GSD-2022-21728
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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-2022-21728",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python\u0027s negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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-2022-21728",
"references": [
"https://www.suse.com/security/cve/CVE-2022-21728.html"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-21728"
],
"details": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python\u0027s negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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-2022-21728",
"modified": "2023-12-13T01:19:14.402846Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
"cve.org": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2022-21728",
"STATE": "PUBLIC",
"TITLE": "Out of bounds read in Tensorflow"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "n/a",
"version": {
"version_data": [
{
"version_value": "n/a"
}
]
}
}
]
},
"vendor_name": "n/a"
}
]
}
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "eng",
"value": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python\u0027s negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
"version": "3.1"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "n/a"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8",
"refsource": "CONFIRM",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8"
},
{
"name": "https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995"
},
{
"name": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428"
},
{
"name": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671"
}
]
},
"source": {
"advisory": "GHSA-6gmv-pjp9-p8w8",
"discovery": "UNKNOWN"
}
},
"gitlab.com": {
"advisories": [
{
"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",
"cvss_v2": "AV:N/AC:L/Au:S/C:P/I:N/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-125",
"CWE-937"
],
"date": "2022-02-10",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python\u0027s negative indexing , however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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",
"2.7.1"
],
"identifier": "CVE-2022-21728",
"identifiers": [
"GHSA-6gmv-pjp9-p8w8",
"CVE-2022-21728"
],
"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": "Out-of-bounds Read",
"urls": [
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8",
"https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995",
"https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428",
"https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671",
"https://nvd.nist.gov/vuln/detail/CVE-2022-21728",
"https://github.com/advisories/GHSA-6gmv-pjp9-p8w8"
],
"uuid": "05fcfd73-1b58-4d97-8765-c3a6bf08b0b2"
},
{
"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",
"cvss_v2": "AV:N/AC:L/Au:S/C:P/I:N/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-125",
"CWE-937"
],
"date": "2022-02-10",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python\u0027s negative indexing , however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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",
"2.7.1"
],
"identifier": "CVE-2022-21728",
"identifiers": [
"GHSA-6gmv-pjp9-p8w8",
"CVE-2022-21728"
],
"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-gpu",
"pubdate": "2022-02-09",
"solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
"title": "Out-of-bounds Read",
"urls": [
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8",
"https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995",
"https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428",
"https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671",
"https://nvd.nist.gov/vuln/detail/CVE-2022-21728",
"https://github.com/advisories/GHSA-6gmv-pjp9-p8w8"
],
"uuid": "887ccf22-e884-404a-b297-eb0c9383b1e0"
},
{
"affected_range": "\u003c=2.5.2||\u003e=2.6.0,\u003c=2.6.2||==2.7.0",
"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",
"cvss_v2": "AV:N/AC:L/Au:S/C:P/I:N/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-125",
"CWE-937"
],
"date": "2022-02-08",
"description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python\u0027s negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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"
],
"identifier": "CVE-2022-21728",
"identifiers": [
"CVE-2022-21728",
"GHSA-6gmv-pjp9-p8w8"
],
"not_impacted": "All versions after 2.5.2 before 2.6.0, all versions after 2.6.2 before 2.7.0, all versions after 2.7.0",
"package_slug": "pypi/tensorflow",
"pubdate": "2022-02-03",
"solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
"title": "Out-of-bounds Read",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2022-21728",
"https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995",
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8"
],
"uuid": "87269ecc-6e16-4429-aa1d-c229afdc9694"
}
]
},
"nvd.nist.gov": {
"configurations": {
"CVE_data_version": "4.0",
"nodes": [
{
"children": [],
"cpe_match": [
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndIncluding": "2.5.2",
"vulnerable": true
},
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndIncluding": "2.6.2",
"versionStartIncluding": "2.6.0",
"vulnerable": true
},
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*",
"cpe_name": [],
"vulnerable": true
}
],
"operator": "OR"
}
]
},
"cve": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2022-21728"
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "en",
"value": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python\u0027s negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. 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."
}
]
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "en",
"value": "CWE-125"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995",
"refsource": "MISC",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995"
},
{
"name": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671",
"refsource": "MISC",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671"
},
{
"name": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428",
"refsource": "MISC",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428"
},
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8",
"refsource": "CONFIRM",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8"
}
]
}
},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "SINGLE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:S/C:P/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.0,
"impactScore": 4.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.2
}
},
"lastModifiedDate": "2022-02-08T20:22Z",
"publishedDate": "2022-02-03T11:15Z"
}
}
}
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…