{"data":{"id":"8ed59e8e-e5e7-476b-b5f9-7dbd71c6a572","title":"Extracting System Prompt of LLM Services in Complex (Agentic) Settings: Hierarchical Optimization and Reliable Evaluation Metrics","summary":"Existing prompt extraction attacks degrade on recent LLM services, whose system prompts are longer and more structured and whose raw outputs are often hidden behind post-processing. The authors propose ExtraHerO, which decomposes extraction into a hierarchical reconstruction guided by a structural prompt template and iteratively updates adversarial queries, with early stopping based on information gain. Across chatbots and agents, it reports average improvements of 12.5% (fidelity), 2.3% (functionality), and 6.0% (adversarial utility) on chatbots, and 12.2%, 34.3%, and 30.5% on agents.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://arxiv.org/abs/2611.04803v1","publishedAt":"2026-11-03T12:37:01.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"low","attackType":["data_extraction"],"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":"2026-11-03T12:37:01.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["confidentiality"],"aiComponentTargeted":"api","llmSpecific":true,"classifierConfidence":0.95,"researchCategory":"preprint","atlasIds":null}}