CVE-2020-15210
25.09.2020, 19:15
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.Enginsight
Affected Products (NVD)
| Vendor | Product | Version |
|---|---|---|
| tensorflow | 𝑥 < 1.15.4 | |
| tensorflow | 2.0.0 ≤ 𝑥 < 2.0.3 | |
| tensorflow | 2.1.0 ≤ 𝑥 < 2.1.2 | |
| tensorflow | 2.2.0 ≤ 𝑥 < 2.2.1 | |
| tensorflow | 2.3.0 ≤ 𝑥 < 2.3.1 | |
| opensuse | leap | 15.2 |
𝑥
= Vulnerable software versions
Early Detection
Affected products identified ahead of NVD analysis through intelligence sources.
| Vendor | Product | Version | Source |
|---|---|---|---|
| tensorflow | tensorflow | 𝑥 < 1.15.4 | CNA |
Common Weakness Enumeration
- CWE-20 - Improper Input ValidationThe product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
- CWE-787 - Out-of-bounds WriteThe software writes data past the end, or before the beginning, of the intended buffer.
References