GHSA-Q4QF-3FC6-8X34
Vulnerability from github – Published: 2020-09-25 18:28 – Updated: 2024-10-30 21:12
VLAI?
Summary
Segfault and data corruption in tensorflow-lite
Details
Impact
To mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72
If the DCHECK does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.
Patches
We have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a and will release patch releases for all versions between 1.15 and 2.3.
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.
Severity ?
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"aliases": [
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"database_specific": {
"cwe_ids": [
"CWE-119",
"CWE-787"
],
"github_reviewed": true,
"github_reviewed_at": "2020-09-25T17:55:41Z",
"nvd_published_at": "2020-09-25T19:15:00Z",
"severity": "MODERATE"
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"details": "### Impact\nTo mimic Python\u0027s indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72\n\nIf the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.\n### Patches\nWe have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a and will release patch releases for all versions between 1.15 and 2.3.\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-q4qf-3fc6-8x34",
"modified": "2024-10-30T21:12:25Z",
"published": "2020-09-25T18:28:43Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15207"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/2d88f470dea2671b430884260f3626b1fe99830a"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-287.yaml"
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{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-322.yaml"
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{
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-130.yaml"
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{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
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{
"type": "WEB",
"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"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:H/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:N/SI:H/SA:H",
"type": "CVSS_V4"
}
],
"summary": "Segfault and data corruption in tensorflow-lite"
}
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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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