Why Your MODEL
Needs an Immune System
Standard "Safety Filters" are designed for content moderation. They aren't built to stop adversarial attacks, data exfiltration, or agent hijacking.
The Attack Vectors
Three ways attackers compromise your AI agents today.
Prompt Injection OWASP LLM01
"Ignore previous instructions" is just the start. Sophisticated attacks like DAN (Do Anything Now) and Base64 obfuscation bypass standard RLHF safety training.
Insecure Outputs OWASP LLM02
Blindly executing model outputs allows XSS and Remote Code Execution. If your agent can write code, it can be tricked into writing malware.
RAG Poisoning CVE-2024-Custom
Attackers inject malicious documents into your Knowledge Base. When your RAG retrieves them, the embedded payload executes, hijacking the session flow.
Model DoS OWASP LLM04
Attackers burn your token budget with infinite loops and massive context expansion attacks (e.g. "Sponge Attacks"), costing you thousands.
MCP Poisoning Active Threat
Compromised MCP servers or tools can return poisoned tool outputs that trick the agent into confirming dangerous actions or escalating privileges.
Data Leakage OWASP LLM06
Invisible text attacks (Steganography) hidden in resumes or PDFs can instruct the model to leak its system prompt or private API keys in the response.
The Evidence
Specialized security architecture beats general-purpose models every time. We tested Citadel against the world's best frontier models.
vs Gemini 2.5 & Llama 3.3
100%
Steganography Detection
Citadel's OCR pipeline catches 100% of hidden text attacks. Gemini 2.5 Flash only catches 75% and has a high false positive rate.
15ms
Average Latency
Our Go-native Gateway is 50x faster than cloud LLM checks (850ms+). Security shouldn't slow you down.
2.4x
More Accurate
Citadel Multimodal scores 81.6% on security benchmarks compared to Llama 3.3 70B's poor 34.7%.
Frequently Asked Questions
DECODING THE SECURITY LAYER