{"data":{"id":"64bfa34b-ed41-4de3-ad47-088e8a76544f","title":"Say Shibboleth: Fingerprinting the LLMs and Harnesses Behind Agentic Attacks","summary":"The authors study fingerprinting of agentic cyberattacks, aiming to infer the attacker's LLM version and harness from telemetry. They introduce shibboleth traps, modular honeypot services that elicit model declarations and characteristic behavior without requiring a successful prompt injection, plus indirect probes of harness behavior. Combined declarative and behavioral inference distinguishes 15 candidate models with about 90% top-1 accuracy, and fixed probe rules identify the correct harness across four harnesses with 92% accuracy.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"https://arxiv.org/abs/2611.12386v1","publishedAt":"2026-11-09T13:27:13.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["other"],"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":"2026-11-09T13:27:13.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["confidentiality"],"aiComponentTargeted":"agent","llmSpecific":true,"classifierConfidence":0.9,"researchCategory":"preprint","atlasIds":null}}