Threat Landscape
Our threat analysis identified 44 distinct attack techniques across 10 categories targeting AI-connected systems. PeriMind addresses or mitigates 92% of in-scope threats. Understanding this landscape is increasingly a regulatory and compliance imperative.
88%
of organizations reported AI agent security incidents
Gravitee 2026
45.6%
rely on shared API keys for agent authentication
Gravitee 2026
79%
have no real-time visibility into autonomous agent activity
CSA/Strata 2026
Sources: Gravitee, State of AI Agent Security 2026 · CSA & Strata Identity, AI Agent Identity Crisis Survey 2026
Attack Categories
Fake MCP servers intercepting connections
Malicious tool definitions injecting behavior
Cross-tool data contamination attacks
Token extraction via tool call manipulation
82% of servers vulnerable to file access
Sensitive data leaked through tool responses
Agents gaining unauthorized system access
Post-approval tool definition changes
Unauthorized AI usage costing $670K avg
Compromised upstream tool packages and MCP servers
92% of in-scope threats addressed or mitigated by the PeriMind control plane.
Security Gaps
Traditional security infrastructure was built for human users and network traffic. AI agent interactions require a fundamentally different approach.
Network layer only. Cannot inspect tool call semantics or understand AI agent intent.
Authenticates the human, not the AI agent. No concept of tool-level authorization.
Blind to tool-level interactions. Designed for cloud app access, not agent-to-system calls.
Cannot understand contextual appropriateness of data flowing through tool responses.
No prevention, no real-time enforcement. Detects after the fact, not at the point of action.
Take Action
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