Vulnerability Monitor

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CVE-2021-29529

TensorFlow is an end-to-end open source platform for machine learning. 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 is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) 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]`. This 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(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer overflow. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Published

2021-05-14T20:15:11.937

Last Modified

2024-11-21T06:01:19.080

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 2.5 (LOW)

CVSSv2 Vector

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

Access Vector: LOCAL
Access Complexity: LOW
Authentication: NONE
Confidentiality Impact: PARTIAL
Integrity Impact: PARTIAL
Availability Impact: PARTIAL

Exploitability Score

3.9

Impact Score

6.4

Weaknesses

Type: Secondary
CWE-131
Type: Primary
CWE-193

Affected Vendors & Products

Type	Vendor	Product	Version/Range	Vulnerable?
Application	google	tensorflow	< 2.1.4	Yes
Application	google	tensorflow	< 2.2.3	Yes
Application	google	tensorflow	< 2.3.3	Yes
Application	google	tensorflow	< 2.4.2	Yes

References

https://github.com/tensorflow/tensorflow/commit/f851613f8f0fb0c838d160ced13c134f778e3ce7 Patch, Third Party Advisory ([email protected])
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jfp7-4j67-8r3q Exploit, Patch, Third Party Advisory ([email protected])
https://github.com/tensorflow/tensorflow/commit/f851613f8f0fb0c838d160ced13c134f778e3ce7 Patch, Third Party Advisory (af854a3a-2127-422b-91ae-364da2661108)
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jfp7-4j67-8r3q Exploit, Patch, Third Party Advisory (af854a3a-2127-422b-91ae-364da2661108)