{"data":{"id":"2732032c-0dc8-4d84-a36b-d44181dc4b12","title":"SEAL: An integral methodology for evaluating the security of agentic LLMs","summary":"The paper presents SEAL, a methodology for generating datasets to benchmark the security of tool-calling LLMs. It combines PyRIT for adversarial prompt generation and Promptfoo for structured evaluation under controlled inference-time settings, without training-time changes or external guardrails. Tested across three adversarial strategies, commercially aligned models and larger open-source architectures showed greater security stability, though a trade-off between robustness and operational availability emerged.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://doi.org/10.1016/j.cose.2026.105237","publishedAt":"2026-11-01T00:00:00.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["prompt_injection","denial_of_service"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"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":"2026-11-01T00:00:00.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality","integrity","availability"],"aiComponentTargeted":"agent","llmSpecific":true,"classifierConfidence":0.93,"researchCategory":"peer_reviewed","atlasIds":["AML.T0051"]}}