CVE-2021-41195 Crash in `tf.math.segment_*` operations
An attacker can cause a denial of service in TensorFlow by triggering an integer overflow in segment operations, leading to an application crash.
- 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-2021-41195?
CVE-2021-41195 is a medium-severity 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 the implementation of `tf.math.segment_*` operations results in a `CHECK`-fail related abort (and denial of service) if a segment id in `segment_ids` is large. This is similar to CVE-2021-29584 (and similar other reported vulnerabilities in TensorFlow, localized to specific APIs): the implementation (both on CPU and GPU) computes the output shape using `AddDim`. However, if the number of elements in the tensor overflows an `int64_t` value, `AddDim` results in a `CHECK` failure which provokes a `std::abort`. Instead, code should use `AddDimWithStatus`. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit 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-190
Which versions are affected by CVE-2021-41195?
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 | All versions | 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-2021-41195?
Upgrade tensorflow to a fixed version for your release line: 2.4.4, 2.5.2 or 2.6.1.
Is CVE-2021-41195 being exploited?
There is no known exploitation of CVE-2021-41195 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-2021-41195, GHSA-cq76-mxrc-vchh, PYSEC-2021-842, PYSEC-2021-844, PYSEC-2021-846.