ProtivAI — AI security at the model layer
Protect AI/LLM workloads — prompt-injection detection, model-supply-chain checks, and AI-incident response. ProtivAI secures the model; Zastapnik governs the agents and MCP tools that act on top of it.
12
AI Workloads
847
Prompts Analyzed
3
Blocked
Last Blocked
Prompt injection attempt on chat-api endpoint (2h ago)
The Problem
AI is a new attack surface
Traditional security tools weren't built for prompt injection, model poisoning, or AI-specific threats.
| Feature | Traditional Security | ProtivAI |
|---|---|---|
| Prompt injection detection | ||
| Model supply chain | ||
| AI-specific incidents | ||
| LLM output monitoring | ||
| Unified risk view |
Capabilities
Security built for AI
Purpose-built defenses for the unique threats facing AI/ML systems.
Prompt Injection Detection
Real-time detection of prompt injection, jailbreak, and adversarial input attempts.
Model Supply Chain
Verify model provenance, check for backdoors, and monitor dependency risks.
Output Monitoring
Detect PII leakage, hallucinations, and harmful content in model outputs.
RAG Security
Secure retrieval-augmented generation pipelines against data poisoning.
Incident Response
Automated response playbooks for AI-specific security incidents.
Model Governance
Track model versions, access controls, and usage policies across your AI fleet.
Integration
AI incidents meet the substrate
AI security events become findings in the unified risk register, enabling correlation with infrastructure vulnerabilities.
Unified Risk View
AI incidents appear alongside vulnerabilities and compliance gaps in one unified risk register.
Compliance Mapping
AI security controls map to EU AI Act, NIST AI RMF, and emerging AI governance frameworks.
Zastapnik Handoff
Model-layer risk signals flow to Zastapnik, the agent action layer, which governs the AI agents and MCP tools acting on those models.
ProtivAI also feeds Istraga, which can investigate AI incidents using the same corpus-backed reasoning it applies to infrastructure findings.