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    Aurva

    AI Runtime & Agent SecurityAI SecurityRuntime ProtectionLLM SecurityAI Governance

    Aurva provides a runtime security layer specifically designed for agentic AI architectures and LLM-driven workflows. It monitors granular data access patterns of AI agents, detects behavioral anomalies that signify prompt injection or agent hijacking, and enforces real-time compliance controls. The platform complements existing WAFs and API security tools by providing visibility into the internal logic and data orchestration of autonomous agents.

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    The Picari read

    Aurva uses eBPF telemetry to trace prompts, model calls, retrieval steps, and agent actions in Kubernetes-based AI workloads. Its main differentiator is identity-aware runtime attribution, which ties each AI action to a human, service, or agent for investigation and control. It fits teams securing internal LLM apps and agentic workflows.

    • Organizations deploying AI agents and LLM-driven workflows that require specialized runtime security beyond traditional WAF and API security.
    • Protecting LLM-driven applications from prompt injection attacks.
    • Monitoring data access and usage by autonomous AI agents.
    • Enforcing compliance for sensitive data handled by AI workflows.
    • Detecting and responding to agent hijacking attempts.

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    Aurva pricing and integrations

    For Aurva integration and pricing details, ask Picari. Start a briefing with your question, such as whether it connects to your SIEM, identity provider and ticketing stack, or how it is priced at your seat count and data volume.

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    Profile last updated on 6 September 2026 by Picari.