5.5
CVE-2021-37677
- EPSS 0.01%
- Published 12.08.2021 23:15:08
- Last modified 21.11.2024 06:15:40
- Source security-advisories@github.com
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TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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.
Data is provided by the 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
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
| Type | Source | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 0.01% | 0.006 |
| Source | 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.