CVE-2020-15197

{"id": "CVE-2020-15197", "metrics": {"cvssMetricV2": [{"type": "Primary", "source": "nvd@nist.gov", "cvssData": {"version": "2.0", "baseScore": 3.5, "accessVector": "NETWORK", "vectorString": "AV:N/AC:M/Au:S/C:N/I:N/A:P", "authentication": "SINGLE", "integrityImpact": "NONE", "accessComplexity": "MEDIUM", "availabilityImpact": "PARTIAL", "confidentialityImpact": "NONE"}, "acInsufInfo": false, "impactScore": 2.9, "baseSeverity": "LOW", "obtainAllPrivilege": false, "exploitabilityScore": 6.8, "obtainUserPrivilege": false, "obtainOtherPrivilege": false, "userInteractionRequired": false}], "cvssMetricV31": [{"type": "Secondary", "source": "security-advisories@github.com", "cvssData": {"scope": "CHANGED", "version": "3.1", "baseScore": 6.3, "attackVector": "NETWORK", "baseSeverity": "MEDIUM", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H", "integrityImpact": "NONE", "userInteraction": "NONE", "attackComplexity": "HIGH", "availabilityImpact": "HIGH", "privilegesRequired": "LOW", "confidentialityImpact": "NONE"}, "impactScore": 4.0, "exploitabilityScore": 1.8}, {"type": "Primary", "source": "nvd@nist.gov", "cvssData": {"scope": "CHANGED", "version": "3.1", "baseScore": 6.3, "attackVector": "NETWORK", "baseSeverity": "MEDIUM", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H", "integrityImpact": "NONE", "userInteraction": "NONE", "attackComplexity": "HIGH", "availabilityImpact": "HIGH", "privilegesRequired": "LOW", "confidentialityImpact": "NONE"}, "impactScore": 4.0, "exploitabilityScore": 1.8}]}, "published": "2020-09-25T19:15:14.963", "references": [{"url": "https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02", "tags": ["Patch", "Third Party Advisory"], "source": "security-advisories@github.com"}, {"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1", "tags": ["Third Party Advisory"], "source": "security-advisories@github.com"}, {"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx", "tags": ["Exploit", "Third Party Advisory"], "source": "security-advisories@github.com"}, {"url": "https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02", "tags": ["Patch", "Third Party Advisory"], "source": "af854a3a-2127-422b-91ae-364da2661108"}, {"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1", "tags": ["Third Party Advisory"], "source": "af854a3a-2127-422b-91ae-364da2661108"}, {"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx", "tags": ["Exploit", "Third Party Advisory"], "source": "af854a3a-2127-422b-91ae-364da2661108"}], "vulnStatus": "Modified", "weaknesses": [{"type": "Secondary", "source": "security-advisories@github.com", "description": [{"lang": "en", "value": "CWE-20"}, {"lang": "en", "value": "CWE-617"}]}], "descriptions": [{"lang": "en", "value": "In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1."}, {"lang": "es", "value": "En Tensorflow anteriores a la versi\u00f3n 2.3.1, la implementaci\u00f3n de \"SparseCountSparseOutput\" no comprueba que los argumentos de entrada formen un tensor disperso v\u00e1lido. En particular, no existe comprobaci\u00f3n de que el tensor de \"\u00edndices\" tenga rango 2. Este tensor debe ser una matriz porque el c\u00f3digo asume que se accede a sus elementos como elementos de una matriz. Sin embargo, los usuarios maliciosos pueden pasar tensores de diferente rango, lo que resulta en un fallo de aserci\u00f3n \"CHECK\" y un bloqueo. Esto puede ser usado para causar denegaci\u00f3n de servicio en instalaciones de servicio, si los usuarios pueden controlar los componentes del tensor disperso de entrada. El problema es parcheado en el commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 y es publicado en TensorFlow versi\u00f3n 2.3.1"}], "lastModified": "2024-11-21T05:05:03.693", "configurations": [{"nodes": [{"negate": false, "cpeMatch": [{"criteria": "cpe:2.3:a:google:tensorflow:2.3.0:*:*:*:-:*:*:*", "vulnerable": true, "matchCriteriaId": "D0A7B69E-9388-48F0-B744-49453EBAF5D5"}], "operator": "OR"}]}], "sourceIdentifier": "security-advisories@github.com"}