CVE-2021-37668 Division by zero in TensorFlow Lite `tf.raw_ops.UnravelIndex`
An attacker can cause a denial of service in TensorFlow Lite applications by triggering a division by zero error in the UnravelIndex operation.
- 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-2021-37668?
CVE-2021-37668 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 12 Aug 2021. It can only be exploited from the same machine or local network, with no action from the victim.
Official description
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0. We have patched the issue in GitHub commit a776040a5e7ebf76eeb7eb923bf1ae417dd4d233. 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.
Weakness: CWE-369
Which versions are affected by CVE-2021-37668?
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 2.3.0 | 2.3.4, 2.4.3, 2.5.1 |
tensorflow PyPI | All versions | 2.3.4 |
tensorflow PyPI | All versions | 2.3.4 |
tensorflow PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
tensorflow PyPI | From 2.4.0 | 2.4.3 |
tensorflow PyPI | From 2.4.0 | 2.4.3 |
16 more packages
tensorflow PyPI | From 2.5.0 | 2.5.1 |
tensorflow PyPI | From 2.5.0 | 2.5.1 |
tensorflow-cpu PyPI | All versions | 2.3.4 |
tensorflow-cpu PyPI | All versions | 2.3.4 |
tensorflow-cpu PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
tensorflow-cpu PyPI | From 2.4.0 | 2.4.3 |
tensorflow-cpu PyPI | From 2.4.0 | 2.4.3 |
tensorflow-cpu PyPI | From 2.5.0 | 2.5.1 |
tensorflow-cpu PyPI | From 2.5.0 | 2.5.1 |
tensorflow-gpu PyPI | All versions | 2.3.4 |
tensorflow-gpu PyPI | All versions | 2.3.4 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
tensorflow-gpu PyPI | From 2.4.0 | 2.4.3 |
tensorflow-gpu PyPI | From 2.4.0 | 2.4.3 |
tensorflow-gpu PyPI | From 2.5.0 | 2.5.1 |
tensorflow-gpu PyPI | From 2.5.0 | 2.5.1 |
Products include Google Tensorflow.
How do I fix CVE-2021-37668?
Upgrade tensorflow to a fixed version for your release line: 2.3.4, 2.4.3 or 2.5.1.
Upgrade, then put limits on request size, rate and nesting depth so one client cannot exhaust the service. More about Denial of service.
Is CVE-2021-37668 being exploited?
There is no known exploitation of CVE-2021-37668 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-2021-37668, GHSA-2wmv-37vq-52g5, PYSEC-2021-290, PYSEC-2021-581, PYSEC-2021-779.