CVE-2021-37664 Heap OOB in boosted trees in TensorFlow
An attacker can read out-of-bounds heap memory in TensorFlow's boosted trees implementation by sending specially crafted arguments.
- 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-2021-37664?
CVE-2021-37664 is a high-severity memory corruption 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 read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `BoostedTreesSparseCalculateBestFeatureSplit`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) needs to validate that each value in `stats_summary_indices` is in range. We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378. 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-125
Which versions are affected by CVE-2021-37664?
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-2021-37664?
Upgrade tensorflow to a fixed version for your release line: 2.3.4, 2.4.3 or 2.5.1.
Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.
Is CVE-2021-37664 being exploited?
There is no known exploitation of CVE-2021-37664 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-2021-37664, GHSA-r4c4-5fpq-56wg, PYSEC-2021-286, PYSEC-2021-577, PYSEC-2021-775.