CVE-2021-29583 Heap buffer overflow and undefined behavior in `FusedBatchNorm`

Low 2.5 Published Updated

Heap buffer overflow and null pointer dereference in TensorFlow's FusedBatchNorm allow attackers to cause crashes or potentially execute code.

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-2021-29583?

CVE-2021-29583 is a low-severity memory corruption 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. The implementation of `tf.raw_ops.FusedBatchNorm` is vulnerable to a heap buffer overflow. If the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers. The implementation(https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that `scale`, `offset`, `mean` and `variance` (the last two only when required) all have the same number of elements as the number of channels of `x`. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary. If the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Weakness: CWE-125, CWE-476

Which versions are affected by CVE-2021-29583?

28 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.

PackageAffectedFixed in
tensorflow BitnamiAll versions2.1.4, 2.2.3, 2.3.3, 2.4.2
tensorflow PyPIAll versions2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3
tensorflow PyPIAll versions2.1.4
tensorflow PyPIAll versions2.1.4
tensorflow PyPIFrom 2.2.02.2.3
tensorflow PyPIFrom 2.2.02.2.3
22 more packages
tensorflow PyPIFrom 2.3.02.3.3
tensorflow PyPIFrom 2.3.02.3.3
tensorflow PyPIFrom 2.4.02.4.2
tensorflow PyPIFrom 2.4.02.4.2
tensorflow-cpu PyPIAll versions2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3
tensorflow-cpu PyPIAll versions2.1.4
tensorflow-cpu PyPIAll versions2.1.4
tensorflow-cpu PyPIFrom 2.2.02.2.3
tensorflow-cpu PyPIFrom 2.2.02.2.3
tensorflow-cpu PyPIFrom 2.3.02.3.3
tensorflow-cpu PyPIFrom 2.3.02.3.3
tensorflow-cpu PyPIFrom 2.4.02.4.2
tensorflow-cpu PyPIFrom 2.4.02.4.2
tensorflow-gpu PyPIAll versions2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3
tensorflow-gpu PyPIAll versions2.1.4
tensorflow-gpu PyPIAll versions2.1.4
tensorflow-gpu PyPIFrom 2.2.02.2.3
tensorflow-gpu PyPIFrom 2.2.02.2.3
tensorflow-gpu PyPIFrom 2.3.02.3.3
tensorflow-gpu PyPIFrom 2.3.02.3.3
tensorflow-gpu PyPIFrom 2.4.02.4.2
tensorflow-gpu PyPIFrom 2.4.02.4.2

Products include Google Tensorflow.

How do I fix CVE-2021-29583?

Upgrade tensorflow to a fixed version for your release line: 2.1.4, 2.2.3, 2.3.3 or 2.4.2.

Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.

Is CVE-2021-29583 being exploited?

There is no known exploitation of CVE-2021-29583 in the wild and no public exploit code.

All Google Tensorflow vulnerabilities

Sources

Also known as BIT-tensorflow-2021-29583, GHSA-9xh4-23q4-v6wr, PYSEC-2021-220, PYSEC-2021-511, PYSEC-2021-709.

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