Vulnerability Monitor

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CVE-2020-15265

In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Published

2020-10-21T21:15:12.257

Last Modified

2024-11-21T05:05:13.733

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 5.9 (MEDIUM)

CVSSv2 Vector

AV:N/AC:L/Au:N/C:N/I:N/A:P

  • Access Vector: NETWORK
  • Access Complexity: LOW
  • Authentication: NONE
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: PARTIAL
Exploitability Score

10.0

Impact Score

2.9

Weaknesses
  • Type: Primary
    CWE-125
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.4.0 Yes
References