Adrian

Adrian is an open-source runtime security monitoring and control engine for AI agents. Its SDK captures agent actions, outputs and reasoning context, evaluates behavior against policies, and can alert operators, pause a risky action, require approval or block execution. The project documents Python/LangChain/LangGraph, TypeScript and a Claude Code plugin, plus Slack, Discord and WhatsApp alerting paths. ^{1 2}

The repository also provides a self-hosted stack with backend, dashboard, SDK and local model container. That materially distinguishes Adrian from a cloud-only monitoring service and makes the implementation surface inspectable.

The open-source toolkit is free. Secure Agentics also provides a managed dashboard; current public terms say the service is free at launch but impose token-based usage limits, and commercial long-term hosted pricing was not verified in this review. Self-hosting requires Docker and, for the documented bundled local classifier path, an NVIDIA GPU is recommended while CPU-only operation is described as possible but slow. ^{1 3}

That makes software access strong but infrastructure and operational cost variable, especially for organizations choosing self-hosting to retain full data sovereignty.

The public repository is meaningful inspectability evidence: it contains the self-hosting stack, SDKs, security policy and integration code. Secure Agentics claims Adrian improves detection accuracy and catches more nuanced attacks than behavior-only monitoring, but those performance claims are vendor-authored and were not independently reproduced by AiToolMap. ¹

Crunchbase independently corroborates Secure Agentics and Adrian as an open-source runtime security toolkit with hosted-backend option, but does not supply efficacy testing. ⁴

Adrian is a defensive control, not a guarantee of agent safety. Its effectiveness depends on seeing the relevant action/reasoning path, correct policy configuration and the accuracy of its analysis. A false negative can still permit destructive infrastructure actions or data exfiltration, so least privilege, sandboxing, credential isolation and conventional monitoring remain necessary.

Privacy deserves specific attention because Adrian can capture reasoning traces, tool calls and other contextual telemetry. Self-hosting can keep the stack and model local; in managed mode, teams should treat the transmitted telemetry as potentially sensitive and apply their own data-classification and retention requirements. The terms also state that if hosted usage limits are exceeded, classification may stop while the underlying agent continues running, making fail-open behavior a deployment consideration. ^{1 3}

The fixed 50-source AiToolMap panel returned no eligible exact-product numeric user-rating signal: 45 no relevant results and five inaccessible sources. No AiToolMap hands-on test was performed.

Adrian fits developers, platform teams and security teams that want runtime visibility and intervention rather than input/output filtering alone. It is especially relevant when agents have consequential tools and the organization wants a self-hosted option plus human approval and messaging integrations. ²

It is less suitable for teams that cannot expose reasoning/context to a monitor, expect a mature independent benchmark record, or need a hosted control that is contractually guaranteed never to stop classifying under usage limits.