CVE-2021-29609

low-risk
Published 2021-05-14

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Do I need to act?

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0.05% chance of exploitation
EPSS score — low exploit probability
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Not on CISA KEV list
No confirmed active exploitation reported to CISA
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Patch status unknown
Check vendor advisories for fix availability and mitigation guidance
5
CVSS 5.3/10 Medium
LOCAL / HIGH complexity

Affected Products (1)

Affected Vendors

19
/ 100
low-risk
Severity 14/34 · Moderate
Exploitability 0/34 · Minimal
Exposure 5/34 · Minimal