CVE-2021-37689

Null pointer dereference in TFLite MLIR optimizations

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Attribution

This vulnerability has been reported by Yakun Zhang of Baidu Security.

An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service:

This is caused by the MLIR optimization of L2NormalizeReduceAxis operator. The implementation unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements:

bool L2NormalizeReduceAxis(Value sq_op, DenseElementsAttr axis) {
  if (sq_op.getType().cast<ShapedType>().getRank() - 1 ==
          *axis.getValues<int>().begin() ||
      *axis.getValues<int>().begin() == -1) {
      // ...
  }
  // ...
}

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

CVE-2021-37689 has a CVSS score of 7.8 (High). 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 (2.3.4, 2.4.3, 2.5.1); upgrading removes the vulnerable code path.

Kodem intelligence

Already deployed Kodem?

We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

1. What is CVE-2021-37689? CVE-2021-37689 is a high-severity null pointer dereference vulnerability in tensorflow (pip), affecting versions < 2.3.4. It is fixed in 2.3.4, 2.4.3, 2.5.1. The application dereferences a null pointer, causing a crash.
2. How severe is CVE-2021-37689? CVE-2021-37689 has a CVSS score of 7.8 (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-2021-37689?
   • tensorflow (pip) (versions < 2.3.4)
   • tensorflow-cpu (pip) (versions < 2.3.4)
   • tensorflow-gpu (pip) (versions < 2.3.4)
4. Is there a fix for CVE-2021-37689? Yes. CVE-2021-37689 is fixed in 2.3.4, 2.4.3, 2.5.1. Upgrade to this version or later.
5. Is CVE-2021-37689 exploitable, and should I be worried? Whether CVE-2021-37689 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-2021-37689 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-2021-37689?
   • Upgrade tensorflow to 2.3.4 or later
   • Upgrade tensorflow to 2.4.3 or later
   • Upgrade tensorflow to 2.5.1 or later
   • Upgrade tensorflow-cpu to 2.3.4 or later
   • Upgrade tensorflow-cpu to 2.4.3 or later
   • Upgrade tensorflow-cpu to 2.5.1 or later
   • Upgrade tensorflow-gpu to 2.3.4 or later
   • Upgrade tensorflow-gpu to 2.4.3 or later
   • Upgrade tensorflow-gpu to 2.5.1 or later

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