TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the `min_range` and `max_range` tensors in parallel but fails to check that they have the same shape. 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.
References
Link | Resource |
---|---|
https://github.com/tensorflow/tensorflow/commit/5899741d0421391ca878da47907b1452f06aaf1b | Patch Third Party Advisory |
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c45w-2wxr-pp53 | Exploit Patch Third Party Advisory |
Configurations
Configuration 1 (hide)
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Information
Published : 2021-05-14 13:15
Updated : 2021-05-20 08:39
NVD link : CVE-2021-29582
Mitre link : CVE-2021-29582
JSON object : View
CWE
CWE-125
Out-of-bounds Read
Products Affected
- tensorflow