CVE-2020-15196
September 25, 2020
In Tensorflow version 2.3.0, the "SparseCountSparseOutput" and "RaggedCountSparseOutput" implementations don't validate that the "weights" tensor has the same shape as the data. The check exists for "DenseCountSparseOutput", where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Affected Packages
tensorflow-cpu (PYTHON):
Affected version(s) =2.3.0 <2.3.1Fix Suggestion:
Update to version 2.3.1tensorflow (PYTHON):
Affected version(s) =2.3.0 <2.3.1Fix Suggestion:
Update to version 2.3.1tensorflow-gpu (PYTHON):
Affected version(s) =2.3.0 <2.3.1Fix Suggestion:
Update to version 2.3.1Related Resources (8)
Do you need more information?
Contact UsCVSS v4
Base Score:
9
Attack Vector
NETWORK
Attack Complexity
HIGH
Attack Requirements
NONE
Privileges Required
LOW
User Interaction
NONE
Vulnerable System Confidentiality
HIGH
Vulnerable System Integrity
HIGH
Vulnerable System Availability
HIGH
Subsequent System Confidentiality
HIGH
Subsequent System Integrity
HIGH
Subsequent System Availability
HIGH
CVSS v3
Base Score:
8.5
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
LOW
User Interaction
NONE
Scope
CHANGED
Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH
CVSS v2
Base Score:
6.5
Access Vector
NETWORK
Access Complexity
LOW
Authentication
SINGLE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
Weakness Type (CWE)
EPSS
Base Score:
0.30
