GHSA-4G9F-63RX-5CW4
Vulnerability from github – Published: 2020-09-25 18:28 – Updated: 2024-10-28 20:05Impact
The tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor.
However, the eager runtime traverses all tensors in the output: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/common_runtime/eager/kernel_and_device.cc#L308-L313
Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault
Patches
We have patched the issue in da8558533d925694483d2c136a9220d6d49d843c and will release a patch release for all affected versions.
We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
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.
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"aliases": [
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"database_specific": {
"cwe_ids": [
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"CWE-476"
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"github_reviewed": true,
"github_reviewed_at": "2020-09-25T16:14:42Z",
"nvd_published_at": "2020-09-25T19:15:00Z",
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"details": "### Impact\nThe [`tf.raw_ops.Switch`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Switch) operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor.\n\nHowever, the eager runtime traverses all tensors in the output:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/common_runtime/eager/kernel_and_device.cc#L308-L313\n\nSince only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault\n\n### Patches\nWe have patched the issue in da8558533d925694483d2c136a9220d6d49d843c and will release a patch release for all affected versions.\n\nWe recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.\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-4g9f-63rx-5cw4",
"modified": "2024-10-28T20:05:37Z",
"published": "2020-09-25T18:28:14Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4g9f-63rx-5cw4"
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{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15190"
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{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/da8558533d925694483d2c136a9220d6d49d843c"
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{
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-270.yaml"
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-305.yaml"
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-113.yaml"
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"url": "https://github.com/tensorflow/tensorflow"
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"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
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{
"type": "WEB",
"url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
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"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
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"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
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"summary": "Segfault in Tensorflow"
}
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.