gsd-2022-23573
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-23573",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
"id": "GSD-2022-23573",
"references": [
"https://www.suse.com/security/cve/CVE-2022-23573.html"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-23573"
],
"details": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
"id": "GSD-2022-23573",
"modified": "2023-12-13T01:19:35.037236Z",
"schema_version": "1.4.0"
}
},
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"ID": "CVE-2022-23573",
"STATE": "PUBLIC",
"TITLE": "Uninitialized variable access in Tensorflow"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "tensorflow",
"version": {
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"version_value": "\u003e= 2.7.0, \u003c 2.7.1"
},
{
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{
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}
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},
"data_format": "MITRE",
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"data_version": "4.0",
"description": {
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{
"lang": "eng",
"value": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.6,
"baseSeverity": "HIGH",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H",
"version": "3.1"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-908: Use of Uninitialized Resource"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q85f-69q7-55h2",
"refsource": "CONFIRM",
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},
{
"name": "https://github.com/tensorflow/tensorflow/commit/ef1d027be116f25e25bb94a60da491c2cf55bd0b",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/ef1d027be116f25e25bb94a60da491c2cf55bd0b"
},
{
"name": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/assign_op.h#L30-L143",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/assign_op.h#L30-L143"
}
]
},
"source": {
"advisory": "GHSA-q85f-69q7-55h2",
"discovery": "UNKNOWN"
}
},
"gitlab.com": {
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{
"affected_range": "\u003c2.5.3||\u003e=2.6.0,\u003c2.6.3||==2.7.0",
"affected_versions": "All versions before 2.5.3, all versions starting from 2.6.0 before 2.6.3, version 2.7.0",
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"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
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"date": "2022-02-11",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized , but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
"fixed_versions": [
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"2.6.3",
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"identifier": "CVE-2022-23573",
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"not_impacted": "All versions starting from 2.5.3 before 2.6.0, all versions starting from 2.6.3 before 2.7.0, all versions after 2.7.0",
"package_slug": "pypi/tensorflow-cpu",
"pubdate": "2022-02-09",
"solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
"title": "Use of Uninitialized Resource",
"urls": [
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"https://github.com/tensorflow/tensorflow/commit/ef1d027be116f25e25bb94a60da491c2cf55bd0b",
"https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/assign_op.h#L30-L143",
"https://nvd.nist.gov/vuln/detail/CVE-2022-23573",
"https://github.com/advisories/GHSA-q85f-69q7-55h2"
],
"uuid": "dec002c6-2432-433d-8abc-2fe05e93ac95"
},
{
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"affected_versions": "All versions before 2.5.3, all versions starting from 2.6.0 before 2.6.3, version 2.7.0",
"cvss_v2": "AV:N/AC:L/Au:S/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
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"CWE-908",
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],
"date": "2022-02-11",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized , but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
"fixed_versions": [
"2.5.3",
"2.6.3",
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],
"identifier": "CVE-2022-23573",
"identifiers": [
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"package_slug": "pypi/tensorflow-gpu",
"pubdate": "2022-02-09",
"solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
"title": "Use of Uninitialized Resource",
"urls": [
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"https://github.com/tensorflow/tensorflow/commit/ef1d027be116f25e25bb94a60da491c2cf55bd0b",
"https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/assign_op.h#L30-L143",
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"uuid": "0281cd07-bc33-449e-bab3-1fe0f23cddfc"
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"affected_versions": "All versions up to 2.5.2, all versions starting from 2.6.0 up to 2.6.2, version 2.7.0",
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"cwe_ids": [
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"CWE-908",
"CWE-937"
],
"date": "2022-02-10",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow We will also cherrypick this commit on TensorFlow, TensorFlow, and TensorFlow, as these are also affected and still in supported range.",
"fixed_versions": [
"2.5.3",
"2.6.3",
"2.7.1"
],
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"package_slug": "pypi/tensorflow",
"pubdate": "2022-02-04",
"solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
"title": "Use of Uninitialized Resource",
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"https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/assign_op.h#L30-L143",
"https://github.com/tensorflow/tensorflow/commit/ef1d027be116f25e25bb94a60da491c2cf55bd0b"
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"uuid": "4d96d1fc-8ffc-4e7c-b23f-c468f9fea090"
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]
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},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "SINGLE",
"availabilityImpact": "PARTIAL",
"baseScore": 6.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:S/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.0,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9
}
},
"lastModifiedDate": "2022-02-10T15:32Z",
"publishedDate": "2022-02-04T23:15Z"
}
}
}
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Sightings
| Author | Source | Type | Date |
|---|
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.