GSD-2021-41196
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-41196",
"description": "TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
"id": "GSD-2021-41196",
"references": [
"https://www.suse.com/security/cve/CVE-2021-41196.html",
"https://security.archlinux.org/CVE-2021-41196"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2021-41196"
],
"details": "TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
"id": "GSD-2021-41196",
"modified": "2023-12-13T01:23:27.379872Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
"cve.org": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2021-41196",
"STATE": "PUBLIC",
"TITLE": "Crash in `max_pool3d` when size argument is 0 or negative"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "tensorflow",
"version": {
"version_data": [
{
"version_value": "\u003e= 2.6.0, \u003c 2.6.1"
},
{
"version_value": "\u003e= 2.5.0, \u003c 2.5.2"
},
{
"version_value": "\u003c 2.4.4"
}
]
}
}
]
},
"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. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 5.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"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"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-191: Integer Underflow (Wrap or Wraparound)"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8",
"refsource": "CONFIRM",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8"
},
{
"name": "https://github.com/tensorflow/tensorflow/issues/51936",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/issues/51936"
},
{
"name": "https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b"
}
]
},
"source": {
"advisory": "GHSA-m539-j985-hcr8",
"discovery": "UNKNOWN"
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "\u003e=2.6.0,\u003c2.6.1||\u003e=2.5.0,\u003c2.5.2||\u003c2.4.4",
"affected_versions": "All versions starting from 2.6.0 before 2.6.1, all versions starting from 2.5.0 before 2.5.2, all versions before 2.4.4",
"cvss_v2": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
"cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-191",
"CWE-937"
],
"date": "2021-11-10",
"description": "TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
"fixed_versions": [
"2.6.1",
"2.4.4",
"2.4.4"
],
"identifier": "CVE-2021-41196",
"identifiers": [
"GHSA-m539-j985-hcr8",
"CVE-2021-41196"
],
"not_impacted": "All versions before 2.6.0, all versions starting from 2.6.1, all versions before 2.5.0, all versions starting from 2.4.4 before 2.5.2",
"package_slug": "pypi/tensorflow-cpu",
"pubdate": "2021-11-10",
"solution": "Upgrade to versions 2.6.1, 2.4.4, 2.4.4 or above.",
"title": "Integer Underflow ",
"urls": [
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8",
"https://nvd.nist.gov/vuln/detail/CVE-2021-41196",
"https://github.com/tensorflow/tensorflow/issues/51936",
"https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b",
"https://github.com/advisories/GHSA-m539-j985-hcr8"
],
"uuid": "38ce2a83-1919-497d-b443-5ce1aded445f"
},
{
"affected_range": "\u003e=2.6.0,\u003c2.6.1||\u003e=2.5.0,\u003c2.5.2||\u003c2.4.4",
"affected_versions": "All versions starting from 2.6.0 before 2.6.1, all versions starting from 2.5.0 before 2.5.2, all versions before 2.4.4",
"cvss_v2": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
"cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-191",
"CWE-937"
],
"date": "2021-11-10",
"description": "TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
"fixed_versions": [
"2.6.1",
"2.4.4",
"2.4.4"
],
"identifier": "CVE-2021-41196",
"identifiers": [
"GHSA-m539-j985-hcr8",
"CVE-2021-41196"
],
"not_impacted": "All versions before 2.6.0, all versions starting from 2.6.1, all versions before 2.5.0, all versions starting from 2.4.4 before 2.5.2",
"package_slug": "pypi/tensorflow-gpu",
"pubdate": "2021-11-10",
"solution": "Upgrade to versions 2.6.1, 2.4.4, 2.4.4 or above.",
"title": "Integer Underflow ",
"urls": [
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8",
"https://nvd.nist.gov/vuln/detail/CVE-2021-41196",
"https://github.com/tensorflow/tensorflow/issues/51936",
"https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b",
"https://github.com/advisories/GHSA-m539-j985-hcr8"
],
"uuid": "1f34a9b0-552a-4552-be49-12eb4974ab0d"
},
{
"affected_range": "\u003c2.4.4||\u003e=2.5.0,\u003c2.5.2||\u003e=2.6.0,\u003c2.6.1",
"affected_versions": "All versions before 2.4.4, all versions starting from 2.5.0 before 2.5.2, all versions starting from 2.6.0 before 2.6.1",
"cvss_v2": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
"cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-191",
"CWE-937"
],
"date": "2021-11-09",
"description": "TensorFlow is an open source platform for machine learning.This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive.",
"fixed_versions": [
"2.4.4",
"2.5.2",
"2.6.1"
],
"identifier": "CVE-2021-41196",
"identifiers": [
"CVE-2021-41196",
"GHSA-m539-j985-hcr8"
],
"not_impacted": "All versions starting from 2.4.4 before 2.5.0, all versions starting from 2.5.2 before 2.6.0, all versions starting from 2.6.1",
"package_slug": "pypi/tensorflow",
"pubdate": "2021-11-05",
"solution": "Upgrade to versions 2.4.4, 2.5.2, 2.6.1 or above.",
"title": "Integer Underflow (Wrap or Wraparound)",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2021-41196",
"https://github.com/tensorflow/tensorflow/issues/51936",
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8"
],
"uuid": "995a77cf-355b-48ce-9811-5faab6551175"
}
]
},
"nvd.nist.gov": {
"configurations": {
"CVE_data_version": "4.0",
"nodes": [
{
"children": [],
"cpe_match": [
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.4.4",
"vulnerable": true
},
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.5.2",
"versionStartIncluding": "2.5.0",
"vulnerable": true
},
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.6.1",
"versionStartIncluding": "2.6.0",
"vulnerable": true
}
],
"operator": "OR"
}
]
},
"cve": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2021-41196"
},
"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. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range."
}
]
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "en",
"value": "CWE-191"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/issues/51936",
"refsource": "MISC",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/issues/51936"
},
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8",
"refsource": "CONFIRM",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8"
},
{
"name": "https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b",
"refsource": "MISC",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b"
}
]
}
},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 2.1,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 3.9,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "LOW",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 5.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"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": "2021-11-09T13:56Z",
"publishedDate": "2021-11-05T20:15Z"
}
}
}
Loading…
Loading…
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Loading…
Loading…