{"data":{"id":"8dfacd8c-c068-4b04-ac17-34eeeb217333","title":"CVE-2024-27133: Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. This issue leads ","summary":"MLflow, a machine learning platform, has a vulnerability where it doesn't properly clean user input from dataset tables, allowing XSS (cross-site scripting, where attackers inject malicious code into web pages). When someone runs a recipe using an untrusted dataset in Jupyter Notebook, this can lead to RCE (remote code execution, where an attacker can run commands on the user's computer).","solution":"A patch is available at https://github.com/mlflow/mlflow/pull/10893","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2024-27133","publishedAt":"2024-02-24T03:15:55.287Z","cveId":"CVE-2024-27133","cweIds":["CWE-79"],"cvssScore":"7.5","cvssSeverity":"high","severity":"high","attackType":["rag_poisoning"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["MLflow"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0.0015,"patchAvailable":null,"disclosureDate":null,"capecIds":["CAPEC-198","CAPEC-86"],"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","confidentiality"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.92,"researchCategory":null,"atlasIds":null}}