Agentic AI is moving fast from pilots to production. That shift changes the security conversation. These systems do not just generate content. They can retrieve sensitive data, invoke tools, and take action using real identities and permissions. When something goes wrong, the failure is not limited to a single response. It can become an automated sequence of access, execution, and downstream impact.
Security teams are already familiar with application risk, identity risk, and data risk. Agentic systems collapse those domains into one operating model. Autonomy introduces a new problem: a system can be “working as designed” while still taking steps that a human would be unlikely to approve, because the boundaries were unclear, permissions were too broad, or tool use was not tightly governed.
The OWASP Top 10 for Agentic Applications (2026) outlines the top ten risks associated with autonomous systems that can act across workflows using real identities, data access, and tools.
This blog is designed to do two things: First, it explores the key findings of the OWASP Top 10 for Agentic Applications. Second, it highlights examples of practical mitigations for risks surfaced in the paper, grounded in Agent 365 and foundational capabilities in Microsoft Copilot Studio.
OWASP (the Open Worldwide Application Security Project) is an online community led by a nonprofit foundation that publishes free and open security resources, including articles, tools, and documentation used across the application security industry. In the years since the organization’s founding, OWASP Top 10 lists have become a common baseline in security programs.
In 2023, OWASP identified a security gap that needed urgent attention: traditional application security guidance wasn’t fully addressing the nascent risks stemming from the integration of LLMs and existing applications and workflows. The OWASP Top 10 for Agentic Applications was designed to offer concise, practical, and actionable guidance for builders, defenders, and decision-makers. It is the work of a global community spanning industry, academia, and government, built through an “expert-led, community-driven approach” that includes open collaboration, peer review, and evidence drawn from research and real-world deployments.
Microsoft has been a supporter of the project for quite some time, and members of the Microsoft AI Red Team helped review the Agentic Top 10 before it was published. Pete Bryan, Principal AI Security Research Lead, on the Microsoft AI Red Team, and Daniel Jones, AI Security Researcher on the Microsoft AI Red Team, also served on the OWASP Agentic Systems and Interfaces Expert Review Board.
Agentic AI delivers a whole range of novel opportunities and benefits. However, unless it is designed and implemented with security in mind, it can also introduce risk. OWASP Top 10s have been the foundation of security best practice for years. When the Microsoft AI Red Team gained the opportunity to help shape a new OWASP list focused on agentic applications, we were excited to share our experiences and perspectives. Our goal was to help the industry as a whole create safe and secure agentic experiences.
Pete Bryan, Principal AI Security Research Lead
Read as a set, the OWASP Top 10 for Agentic Applications makes one point again and again: agentic failures are rarely “bad output.” But they are bad outcomes. Many risks show up when an agent can interpret untrusted content as instruction, chain tools, act with delegated identity, and keep going across sessions and systems. Here is a quick breakdown of the types of risk called out in greater detail in the Top 10:
For security teams, knowing that these issues are top of mind across the global community of agentic AI users is only the first half of the equation. What comes next is addressing each of them through properly implemented controls and guardrails.
In agentic AI, the risk isn’t just what an agent is designed to do, but how it behaves once deployed. That’s why governance and security must span both in development (where intent, permissions, and constraints are defined), and operation (where behavior must be continuously monitored and controlled). For organizations building and deploying agents, Copilot Studio provides a secure foundation to create trustworthy agentic AI. From the earliest stages of the agent lifecycle, built in capabilities help ensure agents are safe and secure by design. Once deployed, IT and security teams can observe, govern, and secure agents across their lifecycle.
In development, Copilot Studio establishes clear behavioral boundaries. Agents are built using predefined actions, connectors, and capabilities, limiting exposure to arbitrary code execution (ASI05), unsafe tool invocation (ASI02), or uncontrolled external dependencies (ASI04). By constraining how agents interact with systems, the platform reduces the risk of unintended behavior, misuse, or redirection through indirect inputs. Copilot Studio also emphasizes containment and recoverability. Agents run in isolated environments, cannot modify their own logic without republishing (ASI10), and can be disabled or restricted when necessary (ASI07, ASI08). For example, if a deployed support agent is coaxed (via an indirect input) to “add a new action that forwards logs to an external endpoint,” it can’t quietly rewrite its own logic or expand its toolset on the fly; changes require republishing, and the agent can be disabled or restricted immediately if concerns arise. These safeguards prevent localized agent failures from propagating across systems and reinforce a key principle: agents should be treated as managed, auditable applications, not unmanaged automation.
To support governance and security during operation, Microsoft Agent 365 will be generally available on May 1. Currently in preview, Agent 365 enables organizations to observe, govern, and secure agents across their lifecycle, providing IT and security teams with centralized visibility, policy enforcement, and protection capabilities for agentic AI.
Once agents are deployed, Security and IT teams can use Agent 365 to gain visibility into agent usage, manage how agents are used, and enforce organizational guardrails across their environment. This includes insights into agent usage, performance, risks, and connections to enterprise data and tools. Teams can also implement policies and controls to help ensure safe and compliant operations. For example, if an agent accesses a sensitive document, IT and security teams can detect the activity in Agent 365, investigate the associated risk, and quickly restrict access or disable the agent before any impact occurs. Key capabilities include:
Together, these capabilities provide continuous oversight and enable rapid response when agent behavior deviates from expected boundaries.
Agentic AI changes not just what software can do, but how it operates, introducing autonomy, delegated authority, and the ability to act across systems. The shift places new demands on how systems are designed, secured, and operated. Organizations that treat agents as privileged applications, with clear identities, scoped permissions, continuous oversight, and lifecycle governance, are better positioned to manage and reduce risk as they adopt agentic AI. Establishing governance early allows teams to scale innovation confidently, rather than retroactively building controls after the agents are embedded in workflows. Here are some resources to look over as the next step in your journey:
OWASP Top 10 for Agentic Applications (2026): The baseline: top risks for agentic systems, with examples and mitigations.
Microsoft AI Red Team: How Microsoft stress-tests AI systems and what teams can learn from that practice.
Microsoft Security for AI: Microsoft’s approach to protecting AI across identity, data, threat protection, and compliance.
Microsoft Agent 365: The enterprise control plane for observing, governing, and securing agents.
Microsoft AI Agents Hub: Role-based readiness resources and guidance for building agents.
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OWASP Top 10 for Agentic Applications content © OWASP Foundation. This content is licensed under CC BY-SA 4.0. For more information, visit https://creativecommons.org/licenses/by-sa/4.0/