Google TensorFlow up to 2.7.1/2.8.0/2.9.0 QuantizedAvgPool min_input/max_input denial of service

CVSS Meta Temp Score
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CTI Interest Score
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5.7$0-$5k0.00

Summaryinfo

A vulnerability identified as problematic has been detected in Google TensorFlow up to 2.7.1/2.8.0/2.9.0. Affected is the function QuantizedAvgPool. The manipulation of the argument min_input/max_input leads to denial of service. This vulnerability is traded as CVE-2022-35966. It is possible to initiate the attack remotely. There is no exploit available. You should upgrade the affected component.

Detailsinfo

A vulnerability was found in Google TensorFlow up to 2.7.1/2.8.0/2.9.0 (Artificial Intelligence Software). It has been rated as problematic. This issue affects the function QuantizedAvgPool. The manipulation of the argument min_input/max_input with an unknown input leads to a denial of service vulnerability. Using CWE to declare the problem leads to CWE-404. The product does not release or incorrectly releases a resource before it is made available for re-use. Impacted is availability. The summary by CVE is:

TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

The weakness was shared 09/17/2022 as GHSA-4w68-4x85-mjj9. The advisory is shared at github.com. The identification of this vulnerability is CVE-2022-35966 since 07/15/2022. Technical details are known, but no exploit is available. MITRE ATT&CK project uses the attack technique T1499 for this issue.

Upgrading to version 2.7.2, 2.8.1, 2.9.1 or 2.10.0 eliminates this vulnerability. Applying the patch 7cdf9d4d2083b739ec81cfdace546b0c99f50622 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

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Productinfo

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Version

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CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 5.7
VulDB Meta Temp Score: 5.7

VulDB Base Score: 3.7
VulDB Temp Score: 3.6
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 7.5
NVD Vector: 🔍

CNA Base Score: 5.9
CNA Vector (GitHub, Inc.): 🔍

CVSSv2info

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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

Exploitinginfo

Class: Denial of service
CWE: CWE-404
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Status: Not defined

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔍

Upgrade: TensorFlow 2.7.2/2.8.1/2.9.1/2.10.0
Patch: 7cdf9d4d2083b739ec81cfdace546b0c99f50622

Timelineinfo

07/15/2022 🔍
09/17/2022 +64 days 🔍
09/17/2022 +0 days 🔍
10/19/2022 +32 days 🔍

Sourcesinfo

Vendor: google.com

Advisory: GHSA-4w68-4x85-mjj9
Status: Confirmed

CVE: CVE-2022-35966 (🔍)
GCVE (CVE): GCVE-0-2022-35966
GCVE (VulDB): GCVE-100-208889

Entryinfo

Created: 09/17/2022 08:10
Updated: 10/19/2022 14:37
Changes: 09/17/2022 08:10 (55), 10/19/2022 14:37 (11)
Complete: 🔍
Cache ID: 216::103

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

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