CVE-2021-29521

描述

TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.

如何修補 CVE-2021-29521

要修補 CVE-2021-29521,請將受影響套件升級到下列已修補版本。

• —升級至 2.3.3 或更新版本
• —升級至 2.3.3 或更新版本
• —升級至 c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5 或更新版本
• —升級至 2.3.3 或更新版本
• —升級至 c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5 或更新版本
• —升級至 2.3.3 或更新版本
• —升級至 c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5 或更新版本

CVE-2021-29521 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)

• >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
• >= 2.3.0, < 2.3.3
• from 0, < c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5 | >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
• >= 2.3.0, < 2.3.3
• from 0, < c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5 | >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
• >= 2.3.0, < 2.3.3
• from 0, < c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5 | >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2

CVSS 分數

參考連結(6)

• ADVISORYnvd.nist.gov/vuln/detail/CVE-2021-29521
• WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-449.yaml
• WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-647.yaml
• WEBgithub.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-158.yaml