GSD-2021-29571
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-29571",
"description": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.",
"id": "GSD-2021-29571",
"references": [
"https://www.suse.com/security/cve/CVE-2021-29571.html",
"https://security.archlinux.org/CVE-2021-29571"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2021-29571"
],
"details": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.",
"id": "GSD-2021-29571",
"modified": "2023-12-13T01:23:36.977095Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
"cve.org": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2021-29571",
"STATE": "PUBLIC",
"TITLE": "Memory corruption in `DrawBoundingBoxesV2`"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "tensorflow",
"version": {
"version_data": [
{
"version_value": "\u003c 2.1.4"
},
{
"version_value": "\u003e= 2.2.0, \u003c 2.2.3"
},
{
"version_value": "\u003e= 2.3.0, \u003c 2.3.3"
},
{
"version_value": "\u003e= 2.4.0, \u003c 2.4.2"
}
]
}
}
]
},
"vendor_name": "tensorflow"
}
]
}
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "eng",
"value": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "HIGH",
"attackVector": "LOCAL",
"availabilityImpact": "LOW",
"baseScore": 4.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:L",
"version": "3.1"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-787: Out-of-bounds Write"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6",
"refsource": "CONFIRM",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6"
},
{
"name": "https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517"
}
]
},
"source": {
"advisory": "GHSA-whr9-vfh2-7hm6",
"discovery": "UNKNOWN"
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "\u003c2.1.4||\u003e=2.2.0,\u003c2.2.3||\u003e=2.3.0,\u003c2.3.3||\u003e=2.4.0,\u003c2.4.2",
"affected_versions": "All versions before 2.1.4, all versions starting from 2.2.0 before 2.2.3, all versions starting from 2.3.0 before 2.3.3, all versions starting from 2.4.0 before 2.4.2",
"cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-78",
"CWE-787",
"CWE-937"
],
"date": "2021-05-21",
"description": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation assumes that the last element of `boxes` input is 4, as required by the op Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.",
"fixed_versions": [
"2.1.4",
"2.2.3",
"2.3.3",
"2.4.2"
],
"identifier": "CVE-2021-29571",
"identifiers": [
"GHSA-whr9-vfh2-7hm6",
"CVE-2021-29571"
],
"not_impacted": "All versions starting from 2.1.4 before 2.2.0, all versions starting from 2.2.3 before 2.3.0, all versions starting from 2.3.3 before 2.4.0, all versions starting from 2.4.2",
"package_slug": "pypi/tensorflow-cpu",
"pubdate": "2021-05-21",
"solution": "Upgrade to versions 2.1.4, 2.2.3, 2.3.3, 2.4.2 or above.",
"title": "Out-of-bounds Write",
"urls": [
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6",
"https://nvd.nist.gov/vuln/detail/CVE-2021-29571",
"https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517",
"https://github.com/advisories/GHSA-whr9-vfh2-7hm6"
],
"uuid": "c3b9cab4-737c-4413-9053-50b3daff7eb0"
},
{
"affected_range": "\u003c2.1.4||\u003e=2.2.0,\u003c2.2.3||\u003e=2.3.0,\u003c2.3.3||\u003e=2.4.0,\u003c2.4.2",
"affected_versions": "All versions before 2.1.4, all versions starting from 2.2.0 before 2.2.3, all versions starting from 2.3.0 before 2.3.3, all versions starting from 2.4.0 before 2.4.2",
"cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-78",
"CWE-787",
"CWE-937"
],
"date": "2021-05-21",
"description": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation assumes that the last element of `boxes` input is 4, as required by the op Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.",
"fixed_versions": [
"2.1.4",
"2.2.3",
"2.3.3",
"2.4.2"
],
"identifier": "CVE-2021-29571",
"identifiers": [
"GHSA-whr9-vfh2-7hm6",
"CVE-2021-29571"
],
"not_impacted": "All versions starting from 2.1.4 before 2.2.0, all versions starting from 2.2.3 before 2.3.0, all versions starting from 2.3.3 before 2.4.0, all versions starting from 2.4.2",
"package_slug": "pypi/tensorflow-gpu",
"pubdate": "2021-05-21",
"solution": "Upgrade to versions 2.1.4, 2.2.3, 2.3.3, 2.4.2 or above.",
"title": "Out-of-bounds Write",
"urls": [
"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6",
"https://nvd.nist.gov/vuln/detail/CVE-2021-29571",
"https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517",
"https://github.com/advisories/GHSA-whr9-vfh2-7hm6"
],
"uuid": "6d0f08cd-6cba-4532-9c60-13b98a8dd670"
},
{
"affected_range": "\u003c=2.1.4||\u003e=2.2.0,\u003c=2.2.3||\u003e=2.3.0,\u003c=2.3.3||\u003e=2.4.0,\u003c=2.4.2",
"affected_versions": "All versions up to 2.1.4, all versions starting from 2.2.0 up to 2.2.3, all versions starting from 2.3.0 up to 2.3.3, all versions starting from 2.4.0 up to 2.4.2",
"cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-787",
"CWE-937"
],
"date": "2021-07-26",
"description": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices.",
"fixed_versions": [
"2.5.0"
],
"identifier": "CVE-2021-29571",
"identifiers": [
"CVE-2021-29571",
"GHSA-whr9-vfh2-7hm6"
],
"not_impacted": "All versions after 2.1.4 before 2.2.0, all versions after 2.2.3 before 2.3.0, all versions after 2.3.3 before 2.4.0, all versions after 2.4.2",
"package_slug": "pypi/tensorflow",
"pubdate": "2021-05-14",
"solution": "Upgrade to version 2.5.0 or above.",
"title": "Out-of-bounds Write",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2021-29571"
],
"uuid": "48df5329-1c9f-49bc-abf9-399e84934eaa"
}
]
},
"nvd.nist.gov": {
"configurations": {
"CVE_data_version": "4.0",
"nodes": [
{
"children": [],
"cpe_match": [
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.1.4",
"vulnerable": true
},
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.2.3",
"versionStartIncluding": "2.2.0",
"vulnerable": true
},
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.3.3",
"versionStartIncluding": "2.3.0",
"vulnerable": true
},
{
"cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.4.2",
"versionStartIncluding": "2.4.0",
"vulnerable": true
}
],
"operator": "OR"
}
]
},
"cve": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2021-29571"
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "en",
"value": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range."
}
]
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "en",
"value": "CWE-787"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517",
"refsource": "MISC",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517"
},
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6",
"refsource": "CONFIRM",
"tags": [
"Exploit",
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6"
}
]
}
},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 4.6,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 3.9,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 5.9
}
},
"lastModifiedDate": "2021-07-26T16:10Z",
"publishedDate": "2021-05-14T20:15Z"
}
}
}
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…