CVE-2020-15197
Denial of Service in Tensorflow
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Description
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 rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Affected
Our own answer: ranges merged, affected separated from platform-only, with confidence and review flags.
Remediation
No guide yetNo remediation guidance has been written for this CVE yet. What the record does show:
Patch and advisory references
References (3)
CVSS
- Attack Vector
- NETWORK
- Complexity
- HIGH
- Privileges
- LOW
- User Interaction
- NONE
- Scope
- CHANGED
- Confidentiality
- NONE
- Integrity
- NONE
- Availability
- HIGH
Quick Info
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