5.5
CVE-2021-37646
- EPSS 0.01%
- Veröffentlicht 12.08.2021 21:15:07
- Zuletzt bearbeitet 21.11.2024 06:15:36
- Quelle security-advisories@github.com
- CVE-Watchlists
- Unerledigt
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. 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 | 0.01% | 0.011 |
| 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-681 Incorrect Conversion between Numeric Types
When converting from one data type to another, such as long to integer, data can be omitted or translated in a way that produces unexpected values. If the resulting values are used in a sensitive context, then dangerous behaviors may occur.