The Problem
AI agents connect to enterprise systems through Model Context Protocol (MCP), exposing tools across Jira, GitHub, Salesforce, Slack, filesystems, and more. This surface is invisible to DLP, CASB, and SIEM tooling. The attack vector is not a single misconfigured tool. It is the combination.
An injection vector: external content the agent processes.
An exfiltration target: sensitive data the agent can read.
An exfiltration channel: an external destination the agent can reach.
When all three are present across any combination of tools, a complete attack path exists — regardless of whether any individual tool is misconfigured. This is the core theoretical gap: traditional security tools evaluate tools individually. AgentWarden evaluates tool combinations.
Core capabilities
Evaluate
AgentWarden checks every tool an agent can access and tags each for Lethal Trifecta capabilities and outputs a prioritized risk report, generated in under five minutes: theoretical vs. actively exercised paths, per-tool contribution, and unused high-risk tools flagged for immediate removal.
Scope
The highest-leverage remediation is scope reduction: eliminating tools the agent doesn't need. AgentWarden identifies unused high-risk tools and recommends specific capability restrictions based on evaluation findings. In practice, this eliminates 90%+ of attack paths before any policy enforcement is required.
Enforce
AgentWarden enforces deny, human approval, or allow decisions per tool call at the agent-tool boundary, in real time. Out-of-box protections, available immediately with no model training or custom configuration required:
Govern AI agents and MCP
AgentWarden re-evaluates agents and MCP servers periodically, detecting new risks introduced by tool changes and permission updates. Policy configurations are version-controlled with delta tracking between evaluation cycles and a full approval audit trail for every policy change. Agent trajectories are monitored continuously, with real-time alerting on policy violations and anomalous behavior before data exfiltration occurs.
Results / Use Case
A Cursor-based coding agent connected to 6 MCP servers — GitLab, Atlassian, GitHub, Playwright, Notion, and a local filesystem — exposed 154 tools to the agent, producing over 1 million distinct data exfiltration attack paths. 80% of observed workflows were operating within risk exposure.
After running AgentWarden:
Workflow policy coverage
Attack surface eliminated
Evaluation duration
AgentWarden integrates via client hooks or network proxy across MCP clients (Cursor, Claude Code, Windsurf, Azure AI Agents, custom agents), MCP servers (Atlassian, GitHub, GitLab, Salesforce, ServiceNow, Slack, Notion, and more), and network security providers including McAfee and Zscaler.
Cursor, Claude Code, Windsurf, Azure AI Agents, custom agents, VS Code
Atlassian, GitHub, GitLab, Salesforce, ServiceNow, Slack, Notion, and more
McAfee, Zscaler, and similar network security solutions
See AgentWarden evaluate your agent deployment — attack path discovery to active policy enforcement.
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