GHSA-RRFP-J2MP-HQ9C
Vulnerability from github – Published: 2020-11-13 17:13 – Updated: 2024-10-30 21:22
VLAI?
Summary
Segfault in `tf.quantization.quantize_and_dequantize`
Details
Impact
An attacker can pass an invalid axis value to tf.quantization.quantize_and_dequantize:
tf.quantization.quantize_and_dequantize(
input=[2.5, 2.5], input_min=[0,0], input_max=[1,1], axis=10)
This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation:
const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);
However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array:
int64 TensorShapeBase<Shape>::dim_size(int d) const {
DCHECK_GE(d, 0);
DCHECK_LT(d, dims());
DoStuffWith(dims_[d]);
}
Since in normal builds, DCHECK-like macros are no-ops, this results in segfault and access out of bounds of the array.
Patches
We have patched the issue in eccb7ec454e6617738554a255d77f08e60ee0808 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
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 in #42105
Severity ?
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.4.0"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.4.0"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.4.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2020-15265"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2020-11-13T17:11:27Z",
"nvd_published_at": "2020-10-21T21:15:00Z",
"severity": "HIGH"
},
"details": "### Impact\nAn attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`:\n\n```python\ntf.quantization.quantize_and_dequantize(\n input=[2.5, 2.5], input_min=[0,0], input_max=[1,1], axis=10)\n```\n\nThis results in accessing [a dimension outside the rank of the input tensor](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74) in the C++ kernel implementation:\n```\nconst int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);\n```\n\nHowever, [`dim_size` only does a `DCHECK`](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/framework/tensor_shape.cc#L292-L307) to validate the argument and then uses it to access the corresponding element of an array:\n```\nint64 TensorShapeBase\u003cShape\u003e::dim_size(int d) const {\n DCHECK_GE(d, 0);\n DCHECK_LT(d, dims());\n DoStuffWith(dims_[d]);\n}\n```\n\nSince in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array.\n\n### Patches\n\nWe have patched the issue in eccb7ec454e6617738554a255d77f08e60ee0808 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.\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 in #42105",
"id": "GHSA-rrfp-j2mp-hq9c",
"modified": "2024-10-30T21:22:54Z",
"published": "2020-11-13T17:13:04Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15265"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/issues/42105"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-295.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-330.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-138.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Segfault in `tf.quantization.quantize_and_dequantize`"
}
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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.
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