Description
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. 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.
Affected products
| Vendor | Product | Affected | Fixed |
|---|---|---|---|
| tensorflow | tensorflow | >= 2.5.0, < 2.5.1, >= 2.4.0, < 2.4.3, < 2.3.4 | — |
Fixed in Linux distributions
Distributions backport fixes, so the version that fixes this vulnerability differs per release — upgrade to at least the version shown. From the distributions' security trackers and advisories.
SUSE
Security tracker ↗| Release | Package | Fixed in | Advisory |
|---|---|---|---|
| SUSE Package Hub 15 SP3 | bazel-skylib1.0.3 | 1.0.3-bp153.2.1 | openSUSE-SU-2022:10014-1 |
| SUSE Package Hub 15 SP3 | bazel3.7 | 3.7.2-bp153.4.1 | openSUSE-SU-2022:10014-1 |
| SUSE Package Hub 15 SP3 | tensorflow2 +3 | 2.6.0-bp153.2.3.1 | openSUSE-SU-2022:10014-1 |
openSUSE
Security tracker ↗| Release | Package | Fixed in | Advisory |
|---|---|---|---|
| openSUSE Leap 15.3 | bazel-skylib1.0.3 | 1.0.3-bp153.2.1 | openSUSE-SU-2022:10014-1 |
| openSUSE Leap 15.3 | bazel3.7 | 3.7.2-bp153.4.1 | openSUSE-SU-2022:10014-1 |
| openSUSE Leap 15.3 | tensorflow2 +3 | 2.6.0-bp153.2.3.1 | openSUSE-SU-2022:10014-1 |
Affected packages
| Ecosystem | Package | Affected | Fixed | Record |
|---|---|---|---|---|
| PyPI | tensorflow | < 2.3.4 | 2.3.4 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow | >= 2.4.0, < 2.4.3 | 2.4.3 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow | >= 2.5.0, < 2.5.1 | 2.5.1 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow | >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 | 2.3.4, 2.4.3 | PYSEC-2021-294 |
| PyPI | tensorflow-cpu | < 2.3.4 | 2.3.4 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow-cpu | >= 2.4.0, < 2.4.3 | 2.4.3 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow-cpu | >= 2.5.0, < 2.5.1 | 2.5.1 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow-cpu | >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 | 2.3.4, 2.4.3 | PYSEC-2021-585 |
| PyPI | tensorflow-gpu | < 2.3.4 | 2.3.4 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow-gpu | >= 2.4.0, < 2.4.3 | 2.4.3 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow-gpu | >= 2.5.0, < 2.5.1 | 2.5.1 | GHSA-5hj3-vjjf-f5m7 |
| PyPI | tensorflow-gpu | >= 2.3.0, < 2.3.4 · >= 2.4.0, < 2.4.3 | 2.3.4, 2.4.3 | PYSEC-2021-783 |
Advisories 1
- openSUSE-SU-2022:10014-1 Security update for tensorflow2 SUSE / openSUSE Security Updates · Feb 4, 2026