gsd-2022-41894
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-41894",
"id": "GSD-2022-41894"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-41894"
],
"details": "TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels \u003e output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.",
"id": "GSD-2022-41894",
"modified": "2023-12-13T01:19:32.890013Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
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"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2022-41894",
"STATE": "PUBLIC",
"TITLE": "Buffer overflow in `CONV_3D_TRANSPOSE` on TFLite"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "tensorflow",
"version": {
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"version_value": "\u003e= 2.10.0, \u003c 2.10.1"
},
{
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"version_value": "\u003c 2.8.4"
}
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{
"lang": "eng",
"value": "TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels \u003e output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
}
},
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"lang": "eng",
"value": "CWE-120: Buffer Copy without Checking Size of Input (\u0027Classic Buffer Overflow\u0027)"
}
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}
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{
"name": "https://github.com/tensorflow/tensorflow/commit/72c0bdcb25305b0b36842d746cc61d72658d2941",
"refsource": "MISC",
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{
"name": "https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121",
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"url": "https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121"
}
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"source": {
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"discovery": "UNKNOWN"
}
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"affected_range": "\u003c2.8.4||\u003e=2.9.0,\u003c2.9.3||\u003e=2.10.0,\u003c2.10.1",
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"cwe_ids": [
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"CWE-937"
],
"date": "2022-11-22",
"description": "TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels \u003e output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.",
"fixed_versions": [
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"2.9.3",
"2.10.1"
],
"identifier": "CVE-2022-41894",
"identifiers": [
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"GHSA-h6q3-vv32-2cq5"
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"not_impacted": "All versions starting from 2.8.4 before 2.9.0, all versions starting from 2.9.3 before 2.10.0, all versions starting from 2.10.1",
"package_slug": "pypi/tensorflow",
"pubdate": "2022-11-18",
"solution": "Upgrade to versions 2.8.4, 2.9.3, 2.10.1 or above.",
"title": "Buffer Copy without Checking Size of Input (\u0027Classic Buffer Overflow\u0027)",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2022-41894",
"https://github.com/tensorflow/tensorflow/commit/72c0bdcb25305b0b36842d746cc61d72658d2941",
"https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121",
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"uuid": "e5e40763-35e9-4b38-9f8a-6ddbf922be84"
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{
"affected_range": "\u003c2.8.4||\u003e=2.9.0,\u003c2.9.3||\u003e=2.10.0,\u003c2.10.1",
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"cwe_ids": [
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"CWE-120",
"CWE-937"
],
"date": "2022-11-21",
"description": "TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels \u003e output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.",
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],
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"package_slug": "pypi/tflite",
"pubdate": "2022-11-21",
"solution": "Upgrade to versions 2.8.4, 2.9.3, 2.10.1 or above.",
"title": "Buffer Copy without Checking Size of Input (\u0027Classic Buffer Overflow\u0027)",
"urls": [
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"https://github.com/tensorflow/tensorflow/commit/72c0bdcb25305b0b36842d746cc61d72658d2941",
"https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121",
"https://github.com/advisories/GHSA-h6q3-vv32-2cq5"
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}
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"impact": {
"baseMetricV3": {
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"attackVector": "NETWORK",
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"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
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"privilegesRequired": "NONE",
"scope": "UNCHANGED",
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"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
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"exploitabilityScore": 2.2,
"impactScore": 5.9
}
},
"lastModifiedDate": "2022-11-22T21:02Z",
"publishedDate": "2022-11-18T22:15Z"
}
}
}
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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.
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