PROTOCOL.READ / 15 min read
Zero Trust Cybersecurity for Autonomous AI Models & LLM Endpoints
Protecting corporate AI agents from prompt injection, memory poisoning, data exfiltration, and adversarial guardrail bypasses.
### Securing the AI Execution Surface
As enterprise AI agents gain access to internal APIs, database connections, and autonomous action channels, the threat surface shifts dramatically.
#### Common Attack Vectors
1. **Direct & Indirect Prompt Injection**: Injecting malicious instructions via external Web pages or ingested email documents.
2. **Data Poisoning**: Infiltrating vector database embeddings to distort model decision outputs.
3. **Tool Misuse**: Manipulating agent function calling parameters to delete files or exfiltrate credentials.
#### Defensive Architecture: The Sanitize-Evaluate-Execute Enclave
We implement an outward-facing **Guardrail Enclave** that validates every input and output tensor before executing downstream function calls.