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PRISM system detects and stops secret leakage in multi-agent LLM pipelines

By PulseAugur Editorial · [1 sources] ·

Researchers have developed PRISM, a new defense system designed to detect and mitigate the leakage of sensitive information in multi-agent Large Language Model (LLM) pipelines. PRISM addresses the risk of information propagating between agents, a phenomenon termed propagation amplification, by analyzing 16 different signals in real-time at each generation step. This approach combines lexical, structural, and behavioral features to calculate a risk score, allowing for per-token intervention and significantly outperforming existing defenses. AI

IMPACT Introduces a novel real-time defense mechanism to secure sensitive data within complex multi-agent LLM systems.

RANK_REASON The cluster contains a research paper detailing a new method for detecting and mitigating secret leakage in LLM pipelines. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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

PRISM system detects and stops secret leakage in multi-agent LLM pipelines

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The cluster contains a research paper detailing a new method for detecting and mitigating secret leakage in LLM pipelines. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Carsten Maple ·

    PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelines

    Multi-agent LLM systems introduce a security risk in which sensitive information accessed by one agent can propagate through shared context and reappear in downstream outputs, even without explicit adversarial intent. We formalise this phenomenon as propagation amplification, whe…

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