{"id":"PYSEC-2026-1634","summary":"ml-logger has path traversal in the file argument","details":"A vulnerability was identified in geyang ml-logger 0.10.36 and prior. Affected by this vulnerability is the function log_handler of the file ml_logger/server.py. Such manipulation of the argument File leads to path traversal. It is possible to launch the attack remotely. The exploit is publicly available and might be used. This product takes the approach of rolling releases to provide continious delivery. Therefore, version details for affected and updated releases are not available.","aliases":["CVE-2025-10951","GHSA-8x9j-2p8r-7xc6"],"modified":"2026-07-07T17:47:44.740211784Z","published":"2026-07-07T16:03:05.640290Z","references":[{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2025-10951"},{"type":"WEB","url":"https://github.com/geyang/ml-logger/issues/73"},{"type":"PACKAGE","url":"https://github.com/geyang/ml-logger"},{"type":"WEB","url":"https://vuldb.com/?ctiid.325821"},{"type":"WEB","url":"https://vuldb.com/?id.325821"},{"type":"WEB","url":"https://vuldb.com/?submit.652462"},{"type":"PACKAGE","url":"https://pypi.org/project/ml-logger"},{"type":"ADVISORY","url":"https://github.com/advisories/GHSA-8x9j-2p8r-7xc6"}],"affected":[{"package":{"name":"ml-logger","ecosystem":"PyPI","purl":"pkg:pypi/ml-logger"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"last_affected":"0.10.36"}]}],"versions":["0.0.1","0.0.10","0.0.11","0.0.12","0.0.13","0.0.14","0.0.16","0.0.17","0.0.18","0.0.19","0.0.2","0.0.20","0.0.21","0.0.22","0.0.23","0.0.24","0.0.25","0.0.26","0.0.27","0.0.28","0.0.29","0.0.3","0.0.30","0.0.31","0.0.32","0.0.33","0.0.34","0.0.35","0.0.36","0.0.37","0.0.38","0.0.39","0.0.4","0.0.40","0.0.41","0.0.42","0.0.43","0.0.44","0.0.45","0.0.46","0.0.47","0.0.48","0.0.49","0.0.5","0.0.50","0.0.51","0.0.52","0.0.53","0.0.54","0.0.55","0.0.56","0.0.57","0.0.58","0.0.59","0.0.6","0.0.60","0.0.61","0.0.62","0.0.7","0.0.8","0.0.9","0.1.0","0.1.1","0.1.10","0.1.11","0.1.12","0.1.13","0.1.14","0.1.15","0.1.16","0.1.17","0.1.18","0.1.19","0.1.20","0.1.21","0.1.22","0.1.23","0.1.24","0.1.25","0.1.26","0.1.27","0.1.28","0.1.29","0.1.3","0.1.30","0.1.31","0.1.32","0.1.33","0.1.34","0.1.35","0.1.36","0.1.37","0.1.38","0.1.39","0.1.4","0.1.40","0.1.5","0.1.6","0.1.7","0.1.8","0.10.0","0.10.1","0.10.10","0.10.11","0.10.12","0.10.13","0.10.14","0.10.15","0.10.16","0.10.17","0.10.18","0.10.19","0.10.2","0.10.20","0.10.21","0.10.22","0.10.23","0.10.24","0.10.25","0.10.26","0.10.27","0.10.28","0.10.29","0.10.3","0.10.30","0.10.31","0.10.32","0.10.33","0.10.34","0.10.35","0.10.36","0.10.4","0.10.5","0.10.6","0.10.7","0.10.8","0.10.9","0.2.0","0.2.1","0.2.10","0.2.11","0.2.12","0.2.13","0.2.15","0.2.16","0.2.17","0.2.18","0.2.19","0.2.2","0.2.20","0.2.3","0.2.4","0.2.5","0.2.6","0.2.7","0.2.8","0.2.9","0.3.0","0.3.1","0.3.2","0.3.3","0.3.4","0.3.5","0.3.6","0.4.0","0.4.10","0.4.11","0.4.12","0.4.13","0.4.14","0.4.15","0.4.16","0.4.17","0.4.18","0.4.19","0.4.2","0.4.20","0.4.22","0.4.23","0.4.24","0.4.26","0.4.27","0.4.28","0.4.29","0.4.3","0.4.30","0.4.31","0.4.32","0.4.33","0.4.34","0.4.35","0.4.36","0.4.37","0.4.38","0.4.39","0.4.4","0.4.40","0.4.41","0.4.42","0.4.43","0.4.44","0.4.45","0.4.46","0.4.47","0.4.48","0.4.49","0.4.5","0.4.50","0.4.51","0.4.52","0.4.54","0.4.55","0.4.56","0.4.57","0.4.58","0.4.59","0.4.6","0.4.60","0.4.61","0.4.62","0.4.65","0.4.66","0.4.67","0.4.68","0.4.69","0.4.7","0.4.8","0.4.9","0.5.0","0.5.1","0.5.10","0.5.12","0.5.13","0.5.14","0.5.15","0.5.16","0.5.17","0.5.2","0.5.4","0.5.5","0.5.6","0.5.7","0.5.8","0.5.9","0.6.0","0.6.1","0.6.10","0.6.11","0.6.12","0.6.13","0.6.14","0.6.15","0.6.16","0.6.17","0.6.18","0.6.19","0.6.2","0.6.20","0.6.21","0.6.22","0.6.24","0.6.25","0.6.26","0.6.27","0.6.28","0.6.29","0.6.3","0.6.30","0.6.31","0.6.32","0.6.33","0.6.34rc1","0.6.34rc10","0.6.34rc2","0.6.34rc3","0.6.34rc4","0.6.34rc5","0.6.34rc6","0.6.34rc7","0.6.34rc8","0.6.34rc9","0.6.4","0.6.5","0.6.6","0.6.7","0.6.8","0.6.9","0.7.0rc1","0.7.0rc2","0.7.0rc3","0.7.0rc4","0.7.0rc5","0.7.0rc6","0.7.1","0.7.10","0.7.11","0.7.12","0.7.13","0.7.14","0.7.15","0.7.16","0.7.17","0.7.2","0.7.3","0.7.4","0.7.5","0.7.6","0.7.7","0.7.8","0.7.9","0.8.0","0.8.1","0.8.10","0.8.100","0.8.101","0.8.102","0.8.103","0.8.104","0.8.105","0.8.106","0.8.108","0.8.109","0.8.11","0.8.110","0.8.111","0.8.112","0.8.113","0.8.114","0.8.115","0.8.116","0.8.117","0.8.118","0.8.119","0.8.12","0.8.120","0.8.121","0.8.13","0.8.14","0.8.16","0.8.17","0.8.18","0.8.19","0.8.2","0.8.20","0.8.21","0.8.22","0.8.23","0.8.24","0.8.25","0.8.26","0.8.27","0.8.29","0.8.3","0.8.30","0.8.31","0.8.32","0.8.33","0.8.34","0.8.35","0.8.36","0.8.37","0.8.38","0.8.39","0.8.4","0.8.40","0.8.41","0.8.42","0.8.43","0.8.44","0.8.45","0.8.46","0.8.47","0.8.48","0.8.49","0.8.5","0.8.50","0.8.51","0.8.52","0.8.53","0.8.54","0.8.55","0.8.6","0.8.60","0.8.61","0.8.62","0.8.63","0.8.64","0.8.65","0.8.66","0.8.67","0.8.68","0.8.69","0.8.70","0.8.71","0.8.72","0.8.74","0.8.75","0.8.76","0.8.77","0.8.78","0.8.79","0.8.80","0.8.81","0.8.82","0.8.83","0.8.84","0.8.85","0.8.86","0.8.87","0.8.88","0.8.89","0.8.9","0.8.90","0.8.91","0.8.92","0.8.93","0.8.94","0.8.95","0.8.96","0.8.97","0.8.98","0.8.99","0.9.0","0.9.1","0.9.2","0.9.3","0.9.4","0.9.5","0.9.6","0.9.7","0.9.8","0.9.9"],"database_specific":{"source":"https://github.com/pypa/advisory-database/blob/main/vulns/ml-logger/PYSEC-2026-1634.yaml"}}],"schema_version":"1.7.5","severity":[{"type":"CVSS_V3","score":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L"},{"type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