CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:N/AC:M/Au:N/C:N/I:N/A:P
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
AI Score
Confidence
High
EPSS
Percentile
69.4%
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. Thus, the code sets up conditions to cause a heap buffer overflow. A BatchedMap
is equivalent to a vector where each element is a hashmap. However, if the first element of splits_values
is not 0, batch_idx
will never be 1, hence there will be no hashmap at index 0 in per_batch_counts
. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Vendor | Product | Version | CPE |
---|---|---|---|
tensorflow | 2.3.0 | cpe:2.3:a:google:tensorflow:2.3.0:*:*:*:-:*:*:* |
[
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": "= 2.3.0"
}
]
}
]
CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:N/AC:M/Au:N/C:N/I:N/A:P
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
AI Score
Confidence
High
EPSS
Percentile
69.4%