gsd-2021-37657
Vulnerability from gsd
Modified
2023-12-13 01:23
Details
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Aliases
Aliases
{ "GSD": { "alias": "CVE-2021-37657", "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.", "id": "GSD-2021-37657", "references": [ "https://www.suse.com/security/cve/CVE-2021-37657.html", "https://security.archlinux.org/CVE-2021-37657" ] }, "gsd": { "metadata": { "exploitCode": "unknown", "remediation": "unknown", "reportConfidence": "confirmed", "type": "vulnerability" }, "osvSchema": { "aliases": [ "CVE-2021-37657" ], "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.", "id": "GSD-2021-37657", "modified": "2023-12-13T01:23:09.804615Z", "schema_version": "1.4.0" } }, "namespaces": { "cve.org": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-37657", "STATE": "PUBLIC", "TITLE": "Reference binding to nullptr in `MatrixDiagV*` ops in TensorFlow" }, "affects": { "vendor": { "vendor_data": [ { "product": { "product_data": [ { "product_name": "tensorflow", "version": { "version_data": [ { "version_value": "\u003e= 2.5.0, \u003c 2.5.1" }, { "version_value": "\u003e= 2.4.0, \u003c 2.4.3" }, { "version_value": "\u003c 2.3.4" } ] } } ] }, "vendor_name": "tensorflow" } ] } }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "eng", "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range." } ] }, "impact": { "cvss": { "attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "HIGH", "baseScore": 7.1, "baseSeverity": "HIGH", "confidentialityImpact": "NONE", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H", "version": "3.1" } }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "eng", "value": "CWE-824: Access of Uninitialized Pointer" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m" }, { "name": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09" } ] }, "source": { "advisory": "GHSA-5xwc-mrhx-5g3m", "discovery": "UNKNOWN" } }, "gitlab.com": { "advisories": [ { "affected_range": "\u003c2.3.4||\u003e=2.4.0,\u003c2.4.3||==2.5.0", "affected_versions": "All versions before 2.3.4, all versions starting from 2.4.0 before 2.4.3, version 2.5.0", "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P", "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "cwe_ids": [ "CWE-1035", "CWE-824", "CWE-937" ], "date": "2021-08-25", "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The implementation has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.", "fixed_versions": [ "2.3.4", "2.4.3", "2.5.1" ], "identifier": "CVE-2021-37657", "identifiers": [ "GHSA-5xwc-mrhx-5g3m", "CVE-2021-37657" ], "not_impacted": "All versions starting from 2.3.4 before 2.4.0, all versions starting from 2.4.3 before 2.5.0, all versions after 2.5.0", "package_slug": "pypi/tensorflow-cpu", "pubdate": "2021-08-25", "solution": "Upgrade to versions 2.3.4, 2.4.3, 2.5.1 or above.", "title": "Access of Uninitialized Pointer", "urls": [ "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m", "https://nvd.nist.gov/vuln/detail/CVE-2021-37657", "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09", "https://github.com/advisories/GHSA-5xwc-mrhx-5g3m" ], "uuid": "155d9e66-8efc-410b-b150-986d2c675662" }, { "affected_range": "\u003c2.3.4||\u003e=2.4.0,\u003c2.4.3||==2.5.0", "affected_versions": "All versions before 2.3.4, all versions starting from 2.4.0 before 2.4.3, version 2.5.0", "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P", "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "cwe_ids": [ "CWE-1035", "CWE-824", "CWE-937" ], "date": "2021-08-25", "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The implementation has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.", "fixed_versions": [ "2.3.4", "2.4.3", "2.5.1" ], "identifier": "CVE-2021-37657", "identifiers": [ "GHSA-5xwc-mrhx-5g3m", "CVE-2021-37657" ], "not_impacted": "All versions starting from 2.3.4 before 2.4.0, all versions starting from 2.4.3 before 2.5.0, all versions after 2.5.0", "package_slug": "pypi/tensorflow-gpu", "pubdate": "2021-08-25", "solution": "Upgrade to versions 2.3.4, 2.4.3, 2.5.1 or above.", "title": "Access of Uninitialized Pointer", "urls": [ "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m", "https://nvd.nist.gov/vuln/detail/CVE-2021-37657", "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09", "https://github.com/advisories/GHSA-5xwc-mrhx-5g3m" ], "uuid": "1c41f248-f922-440c-bbfd-337707296ca9" }, { "affected_range": "\u003e=2.3.0,\u003c2.3.4||\u003e=2.4.0,\u003c2.4.3||\u003e=2.5.0,\u003c=2.6.0", "affected_versions": "All versions starting from 2.3.0 before 2.3.4, all versions starting from 2.4.0 before 2.4.3, all versions starting from 2.5.0 up to 2.6.0", "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P", "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "cwe_ids": [ "CWE-1035", "CWE-937" ], "date": "2021-08-18", "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The implementation has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong.", "fixed_versions": [ "2.3.4", "2.4.3" ], "identifier": "CVE-2021-37657", "identifiers": [ "CVE-2021-37657", "GHSA-5xwc-mrhx-5g3m" ], "not_impacted": "All versions before 2.3.0, all versions starting from 2.3.4 before 2.4.0, all versions starting from 2.4.3 before 2.5.0, all versions after 2.6.0", "package_slug": "pypi/tensorflow", "pubdate": "2021-08-12", "solution": "Upgrade to versions 2.3.4, 2.4.3 or above.", "title": "Access of Uninitialized Pointer", "urls": [ "https://nvd.nist.gov/vuln/detail/CVE-2021-37657" ], "uuid": "c45af75b-4da2-4ed3-870b-520c8d7e92dd" } ] }, "nvd.nist.gov": { "configurations": { "CVE_data_version": "4.0", "nodes": [ { "children": [], "cpe_match": [ { "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "cpe_name": [], "versionEndExcluding": "2.3.4", "versionStartIncluding": "2.3.0", "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "cpe_name": [], "versionEndExcluding": "2.4.3", "versionStartIncluding": "2.4.0", "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true } ], "operator": "OR" } ] }, "cve": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-37657" }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "en", "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range." } ] }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "en", "value": "CWE-824" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09", "refsource": "MISC", "tags": [ "Patch", "Third Party Advisory" ], "url": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09" }, { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m", "refsource": "CONFIRM", "tags": [ "Third Party Advisory" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m" } ] } }, "impact": { "baseMetricV2": { "acInsufInfo": false, "cvssV2": { "accessComplexity": "LOW", "accessVector": "LOCAL", "authentication": "NONE", "availabilityImpact": "PARTIAL", "baseScore": 4.6, "confidentialityImpact": "PARTIAL", "integrityImpact": "PARTIAL", "vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P", "version": "2.0" }, "exploitabilityScore": 3.9, "impactScore": 6.4, "obtainAllPrivilege": false, "obtainOtherPrivilege": false, "obtainUserPrivilege": false, "severity": "MEDIUM", "userInteractionRequired": false }, "baseMetricV3": { "cvssV3": { "attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "HIGH", "baseScore": 7.8, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "version": "3.1" }, "exploitabilityScore": 1.8, "impactScore": 5.9 } }, "lastModifiedDate": "2021-08-18T14:08Z", "publishedDate": "2021-08-12T21:15Z" } } }
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Sightings
Author | Source | Type | Date |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.