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

Researchers have developed PRISM, a new defense system designed to detect and prevent sensitive information leakage in multi-agent Large Language Model (LLM) pipelines. PRISM addresses the risk of information propagating between agents, a phenomenon termed propagation amplification, which can occur even without malicious intent. The system analyzes 16 features at each decoding step to calculate a risk score, allowing for per-token intervention and significantly outperforming existing defenses. AI

IMPACT Introduces a novel defense mechanism to secure multi-agent LLM systems against unintended data leakage.

RANK_REASON The cluster describes a new academic paper detailing a novel defense system for LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

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

COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    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…