{"data":{"id":"9e88b078-a9ee-4d13-8b43-a3819f292971","title":"Risk-Aware Privacy Preservation for LLM Inference","summary":"Researchers propose Rap-LI, a risk-aware privacy preservation framework for LLM inference services such as ChatGPT. It identifies and labels risky content in user prompts, then applies a risk-aware local differential privacy mechanism to sanitize the text. The authors report an average 51.68% improvement in protection against sensitive information leakage over methods with comparable utility.","solution":"N/A -- no mitigation discussed in source.","labels":["research","privacy"],"sourceUrl":"http://ieeexplore.ieee.org/document/11409403","publishedAt":"2026-02-24T13:17:14.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["pii_leakage"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":["OpenAI"],"affectedVendorsRaw":["ChatGPT","LLM inference services"],"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":"2026-02-24T13:17:14.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality"],"aiComponentTargeted":"api","llmSpecific":true,"classifierConfidence":0.9,"researchCategory":"peer_reviewed","atlasIds":null}}