CVE-2022-35967 — Improper Input Validation in Tensorflow

CWE-20 — Improper Input Validation5 documents5 sources
Severity
7.5HIGHNVD
CNA5.9
EPSS
0.1%
top 80.05%
CISA KEV
Not in KEV
Exploit
No known exploits
Affected products
3
TensorflowGoogle TensorflowIntel Optimization FOR Tensorflow
Timeline
PublishedSep 16

Description

TensorFlow is an open source platform for machine learning. If `QuantizedAdd` 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 49b3824d83af706df0ad07e4e677d88659756d89. 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…

CVSS vector

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HExploitability: 3.9 | Impact: 3.6

Affected Packages3 packages

▶NVDgoogle/tensorflow2.7.0 — 2.7.2+3
▶CVEListV5tensorflow/tensorflow< 2.7.2+2
▶PyPIintel/optimization_for_tensorflow2.8.0 — 2.8.1+2

Patches

Patch: github.com ↗Patch: github.com ↗Patch: github.com ↗

🔴Vulnerability Details

3
CVEList
Segfault in `QuantizedAdd` in TensorFlow↗2022-09-16
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GHSA
TensorFlow vulnerable to segfault in `QuantizedAdd`↗2022-09-16
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OSV
TensorFlow vulnerable to segfault in `QuantizedAdd`↗2022-09-16
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📋Vendor Advisories

1
Debian
CVE-2022-35967: tensorflow - TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is...↗2022
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CVE-2022-35967 — Improper Input Validation | cvebase