Real-Time Threat Detection for AI Systems

Get alerted when your AI agents go rogue, leak data, or get tricked by prompt injections.

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Security for your entire AI landscape

One platform. Every AI system. Real-time protection.

Multi-Layer Detection

Deterministic, probabilistic, and self-optimizing anomaly detection models working together — catching what each layer alone would miss.

Full AI Coverage

Monitor custom-built AI agents via SDK and well-known tools like ChatGPT, Claude Code, and Copilot — through daemon, webhook, or direct provider integration.

Instant Alerts

Real-time alerts with full context, feeding directly into your existing SIEM via OpenTelemetry signals.

Every AI system. One security layer.

SDK for Custom AI

Drop-in Python SDK with additional LangChain/LangGraph support. A few lines of code and every AI interaction flows into the detection pipeline.

from stihia import StihiaClient, SenseGuard

client = StihiaClient()
guard = SenseGuard(client, messages)

async for chunk in guard.shield(llm.astream(prompt)):
    yield chunk  # secured by Stihia

Streaming-native — protects token by token as they flow
LangChain & LangGraph — drop-in framework support
Conversation context — full message history captured automatically
Zero restructuring — wrap your existing code, don't rewrite it

Track Every AI Tool

See every interaction across well-known AI systems whether via local daemon, direct webhook, or provider API. One pane of glass, any integration method.

Three layers. Zero blind spots.

The Stihia Sense engine analyzes every message in real-time through three fundamentally different detection approaches — with anomaly models that recursively self-optimize per project.

Layer 01 Signature rules

Deterministic Classifiers

Known threat signatures: destructive tool usage, credential exposure, dangerous commands. Fires instantly with zero ambiguity.

Layer 02 Semantic ML

Probabilistic Classifiers

ML models for semantic threats: prompt injections, social engineering, sophisticated data extraction that keyword matching cannot catch.

Layer 03 Behavioral baselines

Anomaly Detection

Behavioral baselines catch scope creep, unexpected actions, and goal hijacking. Models adapt per project with no manual tuning.

Deploy on your terms

Match hosting to your compliance requirements.

Cloud-Hosted

EU data centers. Fully managed by Stihia. Zero infrastructure work on your side.

Isolated Cloud

Dedicated single-tenant instance. Stronger isolation with Stihia managing operations.

Self-Hosted

Full platform on your infrastructure. Air-gapped environments. Complete data sovereignty.

See threats. Route signals.

Native visibility out of the box, or integrate with your existing SIEM.

Stihia Console dashboard showing threads and severity

Built-in security console

Immediate visibility into your AI traffic. Track active users, view overall thread volume, and drill down into conversations grouped by critical, high, medium, and low severity alerts.

SIEM & OTel Integration

All detection data is exported as standard OpenTelemetry signals. Route alerts to any OTel-capable sink to enrich your current security operations.

Compatible with any SIEM platform
Export to observability tools
Forward to data lakes & custom dashboards
Your existing security toolchain, not another silo

Detect AI security threats before they cause damage

We support you at every step - from onboarding to long-term maintenance - tailoring our solution to meet your specific security requirements.

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Stihia Zmey

Learn about AI agent vulnerabilities through an interactive game

Stihia Zmey allows you to test creative prompt techniques and see how they affect an actual AI agent. Try it out!

Play Zmey

Contact

Got any questions?

Feel free to reach out to us at hello@stihia.ai