AI Governance / Compliance

OWASP Top 10 for LLM Applications 2026: Complete Checklist

This guide organizes the risk domains addressed by OWASP's Top 10 for LLM Applications framework into a practical checklist for governance teams: risk definition, exposure indicators, and the runtime controls that mitigate each domain. Because the framework's exact category wording changes across releases, confirm the current published text before finalizing a formal compliance mapping. The checklist focuses on what can be implemented now: agent identity, permissions, policy enforcement, tool-call governance, and audit logging.

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LLM Risk Domains This Checklist Addresses

This summary keeps the risk areas visible before the deeper article discussion, with emphasis on runtime governance controls that can be implemented around LLM and agentic systems.

Prompt & Input Manipulation

Adversarial or malicious inputs intended to override system instructions or safety constraints.

Output & Data Exposure

Sensitive data surfacing in generated output, context, or logs beyond authorized retention.

Agentic & Tool-Call Overreach

Autonomous agents invoking tools or other agents beyond their intended scope.

Supply Chain & Model Integrity

Risk introduced by third-party models, plugins, or MCP servers in production.

Operational Resilience

Gaps in monitoring, incident response, and audit evidence for production LLM systems.

Practical Runtime Control Mapping

The following table translates the article's governance themes into a compact checklist. It does not replace the OWASP framework text, but helps teams connect risk domains to the controls discussed in this guide.

Risk domain Exposure indicator Runtime control emphasis
Prompt & Input Manipulation Inputs attempt to override system instructions, safety constraints, or intended model behavior. Evaluate proposed actions at runtime with policy enforcement, rather than relying only on model instructions to self-limit behavior.
Output & Data Exposure Sensitive information appears in generated output, context, or logs beyond authorized retention. Use permissions, policy constraints, and audit logging to support review of what was accessed, generated, and retained.
Agentic & Tool-Call Overreach An agent invokes tools, APIs, or other agents beyond its intended scope. Assign non-human agent identity, enforce least-privilege permissions, and use approval workflows for higher-risk actions.
Supply Chain & Model Integrity Third-party models, plugins, tools, or MCP servers introduce risk into production systems. Maintain an inventory of agents, tools, and models, and treat each tool or MCP connection as a distinct trust boundary.
Operational Resilience Monitoring, incident response, or compliance evidence is incomplete for production LLM systems. Capture policy enforcement decisions and tool-call logs as standard audit evidence, then review the mapping on a fixed cadence.

Understanding the OWASP LLM Risk Framework in an Enterprise Context

OWASP's Top 10 for LLM Applications is a risk categorization framework maintained by the OWASP GenAI Security community and revised periodically as deployment patterns evolve. Earlier revisions focused primarily on single-turn chat applications. More recent industry discussion has centered on agentic systems that call tools, invoke other agents, and operate with greater autonomy than a conversational assistant.

Because the framework's exact category names, numbering, and definitions change between releases, this guide does not restate any specific revision's wording as final. Instead, it organizes the risk domains that recur across releases into a practical checklist governance teams can apply today, noting where the 2026 discussion has shifted emphasis toward agent identity, tool-call governance, and integration protocols such as MCP. Before finalizing a compliance mapping, confirm the exact category text against the current published OWASP document and record that version alongside your internal risk register. Enterprise security and governance teams frequently lack a structured way to connect these categories to concrete runtime controls, which leads to inconsistent implementation across production LLM and agentic deployments and gaps that are difficult to detect until an incident occurs.

Why Standard Application Security Controls Fall Short

Traditional application security controls, including web application firewalls, static code analysis, and role-based access control enforced at the application layer, assume a fixed set of code paths and a stable trust boundary. LLM and agentic systems break both assumptions. The sequence of actions an agent takes is generated at inference time based on model output, which means it cannot be fully enumerated in advance through static review alone.

Access control decisions increasingly need to be made at the point of tool invocation or agent action, not only at the perimeter of the application. Conventional controls also have limited visibility into why a model or agent produced a particular output or decision, which makes it difficult to reconstruct an audit trail using standard application logs alone. Closing this gap requires controls that operate at the model, agent, and tool-call layer, in addition to existing application security measures, rather than as a replacement for them.

Runtime Controls That Address LLM and Agentic Risk

Mapping OWASP-style risk domains to concrete controls generally involves five categories of runtime capability. Identity establishes a verifiable, non-human identity for each agent and automated process, separate from the human user who initiated a session. Permissions define what that identity is authorized to do, scoped to least privilege rather than inherited broadly from the application. Policy enforcement applies rules at runtime, evaluating a proposed action or tool call against defined constraints before it executes, rather than relying solely on model instructions to self-limit behavior. Tool-call governance extends this enforcement to the point where an agent invokes an external tool, API, or another agent, including approval workflows for higher-risk actions. Audit logging records these decisions in a form that can support incident review and compliance evidence requests. Trussed AI's runtime governance capabilities address these areas, including agent identity, agent permissions, tool approval workflows, MCP security, and audit logging, as a control layer that operates alongside existing application security tooling rather than replacing it.

Building Audit-Ready Governance Evidence

  • Assign clear ownership for each risk domain across security, platform, and application teams.
  • Maintain a current inventory of agents, tools, and models in production, each with an owner and risk classification.
  • Record the OWASP framework version and category mapping used for each compliance review cycle.
  • Capture policy enforcement decisions and tool-call logs as standard audit evidence, not as an ad hoc addition.
  • Review the risk mapping on a fixed cadence, since agentic capabilities and integrations change frequently.

Where Agentic Systems and Tool Protocols Change the Risk Picture

Recent industry discussion around LLM application security has increasingly focused on agentic deployments, where a model can plan multi-step tasks, call external tools, and coordinate with other agents with limited human review of each step. This shifts risk from what a model generates in a single response to what actions it initiates across a workflow, including calls made through protocols like MCP that connect agents to external tools and data sources. Governance teams evaluating exposure should treat each tool or MCP connection as a distinct trust boundary requiring its own permission scope and approval logic, rather than assuming application-level authentication is sufficient. This is an area where the risk categorization in the framework continues to evolve, and teams should expect their control mapping to require periodic updates as agentic architectures mature.

Exposure Assessment Checklist by Risk Domain

  • Confirm the current published OWASP framework text before finalizing a formal compliance mapping.
  • Record the framework version used alongside the internal risk register.
  • Identify each production agent, tool, model, plugin, and MCP connection with an owner and risk classification.
  • Define least-privilege permissions for each agent identity and automated process.
  • Evaluate proposed tool calls and agent actions against runtime policy before execution.
  • Apply approval workflows for higher-risk tool invocations and agent actions.
  • Capture policy enforcement decisions and tool-call logs as standard audit evidence.
  • Review the risk mapping on a fixed cadence as agentic capabilities and integrations change.

Assess Your LLM Risk Coverage

Runtime governance controls for agent identity, permissions, tool-call approval, and audit logging can be mapped directly to this checklist.

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