CVE-2021-29571 Memory corruption in `DrawBoundingBoxesV2`

Medium 4.5 Published Updated

Attackers can trigger out-of-bounds writes in TensorFlow's DrawBoundingBoxesV2 operation via crafted inputs, leading to memory corruption and potential code execution.

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-2021-29571?

CVE-2021-29571 is a medium-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.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. 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-787

Which versions are affected by CVE-2021-29571?

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-2021-29571?

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-2021-29571 being exploited?

There is no known exploitation of CVE-2021-29571 in the wild and no public exploit code.

All Google Tensorflow vulnerabilities

Sources

Also known as BIT-tensorflow-2021-29571, GHSA-whr9-vfh2-7hm6, PYSEC-2021-208, PYSEC-2021-499, PYSEC-2021-697.

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