Agentic AI Security
Evaluate agent access by intent, not just identity and permissions.
Access with intent
Agentic AI security governs autonomous AI agents by monitoring what they can access, what they are asked to do, and what they actually do. It evaluates agent access based on the intent behind a request, not just the identity and permissions. Equipped with this deeper insight, security teams can pinpoint drift, govern tool usage, and reconstruct actions for investigations and audits.
Evaluate agent activity against the original user request and approved task scope.
Trace agent reasoning, tool calls, and data access from requests to outcomes.
Apply consistent policy and maintain observability as your agent deployments grow.
The Agent Visibility Gap
AI agents can access sensitive data, modify records, and trigger workflows on your organization’s behalf. Unapproved agents put data at risk immediately. Even sanctioned agents, acting within their permissions, can act beyond their intended purpose, creating unmanaged risk to your data, compliance, and operations. Keeping every agent aligned to its purpose requires visibility into intent, not just permissions.
Agent Security Capabilities
Proofpoint Agentic AI Security lets you deploy autonomous AI across your operations with confidence that agent behavior is monitored, governed, and aligned with intent. Agentic AI becomes a sanctioned investment that security teams support, not a risk they must contain.
Features
Discover custom and managed agents as well as their toolchains, MCP connections, and external services.
Pinpoint behavioral drift with telemetry across multi-step and multi-agent workflows.
Flag agent actions that go beyond the original request, even when permissions allow them.
Enforce authentication and content inspection at the MCP boundary for all tool connections.
Maintain a registry of tools, services, and MCP servers your agents depend on and assess their risk.
Reconstruct each action from user request to outcome, and keep a defensible audit trail.
WHY PROOFPOINT
| Capability | Traditional Access Controls | Proofpoint Agentic AI Security |
|---|---|---|
| Intent alignment | Confirm only whether or not an action is permitted, not whether it matches the task | Evaluates agent actions against the user request and expected task scope |
| Workflow visibility | Logs may not connect the full agent chain | Reconstructs workflows from request through reasoning, tool use, and outcome |
| MCP and tool governance | May not identify the protocol and tool layer where agents act | Tracks agent use of MCP servers, APIs, and external tools |
| Behavioral detection | Static policies can miss risk that appears only across multiple steps | Flags drift, scope expansion, and unexpected access across a sequence |
Gain the visibility and controls to scale autonomous AI without losing accountability.
AI Security Platform
Extend protection to workforce AI use and MCP connections for consistent visibility and control.
Add real-time guardrails that detect risky behavior and stop unsafe AI actions before incidents occur.
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Agentic AI security protects autonomous AI agents by monitoring their permissions, intent, workflows, tool use, data access, and outcomes. It helps security teams confirm that agent actions match the user request, business policy, and expected behavior.
Enterprises need AI agent security because agents can act across multiple systems with little human intervention. They may use APIs, tools, and MCP servers to access data or perform actions, so security teams need runtime visibility, policy enforcement, and audit trails across the full workflow.
Securing AI agents starts with discovering each agent, tool, and MCP connection in use. Teams then evaluate agent actions against the user request, apply runtime policy, and keep an audit trail. This adds intent to identity and permission checks.
Look for four capabilities:
Confirm coverage across the APIs, tools, and MCP servers your agents use.
Agent integrity is the assurance that an AI agent's permissions, intended purpose, and actual behavior remain aligned. It helps teams verify that an agent is doing what it should do, only what it is allowed to do, and what the user actually requested.
Secure MCP connections by inventorying each MCP server agents use, enforcing authentication at the MCP boundary, and inspecting the content that crosses it. Apply policy to permitted actions so agents reach data and apps only as intended.
Proofpoint helps secure AI agents by discovering agents and toolchains, monitoring runtime workflows, evaluating actions against user intent, governing MCP and tool connections, detecting anomalies, and reconstructing activity for investigation and compliance.