GHSA-X9J7-X98R-R4W2
Vulnerability from github – Published: 2020-09-25 18:28 – Updated: 2024-10-28 14:55
VLAI?
Summary
Segmentation fault in tensorflow-lite
Details
Impact
If a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption.
Patches
We have patched the issue in d58c96946b 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.
Workarounds
A potential workaround would be to add a custom Verifier to the model loading code to ensure that no operator reuses tensors as both inputs and outputs. Care should be taken to check all types of inputs (i.e., constant or variable tensors as well as optional tensors).
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 discovered from a variant analysis of GHSA-cvpc-8phh-8f45.
Severity ?
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"aliases": [
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],
"database_specific": {
"cwe_ids": [
"CWE-20",
"CWE-787"
],
"github_reviewed": true,
"github_reviewed_at": "2020-09-25T18:15:49Z",
"nvd_published_at": "2020-09-25T19:15:00Z",
"severity": "HIGH"
},
"details": "### Impact\nIf a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption.\n\n### Patches\nWe have patched the issue in d58c96946b 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### Workarounds\nA potential workaround would be to add a custom `Verifier` to the model loading code to ensure that no operator reuses tensors as both inputs and outputs. Care should be taken to check all types of inputs (i.e., constant or variable tensors as well as optional tensors).\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 discovered from a variant analysis of [GHSA-cvpc-8phh-8f45](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvpc-8phh-8f45).",
"id": "GHSA-x9j7-x98r-r4w2",
"modified": "2024-10-28T14:55:40Z",
"published": "2020-09-25T18:28:51Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x9j7-x98r-r4w2"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15210"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/094329d0dcb8290bed2b1ee420934971f422c86d"
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{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/1c8709b437fec10875b0cf271889afec9bbf582e"
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"url": "https://github.com/tensorflow/tensorflow/commit/d58c96946b2880991d63d1dacacb32f0a4dfa453"
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"url": "https://github.com/tensorflow/tensorflow/commit/f4159ccef23d11eb58ee4263beaaeac1be3343c7"
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"url": "https://github.com/tensorflow/tensorflow/commit/f50a14b00560a383865c2273e4a9094add3888d5"
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{
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-290.yaml"
},
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-325.yaml"
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-133.yaml"
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{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
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{
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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:H/PR:N/UI:N/S:U/C:N/I:L/A:H",
"type": "CVSS_V3"
},
{
"score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
}
],
"summary": "Segmentation fault 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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