Description
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Affected products
| Vendor | Product | Affected | Fixed |
|---|---|---|---|
| tensorflow | tensorflow | < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2, >= 2.2.0, < 2.2.1, >= 2.3.0, < 2.3.1 | — |
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.
openSUSE
Security tracker ↗| Release | Package | Fixed in | Advisory |
|---|---|---|---|
| openSUSE Leap 15.2 | tensorflow2 +3 | 2.1.2-lp152.7.3.1 | openSUSE-SU-2020:1766-1 |
Affected packages
| Ecosystem | Package | Affected | Fixed | Record |
|---|---|---|---|---|
| PyPI | tensorflow | < 1.15.4 | 1.15.4 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow | >= 2.0.0, < 2.0.3 | 2.0.3 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow | >= 2.1.0, < 2.1.2 | 2.1.2 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow | >= 2.2.0, < 2.2.1 | 2.2.1 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow | >= 2.3.0, < 2.3.1 | 2.3.1 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow | < 1.15.4 · >= 2.0.0, < 2.0.3 · >= 2.1.0, < 2.1.2 · >= 2.2.0, < 2.2.1 · >= 2.3.0, < 2.3.1 | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 | PYSEC-2020-113 |
| PyPI | tensorflow-cpu | < 1.15.4 | 1.15.4 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-cpu | >= 2.0.0, < 2.0.3 | 2.0.3 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-cpu | >= 2.1.0, < 2.1.2 | 2.1.2 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-cpu | >= 2.2.0, < 2.2.1 | 2.2.1 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-cpu | >= 2.3.0, < 2.3.1 | 2.3.1 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-cpu | < 1.15.4 · >= 2.0.0, < 2.0.3 · >= 2.1.0, < 2.1.2 · >= 2.2.0, < 2.2.1 · >= 2.3.0, < 2.3.1 | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 | PYSEC-2020-270 |
| PyPI | tensorflow-gpu | < 1.15.4 | 1.15.4 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-gpu | >= 2.0.0, < 2.0.3 | 2.0.3 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-gpu | >= 2.1.0, < 2.1.2 | 2.1.2 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-gpu | >= 2.2.0, < 2.2.1 | 2.2.1 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-gpu | >= 2.3.0, < 2.3.1 | 2.3.1 | GHSA-4g9f-63rx-5cw4 |
| PyPI | tensorflow-gpu | < 1.15.4 · >= 2.0.0, < 2.0.3 · >= 2.1.0, < 2.1.2 · >= 2.2.0, < 2.2.1 · >= 2.3.0, < 2.3.1 | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 | PYSEC-2020-305 |
Advisories 1
- openSUSE-SU-2020:1766-1 Security update for tensorflow2 SUSE / openSUSE Security Updates · Feb 4, 2026