{"data":{"id":"9ef99221-b4f3-4ca3-8738-8f88912d44ea","title":"CVE-2020-25459: An issue was discovered in function sync_tree in hetero_decision_tree_guest.py in WeBank FATE (Federated AI Technology E","summary":"CVE-2020-25459 is a vulnerability in WeBank FATE (Federated AI Technology Enabler, a system for training machine learning models across multiple parties) versions 0.1 through 1.4.2 that allows attackers to read sensitive information during the training process. The issue exists in a function called sync_tree in the hetero_decision_tree_guest.py file, which means attackers could access private data while the model is being trained.","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2020-25459","publishedAt":"2022-06-16T21:15:07.713Z","cveId":"CVE-2020-25459","cweIds":["CWE-668"],"cvssScore":"7.5","cvssSeverity":"high","severity":"high","attackType":["data_extraction"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["WeBank FATE"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0.00316,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality"],"aiComponentTargeted":"training_data","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":null,"atlasIds":null}}