Upstream information
Description
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.SUSE information
Overall state of this security issue: Does not affect SUSE products
This issue is currently rated as having important severity.
National Vulnerability Database | |
---|---|
Base Score | 3.6 |
Vector | AV:L/AC:L/Au:N/C:P/I:N/A:P |
Access Vector | Local |
Access Complexity | Low |
Authentication | None |
Confidentiality Impact | Partial |
Integrity Impact | None |
Availability Impact | Partial |
National Vulnerability Database | |
---|---|
Base Score | 7.1 |
Vector | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H |
Attack Vector | Local |
Attack Complexity | Low |
Privileges Required | Low |
User Interaction | None |
Scope | Unchanged |
Confidentiality Impact | High |
Integrity Impact | None |
Availability Impact | High |
CVSSv3 Version | 3.1 |
SUSE Timeline for this CVE
CVE page created: Mon May 17 08:58:28 2021CVE page last modified: Sat Mar 30 16:29:57 2024