CVE-2022-23566

Out of bounds write in Tensorflow

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TensorFlow is vulnerable to a heap OOB write in Grappler:

Status SetUnknownShape(const NodeDef* node, int output_port) {
  shape_inference::ShapeHandle shape = 
      GetUnknownOutputShape(node, output_port);
  InferenceContext* ctx = GetContext(node);
  if (ctx == nullptr) {
    return errors::InvalidArgument("Missing context");
  }
  ctx->set_output(output_port, shape);
  return Status::OK();
}

The set_output function writes to an array at the specified index:

void set_output(int idx, ShapeHandle shape) { outputs_.at(idx) = shape; }

Hence, this gives a malicious user a write primitive.

A write operation targets a memory location beyond the intended buffer boundary. Typical impact: memory corruption, crash, or arbitrary code execution.

CVE-2022-23566 has a CVSS score of 8.8 (High). The vector is network-reachable, 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 (2.5.3, 2.6.3, 2.7.1); upgrading removes the vulnerable code path.

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We have patched the issue in GitHub commit 97282c6d0d34476b6ba033f961590b783fa184cd.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

1. What is CVE-2022-23566? CVE-2022-23566 is a high-severity out-of-bounds write vulnerability in tensorflow (pip), affecting versions < 2.5.3. It is fixed in 2.5.3, 2.6.3, 2.7.1. A write operation targets a memory location beyond the intended buffer boundary.
2. How severe is CVE-2022-23566? CVE-2022-23566 has a CVSS score of 8.8 (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-2022-23566?
   • tensorflow (pip) (versions < 2.5.3)
   • tensorflow-cpu (pip) (versions < 2.5.3)
   • tensorflow-gpu (pip) (versions < 2.5.3)
4. Is there a fix for CVE-2022-23566? Yes. CVE-2022-23566 is fixed in 2.5.3, 2.6.3, 2.7.1. Upgrade to this version or later.
5. Is CVE-2022-23566 exploitable, and should I be worried? Whether CVE-2022-23566 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-2022-23566 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-2022-23566?
   • Upgrade tensorflow to 2.5.3 or later
   • Upgrade tensorflow to 2.6.3 or later
   • Upgrade tensorflow to 2.7.1 or later
   • Upgrade tensorflow-cpu to 2.5.3 or later
   • Upgrade tensorflow-cpu to 2.6.3 or later
   • Upgrade tensorflow-cpu to 2.7.1 or later
   • Upgrade tensorflow-gpu to 2.5.3 or later
   • Upgrade tensorflow-gpu to 2.6.3 or later
   • Upgrade tensorflow-gpu to 2.7.1 or later

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