{"data":{"id":"678021e2-48e3-4411-b87f-258f7981e983","title":"MCP Tool Poisoning in Agentic AI Frameworks: A Cross-Framework Measurement Study","summary":"Researchers measured MCP tool poisoning across 12 agentic AI frameworks, 18 models, and 45 attack scenarios, using real tool execution and a canary HTTP receipt to confirm exfiltration. The overall attack success rate is 22.9% (2,113 vulnerable cells), with 12.1% verifiably exfiltrating a secret. Resistance is model-level rather than framework-level, and a regex description scanner rejects 20 of 45 scenarios at a 7.2% false-positive rate, so metadata scanning is only a partial control.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://arxiv.org/abs/2611.03555v1","publishedAt":"2026-11-02T18:17:08.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["prompt_injection","data_extraction"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":["Anthropic"],"affectedVendorsRaw":["MCP (Model Context Protocol)","Claude Opus 4.8","12 agentic AI frameworks","18 language models"],"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":"2026-11-02T18:17:08.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality","integrity"],"aiComponentTargeted":"plugin","llmSpecific":true,"classifierConfidence":0.95,"researchCategory":"preprint","atlasIds":["AML.T0051"]}}