CVE-2021-29546
Division by 0 in `QuantizedBiasAdd`
描述
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
如何修補 CVE-2021-29546
要修補 CVE-2021-29546,請將受影響套件升級到下列已修補版本。
- —升級至 2.1.4 或更新版本
- —升級至 2.1.4 或更新版本
- —升級至 67784700869470d65d5f2ef20aeb5e97c31673cb 或更新版本
- —升級至 2.1.4 或更新版本
- —升級至 67784700869470d65d5f2ef20aeb5e97c31673cb 或更新版本
- —升級至 2.1.4 或更新版本
- —升級至 67784700869470d65d5f2ef20aeb5e97c31673cb 或更新版本
CVE-2021-29546 正在被利用嗎?
低 — EPSS 為 0.2%,目前沒有觀察到大規模利用活動。
受影響套件(7)
- from 0, < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
- from 0, < 2.1.4
- from 0, < 67784700869470d65d5f2ef20aeb5e97c31673cb | from 0, < 2.2.0rc0, >= 2.2.0, < 2.3.0rc0, >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
- from 0, < 2.1.4
- from 0, < 67784700869470d65d5f2ef20aeb5e97c31673cb | from 0, < 2.2.0rc0, >= 2.2.0, < 2.3.0rc0, >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
- from 0, < 2.1.4
- from 0, < 67784700869470d65d5f2ef20aeb5e97c31673cb | from 0, < 2.2.0rc0, >= 2.2.0, < 2.3.0rc0, >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
CVSS 分數
| 來源 | 版本 | 嚴重程度 | 向量 |
|---|---|---|---|
| osv | CVSS 4.0 | — | CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N |
| osv | CVSS 3.1 | LOW2.5 | CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L |
參考連結(6)
- ADVISORYnvd.nist.gov/vuln/detail/CVE-2021-29546
- WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-474.yaml
- WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-672.yaml
- WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-183.yaml