{"containers": {"cna": {"affected": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": ">= 2.2.0, < 2.2.1"}, {"status": "affected", "version": ">= 2.3.0, < 2.3.1"}]}], "descriptions": [{"lang": "en", "value": "In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code."}], "metrics": [{"cvssV3_1": {"attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 8.1, "baseSeverity": "HIGH", "confidentialityImpact": "LOW", "integrityImpact": "LOW", "privilegesRequired": "NONE", "scope": "CHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H", "version": "3.1"}}], "problemTypes": [{"descriptions": [{"cweId": "CWE-787", "description": "{\"CWE-787\":\"Out-of-bounds Write\"}", "lang": "en", "type": "CWE"}]}], "providerMetadata": {"dateUpdated": "2020-09-25T18:50:33", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M"}, "references": [{"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"}, {"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a"}, {"tags": ["x_refsource_CONFIRM"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq"}], "source": {"advisory": "GHSA-hx2x-85gr-wrpq", "discovery": "UNKNOWN"}, "title": "Out of bounds access in tensorflow-lite", "x_legacyV4Record": {"CVE_data_meta": {"ASSIGNER": "security-advisories@github.com", "ID": "CVE-2020-15212", "STATE": "PUBLIC", "TITLE": "Out of bounds access in tensorflow-lite"}, "affects": {"vendor": {"vendor_data": [{"product": {"product_data": [{"product_name": "tensorflow", "version": {"version_data": [{"version_value": ">= 2.2.0, < 2.2.1"}, {"version_value": ">= 2.3.0, < 2.3.1"}]}}]}, "vendor_name": "tensorflow"}]}}, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": {"description_data": [{"lang": "eng", "value": "In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code."}]}, "impact": {"cvss": {"attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 8.1, "baseSeverity": "HIGH", "confidentialityImpact": "LOW", "integrityImpact": "LOW", "privilegesRequired": "NONE", "scope": "CHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H", "version": "3.1"}}, "problemtype": {"problemtype_data": [{"description": [{"lang": "eng", "value": "{\"CWE-787\":\"Out-of-bounds Write\"}"}]}]}, "references": {"reference_data": [{"name": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"}, {"name": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a"}, {"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq"}]}, "source": {"advisory": "GHSA-hx2x-85gr-wrpq", "discovery": "UNKNOWN"}}}}, "cveMetadata": {"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2020-15212", "datePublished": "2020-09-25T18:50:34", "dateReserved": "2020-06-25T00:00:00", "dateUpdated": "2020-09-25T18:50:33", "state": "PUBLISHED"}, "dataType": "CVE_RECORD", "dataVersion": "5.0"}

{"configurations": [{"nodes": [{"cpeMatch": [{"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*", "matchCriteriaId": "323B716A-E8F7-4CDA-B8FD-A56977D59C02", "versionEndExcluding": "2.2.1", "versionStartIncluding": "2.2.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*", "matchCriteriaId": "C09502A8-B667-4867-BEBD-40333E98A601", "versionEndExcluding": "2.3.1", "versionStartIncluding": "2.3.0", "vulnerable": true}], "negate": false, "operator": "OR"}]}], "descriptions": [{"lang": "en", "value": "In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code."}, {"lang": "es", "value": "En TensorFlow Lite versiones anteriores a 2.2.1 y 2.3.1, los modelos que utilizan la suma de segmentos pueden activar escrituras fuera de l\u00edmites de los b\u00faferes asignados de la pila insertando elementos negativos en el tensor de los ids de segmento. Los usuarios que tienen acceso a \"segment_ids_data\" pueden alterar \"output_index\" y luego escribir fuera del b\u00fafer de \"output_data\". Esto podr\u00eda resultar en un fallo de segmentaci\u00f3n, pero tambi\u00e9n se puede usar para corromper a\u00fan m\u00e1s la memoria y se puede encadenar con otras vulnerabilidades para crear explotaciones m\u00e1s avanzadas. El problema es parcheado en el commit 204945b19e44b57906c9344c0d00120eeeae178a y es publicado en TensorFlow versiones 2.2.1 o 2.3.1. Una soluci\u00f3n alternativa potencial ser\u00eda agregar un \"Verifier\" personalizado al c\u00f3digo de carga del modelo para asegurar que los ids de segmento sean todos positivos, aunque esto solo maneja el caso cuando los ids de segmento son almacenados est\u00e1ticamente en el modelo. Una comprobaci\u00f3n similar podr\u00eda ser realizada si los ids de segmento se generan en el tiempo de ejecuci\u00f3n entre los pasos de inferencia. Si los ids de segmento son generados como salidas de un tensor durante los pasos de inferencia, entonces no existe una posible soluci\u00f3n alternativa y se recomienda a los usuarios actualizar al c\u00f3digo parcheado"}], "id": "CVE-2020-15212", "lastModified": "2021-08-17T13:21:32.277", "metrics": {"cvssMetricV2": [{"acInsufInfo": false, "baseSeverity": "HIGH", "cvssData": {"accessComplexity": "LOW", "accessVector": "NETWORK", "authentication": "NONE", "availabilityImpact": "PARTIAL", "baseScore": 7.5, "confidentialityImpact": "PARTIAL", "integrityImpact": "PARTIAL", "vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P", "version": "2.0"}, "exploitabilityScore": 10.0, "impactScore": 6.4, "obtainAllPrivilege": false, "obtainOtherPrivilege": false, "obtainUserPrivilege": false, "source": "nvd@nist.gov", "type": "Primary", "userInteractionRequired": false}], "cvssMetricV31": [{"cvssData": {"attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 8.6, "baseSeverity": "HIGH", "confidentialityImpact": "LOW", "integrityImpact": "LOW", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H", "version": "3.1"}, "exploitabilityScore": 3.9, "impactScore": 4.7, "source": "nvd@nist.gov", "type": "Primary"}, {"cvssData": {"attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 8.1, "baseSeverity": "HIGH", "confidentialityImpact": "LOW", "integrityImpact": "LOW", "privilegesRequired": "NONE", "scope": "CHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H", "version": "3.1"}, "exploitabilityScore": 2.2, "impactScore": 5.3, "source": "security-advisories@github.com", "type": "Secondary"}]}, "published": "2020-09-25T19:15:16.510", "references": [{"source": "security-advisories@github.com", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a"}, {"source": "security-advisories@github.com", "tags": ["Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"}, {"source": "security-advisories@github.com", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Analyzed", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-787"}], "source": "nvd@nist.gov", "type": "Primary"}, {"description": [{"lang": "en", "value": "CWE-787"}], "source": "security-advisories@github.com", "type": "Secondary"}]}

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