CVE-2023-25660

TensorFlow vulnerable to seg fault in tf.raw_ops.Print

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 Yu Tian of Qihoo 360 AIVul Team

When the parameter summarize of tf.raw_ops.Print is zero, the new method SummarizeArray<bool> will reference to a nullptr, leading to a seg fault.

import tensorflow as tf

tf.raw_ops.Print(input =  tf.constant([1, 1, 1, 1],dtype=tf.int32),
                            data =  [[False, False, False, False], [False], [False, False, False]],
                            message =  'tmp/I',
                            first_n = 100,
                            summarize = 0)

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

CVE-2023-25660 has a CVSS score of 7.5 (High). The vector is network-reachable, no 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 (2.11.1); upgrading removes the vulnerable code path.

Kodem intelligence

Already deployed Kodem?

We have patched the issue in GitHub commit 6d423b8bcc9aa9f5554dc988c1c16d038b508df1.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

1. What is CVE-2023-25660? CVE-2023-25660 is a high-severity null pointer dereference vulnerability in tensorflow (pip), affecting versions < 2.11.1. It is fixed in 2.11.1. The application dereferences a null pointer, causing a crash.
2. How severe is CVE-2023-25660? CVE-2023-25660 has a CVSS score of 7.5 (High). 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-2023-25660?
   • tensorflow (pip) (versions < 2.11.1)
   • tensorflow-cpu (pip) (versions < 2.11.1)
   • tensorflow-gpu (pip) (versions < 2.11.1)
4. Is there a fix for CVE-2023-25660? Yes. CVE-2023-25660 is fixed in 2.11.1. Upgrade to this version or later.
5. Is CVE-2023-25660 exploitable, and should I be worried? Whether CVE-2023-25660 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-2023-25660 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-2023-25660?
   • Upgrade tensorflow to 2.11.1 or later
   • Upgrade tensorflow-cpu to 2.11.1 or later
   • Upgrade tensorflow-gpu to 2.11.1 or later

Other vulnerabilities in tensorflow