CVE-2022-217316.5MediumCWE-843

CVE-2022-21731: Type confusion leading to segfault in Tensorflow

Google · Tensorflow

Affected: Google Tensorflow · Exploitation: unlikely (under 1%)

Not in CyberSIXT coverage yet: no article names this CVE. This page shows the public record.

0.8%probability of exploitation in the next 30 days

58th percentile

050100

Higher than 58% of scored CVEs

6.5MediumCVSS 3.1

LowMediumHighCrit.

DescriptionCVE.org

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

On the Atlas

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Open the Atlas

Exploitation: Unlikely (under 1%). EPSS under 1%, or no score yet.
CISA KEV: Not listed
Public check: No public nuclei template
Weakness: Type Confusion · Memory Corruption
Vendor: Google
Published: February 2022
Band: Unlikely (under 1%), February 2022

CoverageNo articles yet

No CyberSIXT article names CVE-2022-21731 yet, so there is no coverage timeline, action brief or change log for it. Everything on this page comes from the public CVE record, CISA KEV, EPSS and the nuclei template index. Search the archive or see the CVEs in the news.