gsd-2022-29204
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-29204",
"description": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
"id": "GSD-2022-29204",
"references": [
"https://www.suse.com/security/cve/CVE-2022-29204.html"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-29204"
],
"details": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
"id": "GSD-2022-29204",
"modified": "2023-12-13T01:19:41.648761Z",
"schema_version": "1.4.0"
}
},
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"ID": "CVE-2022-29204",
"STATE": "PUBLIC",
"TITLE": "Missing validation causes denial of service in TensorFlow via `Conv3DBackpropFilterV2`"
},
"affects": {
"vendor": {
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"impact": {
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"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 5.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
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"value": "CWE-191: Integer Underflow (Wrap or Wraparound)"
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"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L83-L14"
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"source": {
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"discovery": "UNKNOWN"
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"affected_versions": "All versions before 2.6.4, all versions starting from 2.7.0 before 2.7.2, all versions starting from 2.8.0 before 2.8.1",
"cwe_ids": [
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"date": "2022-05-24",
"description": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
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"identifier": "CVE-2022-29204",
"identifiers": [
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"package_slug": "pypi/tensorflow-cpu",
"pubdate": "2022-05-24",
"solution": "Upgrade to versions 2.6.4, 2.7.2, 2.8.1 or above.",
"title": "Missing validation causes denial of service via `Conv3DBackpropFilterV2`",
"urls": [
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"https://github.com/tensorflow/tensorflow/commit/20cb18724b0bf6c09071a3f53434c4eec53cc147",
"https://github.com/tensorflow/tensorflow/commit/84563f265f28b3c36a15335c8b005d405260e943",
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"https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4",
"https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2",
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"package_slug": "pypi/tensorflow-gpu",
"pubdate": "2022-05-24",
"solution": "Upgrade to versions 2.6.4, 2.7.2, 2.8.1 or above.",
"title": "Missing validation causes denial of service via `Conv3DBackpropFilterV2`",
"urls": [
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"https://github.com/tensorflow/tensorflow/commit/20cb18724b0bf6c09071a3f53434c4eec53cc147",
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"package_slug": "pypi/tensorflow",
"pubdate": "2022-05-20",
"solution": "Upgrade to versions 2.6.4, 2.7.2, 2.8.1 or above.",
"title": "Missing validation causes denial of service via `Conv3DBackpropFilterV2`",
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"https://github.com/tensorflow/tensorflow/commit/20cb18724b0bf6c09071a3f53434c4eec53cc147",
"https://github.com/tensorflow/tensorflow/commit/84563f265f28b3c36a15335c8b005d405260e943",
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"https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4",
"https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2",
"https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1",
"https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0",
"https://github.com/advisories/GHSA-hx9q-2mx4-m4pg"
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"impact": {
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"authentication": "NONE",
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"vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
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"exploitabilityScore": 3.9,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
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"baseScore": 5.5,
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"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 3.6
}
},
"lastModifiedDate": "2022-06-02T19:27Z",
"publishedDate": "2022-05-20T23:15Z"
}
}
}
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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.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- 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.
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