gsd-2022-35967
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Aliases
Aliases
{ "GSD": { "alias": "CVE-2022-35967", "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.", "id": "GSD-2022-35967", "references": [ "https://www.suse.com/security/cve/CVE-2022-35967.html" ] }, "gsd": { "metadata": { "exploitCode": "unknown", "remediation": "unknown", "reportConfidence": "confirmed", "type": "vulnerability" }, "osvSchema": { "aliases": [ "CVE-2022-35967" ], "details": "TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.", "id": "GSD-2022-35967", "modified": "2023-12-13T01:19:33.709969Z", "schema_version": "1.4.0" } }, "namespaces": { "cve.org": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2022-35967", "STATE": "PUBLIC", "TITLE": "Segfault in `QuantizedAdd` in TensorFlow" }, "affects": { "vendor": { "vendor_data": [ { "product": { "product_data": [ { "product_name": "tensorflow", "version": { "version_data": [ { "version_value": "\u003c 2.7.2" }, { "version_value": "\u003e= 2.8.0, \u003c 2.8.1" }, { "version_value": "\u003e= 2.9.0, \u003c 2.9.1" } ] } } ] }, "vendor_name": "tensorflow" } ] } }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "eng", "value": "TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue." } ] }, "impact": { "cvss": { "attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 5.9, "baseSeverity": "MEDIUM", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H", "version": "3.1" } }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "eng", "value": "CWE-20: Improper Input Validation" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x" }, { "name": "https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89" } ] }, "source": { "advisory": "GHSA-v6h3-348g-6h5x", "discovery": "UNKNOWN" } }, "gitlab.com": { "advisories": [ { "affected_range": "\u003c2.7.2||\u003e=2.8.0,\u003c2.8.1||\u003e=2.9.0,\u003c2.9.1", "affected_versions": "All versions before 2.7.2, all versions starting from 2.8.0 before 2.8.1, all versions starting from 2.9.0 before 2.9.1", "cwe_ids": [ "CWE-1035", "CWE-20", "CWE-937" ], "date": "2022-09-16", "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.", "fixed_versions": [ "2.7.2", "2.8.1", "2.9.1" ], "identifier": "CVE-2022-35967", "identifiers": [ "GHSA-v6h3-348g-6h5x", "CVE-2022-35967" ], "not_impacted": "All versions starting from 2.7.2 before 2.8.0, all versions starting from 2.8.1 before 2.9.0, all versions starting from 2.9.1", "package_slug": "pypi/tensorflow-cpu", "pubdate": "2022-09-16", "solution": "Upgrade to versions 2.7.2, 2.8.1, 2.9.1 or above.", "title": "Improper Input Validation", "urls": [ "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x", "https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89", "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0", "https://github.com/advisories/GHSA-v6h3-348g-6h5x" ], "uuid": "a7ecbec7-aeb1-4250-a14a-2a838aab67e9" }, { "affected_range": "\u003c2.7.2||\u003e=2.8.0,\u003c2.8.1||\u003e=2.9.0,\u003c2.9.1", "affected_versions": "All versions before 2.7.2, all versions starting from 2.8.0 before 2.8.1, all versions starting from 2.9.0 before 2.9.1", "cwe_ids": [ "CWE-1035", "CWE-20", "CWE-937" ], "date": "2022-09-16", "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.", "fixed_versions": [ "2.7.2", "2.8.1", "2.9.1" ], "identifier": "CVE-2022-35967", "identifiers": [ "GHSA-v6h3-348g-6h5x", "CVE-2022-35967" ], "not_impacted": "All versions starting from 2.7.2 before 2.8.0, all versions starting from 2.8.1 before 2.9.0, all versions starting from 2.9.1", "package_slug": "pypi/tensorflow-gpu", "pubdate": "2022-09-16", "solution": "Upgrade to versions 2.7.2, 2.8.1, 2.9.1 or above.", "title": "Improper Input Validation", "urls": [ "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x", "https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89", "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0", "https://github.com/advisories/GHSA-v6h3-348g-6h5x" ], "uuid": "fe521734-b3b1-4e7f-877e-bb80c4e8f09a" }, { "affected_range": "\u003e=2.7.0,\u003c2.7.2||\u003e=2.8.0,\u003c2.8.1||\u003e=2.9.0,\u003c2.9.1||==2.10", "affected_versions": "All versions starting from 2.7.0 before 2.7.2, all versions starting from 2.8.0 before 2.8.1, all versions starting from 2.9.0 before 2.9.1, version 2.10", "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H", "cwe_ids": [ "CWE-1035", "CWE-937" ], "date": "2022-09-20", "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.", "fixed_versions": [ "2.7.2", "2.8.1", "2.9.1" ], "identifier": "CVE-2022-35967", "identifiers": [ "CVE-2022-35967", "GHSA-v6h3-348g-6h5x" ], "not_impacted": "All versions before 2.7.0, all versions starting from 2.7.2 before 2.8.0, all versions starting from 2.8.1 before 2.9.0, all versions starting from 2.9.1 before 2.10, all versions after 2.10", "package_slug": "pypi/tensorflow", "pubdate": "2022-09-16", "solution": "Upgrade to versions 2.7.2, 2.8.1, 2.9.1 or above.", "title": "Improper Input Validation", "urls": [ "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x", "https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89", "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0", "https://github.com/advisories/GHSA-v6h3-348g-6h5x" ], "uuid": "cb005472-01d1-4537-8251-e887c3bb780e" } ] }, "nvd.nist.gov": { "configurations": { "CVE_data_version": "4.0", "nodes": [ { "children": [], "cpe_match": [ { "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "cpe_name": [], "versionEndExcluding": "2.7.2", "versionStartIncluding": "2.7.0", "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "cpe_name": [], "versionEndExcluding": "2.8.1", "versionStartIncluding": "2.8.0", "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.10:rc1:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.10:rc2:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.10:rc3:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.10:rc0:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "cpe_name": [], "versionEndExcluding": "2.9.1", "versionStartIncluding": "2.9.0", "vulnerable": true } ], "operator": "OR" } ] }, "cve": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2022-35967" }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "en", "value": "TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue." } ] }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "en", "value": "NVD-CWE-noinfo" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x", "refsource": "CONFIRM", "tags": [ "Patch", "Third Party Advisory" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x" }, { "name": "https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89", "refsource": "MISC", "tags": [ "Patch", "Third Party Advisory" ], "url": "https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89" } ] } }, "impact": { "baseMetricV3": { "cvssV3": { "attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 7.5, "baseSeverity": "HIGH", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H", "version": "3.1" }, "exploitabilityScore": 3.9, "impactScore": 3.6 } }, "lastModifiedDate": "2022-09-20T20:06Z", "publishedDate": "2022-09-16T21:15Z" } } }
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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.
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- 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.