7.7

CVE-2021-37647: google tensorflow NULL Pointer Dereference

CVSS: 7.7v3.1HighModified
AliasesGHSA-c5x2-p679-95wcBIT-tensorflow-2021-37647PYSEC-2021-269
Published 12-08-2021Last modified 04-08-2024
Open JSON

Vulnerability summary

CVE-2021-37647 is a high (CVSS 7.7) NULL Pointer Dereference vulnerability in google tensorflow. EPSS estimates a 0.16% chance of exploitation in the next 30 days, higher than 4.7% of scored vulnerabilities.

Overall risk
31/100
0100
Medium · default modelHow is this calculated?
CVSS score
7.7/10
010
High · v3.1 (CVE.org)
EPSS score
0.16%
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
OPENSUSE-SU-2022:10014-1

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. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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

0.16%

Chance of exploitation in the next 30 days

Percentile

5%

Versus all other CVEs

30-day change

0.00 pp

From 0.16% on 19-09-2026

19-09-202619-10-2026
EPSS score
0.16%

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 | < 02cc160e29d20631de3859c6653184e3f876b9d7 | ≥ 2.4.0, < 2.4.3
  • tensorflow-cpu< 2.3.4 | ≥ 2.5.0, < 2.5.1 | < 02cc160e29d20631de3859c6653184e3f876b9d7 | ≥ 2.4.0, < 2.4.3
  • tensorflow-gpu< 2.3.4 | ≥ 2.5.0, < 2.5.1 | < 02cc160e29d20631de3859c6653184e3f876b9d7 | ≥ 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

7 links