CVE-2021-29521 Segfault in SparseCountSparseOutput
An attacker can cause a segmentation fault and crash the application by providing a negative dense shape to the SparseCountSparseOutput 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-2021-29521?
CVE-2021-29521 is a low-severity denial of service vulnerability in Google Tensorflow, published on 14 May 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. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.
Weakness: CWE-131
Which versions are affected by CVE-2021-29521?
16 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 | 2.3.3, 2.4.2 |
tensorflow PyPI | From 2.3.0 | 2.3.3, 2.4.2 |
tensorflow PyPI | From 2.3.0 | 2.3.3 |
tensorflow PyPI | From 2.3.0 | 2.3.3 |
tensorflow PyPI | From 2.4.0 | 2.4.2 |
tensorflow PyPI | From 2.4.0 | 2.4.2 |
10 more packages
tensorflow-cpu PyPI | From 2.3.0 | 2.3.3, 2.4.2 |
tensorflow-cpu PyPI | From 2.3.0 | 2.3.3 |
tensorflow-cpu PyPI | From 2.3.0 | 2.3.3 |
tensorflow-cpu PyPI | From 2.4.0 | 2.4.2 |
tensorflow-cpu PyPI | From 2.4.0 | 2.4.2 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.3, 2.4.2 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.3 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.3 |
tensorflow-gpu PyPI | From 2.4.0 | 2.4.2 |
tensorflow-gpu PyPI | From 2.4.0 | 2.4.2 |
Products include Google Tensorflow.
How do I fix CVE-2021-29521?
Upgrade tensorflow to a fixed version for your release line: 2.3.3 or 2.4.2.
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-2021-29521 being exploited?
There is no known exploitation of CVE-2021-29521 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-2021-29521, GHSA-hr84-fqvp-48mm, PYSEC-2021-158, PYSEC-2021-449, PYSEC-2021-647.