CVE-2021-41203
Missing validation during checkpoint loading
Using tensorflow by tensorflow?
Get instant alerts when new vulnerabilities affect tensorflow - before attackers find them.
Description
TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
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
- https://github.com/tensorflow/tensorflow/commit/368af875869a204b4ac552b9ddda59f6a46a56ec
- https://github.com/tensorflow/tensorflow/commit/abcced051cb1bd8fb05046ac3b6023a7ebcc4578
- https://github.com/tensorflow/tensorflow/commit/b619c6f865715ca3b15ef1842b5b95edbaa710ad
- https://github.com/tensorflow/tensorflow/commit/e8dc63704c88007ee4713076605c90188d66f3d2
References (5)
CVSS
- Attack Vector
- LOCAL
- Complexity
- LOW
- Privileges
- LOW
- User Interaction
- NONE
- Scope
- UNCHANGED
- Confidentiality
- HIGH
- Integrity
- HIGH
- Availability
- HIGH
Quick Info
Get alerted
Stop reading CVE feeds looking for your own stack
Track the products you run and VulnTracker tells you when a new CVE affects them — with what is known about fixing it, and nothing about the rest.