6.8 Medium
CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:N/AC:M/Au:N/C:P/I:P/A:P
4.8 Medium
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
LOW
Integrity Impact
LOW
Availability Impact
NONE
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N
0.001 Low
EPSS
Percentile
47.8%
In Tensorflow before version 2.3.1, the RaggedCountSparseOutput
implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the splits
tensor generate a valid partitioning of the values
tensor. Hence, the code is prone to heap buffer overflow. If split_values
does not end with a value at least num_values
then the while
loop condition will trigger a read outside of the bounds of split_values
once batch_idx
grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
6.8 Medium
CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:N/AC:M/Au:N/C:P/I:P/A:P
4.8 Medium
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
LOW
Integrity Impact
LOW
Availability Impact
NONE
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N
0.001 Low
EPSS
Percentile
47.8%