CVE-2022-29206

Missing validation results in undefined behavior in `SparseTensorDenseAdd

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Attribution

This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.

The implementation of tf.raw_ops.SparseTensorDenseAdd does not fully validate the input arguments:

import tensorflow as tf

a_indices = tf.constant(0, shape=[17, 2], dtype=tf.int64)
a_values = tf.constant([], shape=[0], dtype=tf.float32)
a_shape = tf.constant([6, 12], shape=[2], dtype=tf.int64)

b = tf.constant(-0.223668531, shape=[6, 12], dtype=tf.float32)

tf.raw_ops.SparseTensorDenseAdd(
    a_indices=a_indices, a_values=a_values, a_shape=a_shape, b=b)

In this case, a reference gets bound to a nullptr during kernel execution. This is UB.

The application does not adequately validate input before processing it, allowing unexpected values to reach sensitive code paths. Typical impact: varies by context: data corruption, logic bypass, or denial of service.

CVE-2022-29206 has a CVSS score of 5.5 (Medium). The vector is requires local access, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (2.6.4, 2.7.2, 2.8.1); upgrading removes the vulnerable code path.

Kodem intelligence

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We have patched the issue in GitHub commit 11ced8467eccad9c7cb94867708be8fa5c66c730.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.

1. What is CVE-2022-29206? CVE-2022-29206 is a medium-severity improper input validation vulnerability in tensorflow (pip), affecting versions < 2.6.4. It is fixed in 2.6.4, 2.7.2, 2.8.1. The application does not adequately validate input before processing it, allowing unexpected values to reach sensitive code paths.
2. How severe is CVE-2022-29206? CVE-2022-29206 has a CVSS score of 5.5 (Medium). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
3. Which packages are affected by CVE-2022-29206?
   • tensorflow (pip) (versions < 2.6.4)
   • tensorflow-cpu (pip) (versions < 2.6.4)
   • tensorflow-gpu (pip) (versions < 2.6.4)
4. Is there a fix for CVE-2022-29206? Yes. CVE-2022-29206 is fixed in 2.6.4, 2.7.2, 2.8.1. Upgrade to this version or later.
5. Is CVE-2022-29206 exploitable, and should I be worried? Whether CVE-2022-29206 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
6. What actually determines whether CVE-2022-29206 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
7. How do I fix CVE-2022-29206?
   • Upgrade tensorflow to 2.6.4 or later
   • Upgrade tensorflow to 2.7.2 or later
   • Upgrade tensorflow to 2.8.1 or later
   • Upgrade tensorflow-cpu to 2.6.4 or later
   • Upgrade tensorflow-cpu to 2.7.2 or later
   • Upgrade tensorflow-cpu to 2.8.1 or later
   • Upgrade tensorflow-gpu to 2.6.4 or later
   • Upgrade tensorflow-gpu to 2.7.2 or later
   • Upgrade tensorflow-gpu to 2.8.1 or later

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