GitHub_MCVE-2020-15198CVE-2020-15198
CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
NONE
AV:N/AC:M/Au:N/C:P/I:P/A:N
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
CHANGED
Confidentiality Impact
LOW
Integrity Impact
LOW
Availability Impact
NONE
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N
AI Score
Confidence
High
EPSS
Percentile
40.5%
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Affected configurations
| Vendor | Product | Version | CPE |
|---|---|---|---|
| tensorflow | * | cpe:2.3:a:google:tensorflow:*:*:*:*:-:*:*:* |
CNA Affected
[
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": ">= 2.3.0, < 2.3.1"
}
]
}
]Related
CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
NONE
AV:N/AC:M/Au:N/C:P/I:P/A:N
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
CHANGED
Confidentiality Impact
LOW
Integrity Impact
LOW
Availability Impact
NONE
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N
AI Score
Confidence
High
EPSS
Percentile
40.5%