ghsa-9697-98pf-4rw7
Vulnerability from github
6.8 (Medium) - CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N
Impact
An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to tf.raw_ops.UpperBound:
```python import tensorflow as tf
tf.raw_ops.UpperBound( sorted_input=[1,2,3], values=tf.constant(value=[[0,0,0],[1,1,1],[2,2,2]],dtype=tf.int64), out_type=tf.int64) ```
The implementation does not validate the rank of sorted_input argument:
cc
void Compute(OpKernelContext* ctx) override {
const Tensor& sorted_inputs_t = ctx->input(0);
// ...
OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),
Status(error::INVALID_ARGUMENT,
"Leading dim_size of both tensors must match."));
// ...
if (output_t->dtype() == DT_INT32) {
OP_REQUIRES(ctx,
FastBoundsCheck(sorted_inputs_t.dim_size(1), ...));
// ...
}
As we access the first two dimensions of sorted_inputs_t tensor, it must have rank at least 2.
A similar issue occurs in tf.raw_ops.LowerBound.
Patches
We have patched the issue in GitHub commit 42459e4273c2e47a3232cc16c4f4fff3b3a35c38.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
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{
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"2.5.0"
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},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
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{
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{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
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"ranges": [
{
"events": [
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"introduced": "2.4.0"
},
{
"fixed": "2.4.3"
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},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.5.0"
},
{
"fixed": "2.5.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"2.5.0"
]
}
],
"aliases": [
"CVE-2021-37670"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2021-08-24T14:24:19Z",
"nvd_published_at": "2021-08-12T23:15:00Z",
"severity": "MODERATE"
},
"details": "### Impact\nAn attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`:\n\n```python\nimport tensorflow as tf\n \ntf.raw_ops.UpperBound(\n sorted_input=[1,2,3],\n values=tf.constant(value=[[0,0,0],[1,1,1],[2,2,2]],dtype=tf.int64),\n out_type=tf.int64)\n```\n \nThe [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument:\n\n```cc\n void Compute(OpKernelContext* ctx) override {\n const Tensor\u0026 sorted_inputs_t = ctx-\u003einput(0);\n // ...\n OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0),\n Status(error::INVALID_ARGUMENT,\n \"Leading dim_size of both tensors must match.\"));\n // ...\n if (output_t-\u003edtype() == DT_INT32) {\n OP_REQUIRES(ctx,\n FastBoundsCheck(sorted_inputs_t.dim_size(1), ...));\n // ...\n }\n```\n\nAs we access the first two dimensions of `sorted_inputs_t` tensor, it must have rank at least 2.\n\nA similar issue occurs in `tf.raw_ops.LowerBound`.\n\n### Patches\nWe have patched the issue in GitHub commit [42459e4273c2e47a3232cc16c4f4fff3b3a35c38](https://github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c38).\n \nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.\n \n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by members of the Aivul Team from Qihoo 360.",
"id": "GHSA-9697-98pf-4rw7",
"modified": "2024-11-13T21:00:58Z",
"published": "2021-08-25T14:41:44Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9697-98pf-4rw7"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37670"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c38"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-583.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-781.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-292.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Heap OOB in `UpperBound` and `LowerBound`"
}
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.