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
6.9 Medium
AI Score
Confidence
High
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.
CPE | Name | Operator | Version |
---|---|---|---|
tensorflow | le | 2.3.0 | |
tensorflow | ge | 2.3.0 |
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
6.9 Medium
AI Score
Confidence
High
0.001 Low
EPSS
Percentile
47.8%