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Databricks Omnigent blocks slow-burn AI agent attacks with contextual policies

Databricks has introduced Omnigent, a system designed to counter slow-burn prompt injection attacks against AI agents. These attacks involve breaking down malicious actions into seemingly innocuous individual steps, making them difficult to detect with traditional stateless guardrails. Omnigent employs stateful contextual policies that track the entire session's activity, allowing it to identify and block the final malicious step, such as exfiltrating sensitive data, even if each preceding action appears legitimate. AI

IMPACT Enhances AI agent security by providing a defense against sophisticated prompt injection attacks.

RANK_REASON Product announcement for an AI safety tool.

Read on Databricks Blog →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Databricks Omnigent blocks slow-burn AI agent attacks with contextual policies

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Product announcement for an AI safety tool.
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68 days old
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COVERAGE [1]

  1. Databricks Blog TIER_1 English(EN) ·

    Blocking Slow-Burn Attacks: Contextual Policies in Omnigent

    Judging an agent one action at a time isn't enough. In this post, we show how a realistic...