5.5
CVE-2021-37674
- EPSS 0.03%
- Veröffentlicht 12.08.2021 23:15:07
- Zuletzt bearbeitet 21.11.2024 06:15:40
- Quelle security-advisories@github.com
- CVE-Watchlists
- Unerledigt
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Daten sind bereitgestellt durch National Vulnerability Database (NVD)
Google ≫ Tensorflow Version >= 2.3.0 < 2.3.4
Google ≫ Tensorflow Version >= 2.4.0 < 2.4.3
Google ≫ Tensorflow Version2.5.0
Google ≫ Tensorflow Version2.6.0 Updaterc0
Google ≫ Tensorflow Version2.6.0 Updaterc1
Google ≫ Tensorflow Version2.6.0 Updaterc2
| Typ | Quelle | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 0.03% | 0.086 |
| Quelle | Base Score | Exploit Score | Impact Score | Vector String |
|---|---|---|---|---|
| nvd@nist.gov | 5.5 | 1.8 | 3.6 |
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
|
| nvd@nist.gov | 2.1 | 3.9 | 2.9 |
AV:L/AC:L/Au:N/C:N/I:N/A:P
|
| security-advisories@github.com | 5.5 | 1.8 | 3.6 |
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
|
CWE-1284 Improper Validation of Specified Quantity in Input
The product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties.
CWE-20 Improper Input Validation
The 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.