7.1 High
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
3.6 Low
CVSS2
Access Vector
LOCAL
Access Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:N/A:P
0.0004 Low
EPSS
Percentile
11.7%
TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to tf.raw_ops.RaggedGather
don’t determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The implementation directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by params_nested_splits
is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
CPE | Name | Operator | Version |
---|---|---|---|
tensorflow-gpu | eq | 2.3.1 | |
tensorflow-gpu | eq | 2.4.1 | |
tensorflow-gpu | eq | 2.4.2 | |
tensorflow-gpu | eq | 2.3.2 | |
tensorflow-gpu | eq | 2.3.0 | |
tensorflow-gpu | eq | 2.3.3 | |
tensorflow-gpu | eq | 2.4.0 |
7.1 High
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
3.6 Low
CVSS2
Access Vector
LOCAL
Access Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:N/A:P
0.0004 Low
EPSS
Percentile
11.7%