7.8

CVE-2021-37689: google tensorflow NULL Pointer Dereference

CVSS: 7.8v3.1HighModified
AliasesGHSA-wf5p-c75w-w3whBIT-tensorflow-2021-37689PYSEC-2021-311
Published 12-08-2021Last modified 04-08-2024

Vulnerability summary

CVE-2021-37689 is a high (CVSS 7.8) NULL Pointer Dereference vulnerability in google tensorflow. EPSS estimates a 0.17% chance of exploitation in the next 30 days, higher than 5.3% of scored vulnerabilities.

Overall risk
31/100
0100
Medium · default modelHow is this calculated?
CVSS score
7.8/10
010
High · v3.1 (CVE.org)
EPSS score
0.17%
0%100%
Low · 0.00 pp in 30 days
KEVNot listedIn no KEV catalog
RansomwareNone recordedNo known use recorded
Public exploits0No public exploits recorded

Advisory lineage

Upstream 0 · Downstream 1 · Related 1

Timeline

  1. 12-08-2021
    PublishedVulnerability first disclosed.
  2. 04-08-2024
    Last modifiedVulnerability information updated.

Description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

CVSS metrics

5 scores · 3 sources · 3 versions

EPSS trend

Probability

0.17%

Chance of exploitation in the next 30 days

Percentile

5%

Versus all other CVEs

30-day change

0.00 pp

From 0.17% on 18-09-2026

18-09-202618-10-2026
EPSS score
0.17%

Known exploited

Compare KEV catalogs

Not in any of the 3 tracked catalogs.

Public exploits

0 found

No public exploits indexed.

Weaknesses

CWE · root cause

Affected systems

PyPI3 products
  • tensorflow< 2.3.4 | ≥ 2.5.0, < 2.5.1 | < d6b57f461b39fd1aa8c1b870f1b974aac3554955 | ≥ 2.4.0, < 2.4.3
  • tensorflow-cpu< 2.3.4 | ≥ 2.5.0, < 2.5.1 | < d6b57f461b39fd1aa8c1b870f1b974aac3554955 | ≥ 2.4.0, < 2.4.3
  • tensorflow-gpu< 2.3.4 | ≥ 2.5.0, < 2.5.1 | < d6b57f461b39fd1aa8c1b870f1b974aac3554955 | ≥ 2.4.0, < 2.4.3
Google1 product
  • tensorflow≥ 2.3.0, < 2.3.4 | ≥ 2.4.0, < 2.4.3 | 2.5.0 | 2.6.0:rc0 | 2.6.0:rc1 | 2.6.0:rc2
Tensorflow1 product
  • tensorflow≥ 2.5.0, < 2.5.1 | ≥ 2.4.0, < 2.4.3 | < 2.3.4

3 vendors · 5 products

References

8 links