{"data":{"id":"95a52f49-49de-4acc-a687-75cbfd4667f7","title":"PRISM: Causal Counterfactual Minimization of Agent Tool Privileges via Information Bottleneck Role Induction","summary":"The paper introduces PRISM, a method that treats LLM agents as the object of role engineering to reduce over-authorization of tools exposed through the Model Context Protocol (MCP). PRISM learns a counterfactual necessity model from sandbox interventions, compresses trajectories with an information bottleneck, and prunes roles via a bilevel Stackelberg game sampled by a generative flow network. On AgentDojo, $τ$-bench and ToolEmu it cuts authorized tools per role by 78.3%, reaches a 78.2% task success rate and 88.7% counterfactual necessity accuracy, and lowers blast radius to 15.9%.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://arxiv.org/abs/2611.11539v1","publishedAt":"2026-11-08T18:24:07.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["LLM agents","Model Context Protocol (MCP)"],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-11-08T18:24:07.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality","integrity"],"aiComponentTargeted":"agent","llmSpecific":true,"classifierConfidence":0.9,"researchCategory":"preprint","atlasIds":null}}