CVE-2020-15197 Denial of Service in Tensorflow
Attackers can cause a crash in TensorFlow serving installations by providing invalid sparse tensor inputs, leading to denial of service.
- Exploited in the wild
- Not known
- Login needed
- Any signed-in user
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2020-15197?
CVE-2020-15197 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 25 Sep 2020. Any signed-in user can exploit it over the network, with no action from the victim.
Official description
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Which versions are affected by CVE-2020-15197?
10 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 | 2.3.1 |
tensorflow PyPI | All versions | 2.3.1 |
tensorflow PyPI | From 2.3.0 | 2.3.1 |
tensorflow PyPI | From 2.3.0 | 2.3.1 |
tensorflow-cpu PyPI | All versions | 2.3.1 |
tensorflow-cpu PyPI | From 2.3.0 | 2.3.1 |
4 more packages
tensorflow-cpu PyPI | From 2.3.0 | 2.3.1 |
tensorflow-gpu PyPI | All versions | 2.3.1 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.1 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.1 |
Products include Google Tensorflow.
How do I fix CVE-2020-15197?
Upgrade tensorflow to 2.3.1 or later.
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-2020-15197 being exploited?
There is no known exploitation of CVE-2020-15197 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-2020-15197, GHSA-qc53-44cj-vfvx, PYSEC-2020-120, PYSEC-2020-277, PYSEC-2020-312.