CVE-2021-41206 Incomplete validation of shapes in multiple TF ops
Missing shape validation in TensorFlow operations allows attackers to trigger memory corruption, leading to crashes or potential code execution.
- Exploited in the wild
- Not known
- Login needed
- Any signed-in user
- Attackable
- Local or same network only
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2021-41206?
CVE-2021-41206 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 5 Nov 2021. It can only be exploited from the same machine or local network, with no action from the victim.
Official description
TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Weakness: CWE-354
Which versions are affected by CVE-2021-41206?
22 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.
| Package | Affected | Fixed in |
|---|---|---|
tensorflow Bitnami | From 2.4.0 | 2.4.4, 2.5.2, 2.6.1 |
tensorflow PyPI | All versions | 2.4.4, 2.5.2, 2.6.1 |
tensorflow PyPI | All versions | 2.4.4 |
tensorflow PyPI | All versions | 2.4.4 |
tensorflow PyPI | From 2.5.0 | 2.5.2 |
tensorflow PyPI | From 2.5.0 | 2.5.2 |
16 more packages
tensorflow PyPI | From 2.6.0 | 2.6.1 |
tensorflow PyPI | From 2.6.0 | 2.6.1 |
tensorflow-cpu PyPI | All versions | 2.4.4, 2.5.2, 2.6.1 |
tensorflow-cpu PyPI | All versions | 2.4.4 |
tensorflow-cpu PyPI | All versions | 2.4.4 |
tensorflow-cpu PyPI | From 2.5.0 | 2.5.2 |
tensorflow-cpu PyPI | From 2.5.0 | 2.5.2 |
tensorflow-cpu PyPI | From 2.6.0 | 2.6.1 |
tensorflow-cpu PyPI | From 2.6.0 | 2.6.1 |
tensorflow-gpu PyPI | All versions | 2.4.4, 2.5.2, 2.6.1 |
tensorflow-gpu PyPI | All versions | 2.4.4 |
tensorflow-gpu PyPI | All versions | 2.4.4 |
tensorflow-gpu PyPI | From 2.5.0 | 2.5.2 |
tensorflow-gpu PyPI | From 2.5.0 | 2.5.2 |
tensorflow-gpu PyPI | From 2.6.0 | 2.6.1 |
tensorflow-gpu PyPI | From 2.6.0 | 2.6.1 |
Products include Google Tensorflow.
How do I fix CVE-2021-41206?
Upgrade tensorflow to a fixed version for your release line: 2.4.4, 2.5.2 or 2.6.1.
Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.
Is CVE-2021-41206 being exploited?
There is no known exploitation of CVE-2021-41206 in the wild and no public exploit code.
Other vulnerabilities in Google Tensorflow
- CVE-2023-25668 TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
- CVE-2018-7575 Integer Overflow or Wraparound in Google TensorFlow
- CVE-2021-37678 Arbitrary code execution due to YAML deserialization
- CVE-2021-35958 Path traversal in n/a
- CVE-2020-15202 Integer truncation in Shard API usage
Sources
Also known as BIT-tensorflow-2021-41206, GHSA-pgcq-h79j-2f69, PYSEC-2021-843, PYSEC-2021-845, PYSEC-2021-847.