CVE-2021-41203
05.11.2021, 21:15
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.Enginsight
| Vendor | Product | Version |
|---|---|---|
| tensorflow | 𝑥 < 2.4.4 | |
| tensorflow | 2.5.0 ≤ 𝑥 < 2.5.2 | |
| tensorflow | 2.6.0 ≤ 𝑥 < 2.6.1 |
𝑥
= Vulnerable software versions
Common Weakness Enumeration
- CWE-345 - Insufficient Verification of Data AuthenticityThe software does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data.
- CWE-190 - Integer Overflow or WraparoundThe software performs a calculation that can produce an integer overflow or wraparound, when the logic assumes that the resulting value will always be larger than the original value. This can introduce other weaknesses when the calculation is used for resource management or execution control.
References