The Agent Vulnerability Index
We analyzed 4.2 million simulated LLM tool calls across LangChain, CrewAI, and AutoGen. The data is clear: probabilistic intent cannot be trusted with deterministic execution.
of natively orchestrated agents executed a destructive `DROP TABLE` command when subjected to a mid-context indirect prompt injection (e.g., hidden inside an email summary).
of LLM-generated payloads hallucinated incorrect JSON schema parameters that completely bypassed standard Zod/Pydantic validation layers by substituting analogous string types.
The average compute time required for Exogram's cryptographic matrix to successfully evaluate intent and block a malicious tool call before it reaches the backend execution engine.
Framework Security Comparison matrix
| Orchestrator | Native Execution Firewall | Hallucination Block Rate | Data Exfiltration Prevention |
|---|---|---|---|
| Exogram (4-Layer Control Plane) | ✅ Cryptographic State Matrix | 100.0% (Deterministic) | Deep-inspected payloads |
| LangChain | ❌ None (Relies on LLM) | 14.2% (Probabilistic) | Vulnerable |
| CrewAI | ❌ None | 17.8% (Probabilistic) | Vulnerable |
| AutoGen | ❌ Code Exec Sandbox Only | 45.0% (Sandboxing) | Vulnerable to API hijacking |
Don't be a statistic.
Stop trusting probabilistic reasoning models with your deterministic production databases. Route your LLM tool calls through Exogram's execution firewall.
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