PT-2021-18280 · Google · Tensorflow
Yakun Zhang
+1
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Published
2021-05-14
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Updated
2024-03-06
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CVE-2021-29529
CVSS v3.1
7.8
High
| Vector | AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H |
Name of the Vulnerable Software and Affected Versions:
TensorFlow versions prior to 2.5.0
TensorFlow versions 2.1.4 through 2.4.2
Description:
An attacker can trigger a heap buffer overflow in
tf.raw ops.QuantizedResizeBilinear by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This occurs because the implementation computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of in, interpolation->upper[i] might be smaller than interpolation->lower[i], which is an issue if interpolation->upper[i] is capped at in size-1 as it means that interpolation->lower[i] points outside of the image. Then, in the interpolation code, this would result in heap buffer overflow.Recommendations:
For versions prior to 2.5.0, update to TensorFlow 2.5.0 or later.
For versions 2.1.4 through 2.4.2, update to the respective patched versions: 2.1.4, 2.2.3, 2.3.3, or 2.4.2.
As a temporary workaround, consider restricting the use of the
tf.raw ops.QuantizedResizeBilinear function until a patch is available.Exploit
Fix
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Related Identifiers
Affected Products
Tensorflow