What is CVE-2022-29205?

CVE-2022-29205 is a medium-severity null pointer dereference vulnerability in tensorflow (pip), affecting versions < 2.6.4. It is fixed in 2.6.4, 2.7.2, 2.8.1. The application dereferences a null pointer, causing a crash.

How severe is CVE-2022-29205?

CVE-2022-29205 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.

Which packages are affected by CVE-2022-29205?

tensorflow (pip) versions < 2.6.4; tensorflow-cpu (pip) versions < 2.6.4; tensorflow-gpu (pip) versions < 2.6.4.

Is there a fix for CVE-2022-29205?

Yes. CVE-2022-29205 is fixed in 2.6.4, 2.7.2, 2.8.1. Upgrade to this version or later.

Is CVE-2022-29205 exploitable, and should I be worried?

Whether CVE-2022-29205 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.

What actually determines whether CVE-2022-29205 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.

How do I fix CVE-2022-29205?

Upgrade: tensorflow to 2.6.4 or later, tensorflow to 2.7.2 or later, tensorflow to 2.8.1 or later, tensorflow-cpu to 2.6.4 or later, tensorflow-cpu to 2.7.2 or later, tensorflow-cpu to 2.8.1 or later, tensorflow-gpu to 2.6.4 or later, tensorflow-gpu to 2.7.2 or later, tensorflow-gpu to 2.8.1 or later.

CVE-2022-29205 in tensorflow

Q: How severe is CVE-2022-29205?

CVE-2022-29205 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.

Q: Which packages are affected by CVE-2022-29205?

tensorflow (pip) versions < 2.6.4; tensorflow-cpu (pip) versions < 2.6.4; tensorflow-gpu (pip) versions < 2.6.4.

Q: Is there a fix for CVE-2022-29205?

Yes. CVE-2022-29205 is fixed in 2.6.4, 2.7.2, 2.8.1. Upgrade to this version or later.

Q: Is CVE-2022-29205 exploitable, and should I be worried?

Whether CVE-2022-29205 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.

Q: What actually determines whether CVE-2022-29205 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.

Q: How do I fix CVE-2022-29205?

Upgrade: tensorflow to 2.6.4 or later, tensorflow to 2.7.2 or later, tensorflow to 2.8.1 or later, tensorflow-cpu to 2.6.4 or later, tensorflow-cpu to 2.7.2 or later, tensorflow-cpu to 2.8.1 or later, tensorflow-gpu to 2.6.4 or later, tensorflow-gpu to 2.7.2 or later, tensorflow-gpu to 2.8.1 or later.

Summary

Segfault due to missing support for quantized types

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Hong Jin from Singapore Management University.

Impact

There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types (added after migration to TF 2.x):

import numpy as np
import tensorflow as tf

tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))

In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault.

The application dereferences a null pointer, causing a crash. Typical impact: denial of service via crash.

CVE-2022-29205 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.

Affected versions

tensorflow (< 2.6.4) tensorflow (>= 2.7.0, < 2.7.2) tensorflow (>= 2.8.0, < 2.8.1) tensorflow-cpu (< 2.6.4) tensorflow-cpu (>= 2.7.0, < 2.7.2) tensorflow-cpu (>= 2.8.0, < 2.8.1) tensorflow-gpu (< 2.6.4) tensorflow-gpu (>= 2.7.0, < 2.7.2) tensorflow-gpu (>= 2.8.0, < 2.8.1)

Security releases

tensorflow → 2.6.4 (pip) tensorflow → 2.7.2 (pip) tensorflow → 2.8.1 (pip) tensorflow-cpu → 2.6.4 (pip) tensorflow-cpu → 2.7.2 (pip) tensorflow-cpu → 2.8.1 (pip) tensorflow-gpu → 2.6.4 (pip) tensorflow-gpu → 2.7.2 (pip) tensorflow-gpu → 2.8.1 (pip)

Kodem intelligence

Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.

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. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.

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Remediation advice

We have patched the issue in GitHub commit 237822b59fc504dda2c564787f5d3ad9c4aa62d9.

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.

Frequently Asked Questions

What is CVE-2022-29205? CVE-2022-29205 is a medium-severity null pointer dereference vulnerability in tensorflow (pip), affecting versions < 2.6.4. It is fixed in 2.6.4, 2.7.2, 2.8.1. The application dereferences a null pointer, causing a crash.
How severe is CVE-2022-29205? CVE-2022-29205 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.
Which packages are affected by CVE-2022-29205?
- tensorflow (pip) (versions < 2.6.4)
- tensorflow-cpu (pip) (versions < 2.6.4)
- tensorflow-gpu (pip) (versions < 2.6.4)
Is there a fix for CVE-2022-29205? Yes. CVE-2022-29205 is fixed in 2.6.4, 2.7.2, 2.8.1. Upgrade to this version or later.
Is CVE-2022-29205 exploitable, and should I be worried? Whether CVE-2022-29205 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
What actually determines whether CVE-2022-29205 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.
How do I fix CVE-2022-29205?
- 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

Other vulnerabilities in tensorflow

CVE-IDSeverityPackage summary

CVE-2023-33976Hightensorflow: TensorFlow has segfault in array_ops.upper_bound CVE-2023-25661Mediumtensorflow: TensorFlow Denial of Service vulnerability CVE-2023-25659Hightensorflow: TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch CVE-2023-25660Hightensorflow: TensorFlow vulnerable to seg fault in `tf.raw_ops.Print`CVE-2023-25662Hightensorflow: TensorFlow vulnerable to integer overflow in EditDistance