Traditional application security protects the software and services an AI agent runs on; agent runtime security constrains what the agent can access, decide, and do while it is operating. They are complementary layers, not alternatives: an agent still needs secure code, APIs, identity, and data handling, while runtime controls address its tools, instructions, context, delegated permissions, and actions across a workflow.
What does traditional application security protect?
Traditional application security focuses on the application itself: its code, web endpoints, data, dependencies, configuration, and supporting services. It asks whether software handles inputs, identity, data, and interfaces safely, and whether a weakness in those areas could be exploited.
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OWASP describes its Top 10 as an awareness document for developers and web application security. The project page identifies the 2025 edition as the latest released version. It is a useful risk-awareness baseline, not a complete security program.
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For an AI agent, these controls still matter. The agent may be delivered through a web application, call an API, retrieve data from a service, or rely on third-party components. A weakness in any of those parts can expose the system or the information it handles, regardless of whether an AI model is involved.
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What does AI agent runtime security protect?
Agent runtime security focuses on the agent’s behavior and authority while it is running. An agent can interpret instructions and context, choose tools, use an identity with particular permissions, and take actions that affect other systems. Runtime security seeks to limit unsafe behavior at those decision and action points, including when the agent is manipulated or makes a poor choice.
That scope extends beyond the prompt. Relevant boundaries include what tools and data the agent can reach, what identity it uses, what actions it may take without approval, what context or memory it receives, and what activity is recorded. OWASP’s 2026 Agentic Applications Top 10, dated December 9, 2025, addresses systems that plan, act, and make decisions across workflows. Its landing page says the framework was developed with more than 100 industry experts, researchers, and practitioners; that figure describes contributors, not how frequently agent attacks occur.
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OWASP’s September 2026 announcement describes its Agent Control Standard as extending agentic risk, identity, governance, and testing guidance toward practical runtime enforcement. The framing is that controls should constrain what systems can access, decide, and do—not rely on the assumption that an AI will never fail or be fooled. Read the announcement.
How do the two security layers differ?
| Comparison | Traditional application security | AI agent runtime security |
|---|---|---|
| Primary focus | Application code, web endpoints, data, dependencies, and supporting services. | Agent behavior, instructions or goals, tools, context or memory, delegated identity, and workflow actions. |
| Typical failure path | An attacker exploits a weakness in code, configuration, identity, data handling, or a dependency. | An agent is manipulated or over-authorized, misuses a tool, exposes context, or propagates an unsafe action. |
| Where controls operate | During secure design and development, and in application and infrastructure safeguards. | At runtime, by constraining tool and data access, requiring authorization for sensitive actions, and recording activity. |
| Shared concerns | Authentication, authorization, least privilege, dependency security, data protection, monitoring, and testing remain important in both layers. Agent systems need these controls along with explicit treatment of tools, identity, context, and action chains. | |
This comparison is a practical synthesis of OWASP’s application, LLM, agentic, MCP, and runtime guidance; it is not a verbatim OWASP taxonomy. See the web application Top 10, 2026 LLM Applications guide, 2026 Agentic Applications Top 10, and MCP Top 10.
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Where do the threats overlap?
The boundary is not clean. An agent can call an ordinary application or API, so weaknesses in authentication, authorization, input handling, dependencies, or logging can become part of an agent attack path. At the same time, a conventional application control may not fully capture the agent’s changing tool choices, instruction hierarchy, or ability to chain actions over a workflow.
A software weakness can expose a system the agent uses
A flaw in an application or service may expose data or functionality. If an agent can reach that service, its integration does not make the underlying weakness disappear; application controls must still protect the endpoint and the data behind it.
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A legitimate tool can still be misused
An agent may have valid credentials and still possess more authority than its task requires. Hostile instructions or retrieved context can steer it toward using a legitimate tool in an unsafe way. Review the agent’s identity and permissions as well as the tool’s own authentication and authorization.
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OWASP’s MCP Top 10 covers risks in MCP-enabled systems, including token and secret exposure, privilege scope creep, tool poisoning, supply-chain attacks, command execution, prompt injection, insufficient authentication and authorization, missing audit telemetry, shadow servers, and context over-sharing. OWASP labels this resource a beta version in a pilot-feedback phase, so treat it as an evolving guide rather than a settled standard.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you apply both layers to an agent?
- Secure the application and its integrations. Apply ordinary secure development and application controls to the agent’s interface, APIs, services, data stores, dependencies, and configuration. Identify which systems the agent can call and protect their endpoints.
- Map the agent’s authority. Inventory its tools, data sources, identities, and workflow connections. For each, record what it can read, change, send, or execute, and reduce permissions to what its task needs.
- Put boundaries at consequential actions. Define which actions the agent may take automatically and which need authorization. Enforce those rules where the action occurs, rather than assuming a prompt filter alone will keep the agent within bounds.
- Protect context and secrets. Review what instructions, retrieved material, memory, tokens, and credentials the agent can access or pass between tools. Limit unnecessary exposure and consider how untrusted context could influence a decision.
- Test realistic attack paths and monitor activity. Test both conventional application weaknesses and agent-specific scenarios, such as manipulated instructions, tool misuse, overbroad identity, and unsafe action chains. Record tool use and consequential actions so teams can investigate unexpected behavior.
Which OWASP guidance is relevant?
These resources cover connected but distinct parts of the problem; they should not be treated as interchangeable standards.
Quick Recap
- Web application risks: OWASP’s Top 10 is a general awareness baseline for web application security. The landing page identifies 2025 as its latest released edition.
- LLM-powered application risks: The OWASP GenAI LLM Top 10 2026 covers risks to LLM-powered applications and includes attack scenarios, mitigations, updated rankings, and mappings to NIST, MITRE ATLAS, CWE, and the Agentic Applications Top 10. OWASP’s September 2026 announcement says the guide drew contributions from hundreds of AI security experts and research informed by thousands of real-world AI security incidents. Those counts describe the guide’s development and input; they are not estimates of attack frequency or incident rates. Announcement details.
- Agentic system risks: The 2026 Agentic Applications Top 10 focuses on autonomous and agentic systems that plan, act, and make decisions across workflows.
- MCP-specific risks: The MCP Top 10 addresses MCP-enabled systems and is currently described on its project page as beta and in a pilot-feedback phase.
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