CVE-2021-29530 Invalid validation in `SparseMatrixSparseCholesky`

Low 2.5 Published Updated

An attacker can cause a denial of service via null pointer dereference in TensorFlow's SparseMatrixSparseCholesky operation due to improper input validation.

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-2021-29530?

CVE-2021-29530 is a low-severity 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. An attacker can trigger a null pointer dereference by providing an invalid `permutation` to `tf.raw_ops.SparseMatrixSparseCholesky`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/kernels/sparse/sparse_cholesky_op.cc#L85-L86) fails to properly validate the input arguments. Although `ValidateInputs` is called and there are checks in the body of this function, the code proceeds to the next line in `ValidateInputs` since `OP_REQUIRES`(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/framework/op_requires.h#L41-L48) is a macro that only exits the current function. Thus, the first validation condition that fails in `ValidateInputs` will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check `context->status()` or to convert `ValidateInputs` to return a `Status`. 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-476

Which versions are affected by CVE-2021-29530?

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 versions2.1.4, 2.2.3, 2.3.3, 2.4.2
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 versions2.1.4, 2.2.3, 2.3.3, 2.4.2
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 versions2.1.4, 2.2.3, 2.3.3, 2.4.2
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-2021-29530?

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

Is CVE-2021-29530 being exploited?

There is no known exploitation of CVE-2021-29530 in the wild and no public exploit code.

All Google Tensorflow vulnerabilities

Sources

Also known as BIT-tensorflow-2021-29530, GHSA-xcwj-wfcm-m23c, PYSEC-2021-167, PYSEC-2021-458, PYSEC-2021-656.

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