agent's authority to escalate.

Gateway control: per-agent isolation and lineage tracking. Each agent in a workflow has its own policy. The gateway tracks the lineage of every request back to its originating user session. Cross-agent state transfer requires explicit policy authorization, not implicit trust.

Audit fields: agent_lineage_chain, originating_user_session, cross_agent_transfer_decision.

AAA07: Memory Poisoning

Agents that maintain long-term memory across sessions are vulnerable to memory-write injection. An adversarial input writes a false fact into memory; the fact biases all future decisions.

Gateway control: memory-write authorization. Writes to long-term memory are routed through a policy decision point. Writes from low-trust input channels (untrusted users, external tool responses) require additional validation before commit. The gateway can also tag memory entries with their source for downstream trust evaluation.

Audit fields: memory_write_source, memory_write_authorization, memory_entry_tags.

AAA08: Insecure Tool Output Handling

The model treats tool outputs as authoritative input. A tool that returns adversarial content (a poisoned web page, a hostile email body) can drive the model to take unintended actions on subsequent steps.

Gateway control: tool response sanitization and classification on the return path. Responses are classified before they re-enter the model's context window. High-risk responses trigger policy-aware handling: redaction, quarantine, or operator escalation.

Audit fields: tool_response_classification, response_sanitization_action, operator_escalation_event.

AAA09: Plan and Goal Manipulation

The agent's goal is set at session start. A long-running agent can have its goal drift through a sequence of subtle prompts that reshape the objective without crossing the prompt-injection threshold.

Gateway control: goal-state continuity check. The gateway can require the agent's declared goal to be re-attested at policy checkpoints during long sessions. Goal drift beyond a policy threshold triggers session termination or operator review.

Audit fields: session_goal_attestation_chain, goal_drift_metric, checkpoint_decision.

AAA10: Insufficient Logging and Forensic Reconstruction

The framework's final category is the one that ties the others to compliance. An incident that an agent participated in cannot be investigated without a record that spans the prompts, tool calls, identity context, and decisions.

Gateway control: per-decision audit record with tamper-evident write path. Every request and response is recorded with identity, policy version, and decision outcome. Records are signed and written before the response returns to the application.

Audit fields: the union of the above. The point is not which fields; the point is that the gateway is the system of record, not the application.

Example policy rule

A policy rule that combines several of the controls above looks like this in a declarative form:

The rule maps to AAA01, AAA02, AAA04, AAA05, and AAA10 simultaneously. A single inline gateway evaluates the rule per request.

Compliance posture

The OWASP framework operates as a recognized reference for board justification rather than a regulation. Boards asking "how do we know our AI security is adequate?" can be answered with a control inventory mapped to a named framework. The EU AI Act Article 12 logging obligation, the NIST AI RMF MEASURE function, and the ISO 42001 control set all align with the audit fields the gateway produces.

For platform leads, the framework is also a procurement instrument. Vendors should be asked to map their product to each of the 10 categories and to show the audit field set per category. A vendor that cannot produce that map is selling a partial control.

DeepInspect

This is exactly what DeepInspect does. DeepInspect sits inline between agents and the tools and LLM endpoints they call. Each request is evaluated against identity, scope, prompt classification, tool authorization, and organizational policy. The audit record is signed and written before the response returns. The control map above is the literal control inventory the product produces.

If you are mapping the OWASP Top 10 for Agentic Applications to a procurement instrument and want to compare what an inline gateway covers versus what your existing stack covers, book a demo today.