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CVE-2021-29521
Good to know:
Date: May 14, 2021
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.
Language: Python
Severity Score
Severity Score
Weakness Type (CWE)
Incorrect Calculation of Buffer Size
CWE-131Top Fix
Upgrade Version
Upgrade to version tensorflow - 2.5.0, tensorflow-cpu - 2.5.0, tensorflow-gpu - 2.5.0
CVSS v3.1
Base Score: |
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Attack Vector (AV): | NETWORK |
Attack Complexity (AC): | LOW |
Privileges Required (PR): | NONE |
User Interaction (UI): | NONE |
Scope (S): | UNCHANGED |
Confidentiality (C): | LOW |
Integrity (I): | LOW |
Availability (A): | NONE |
CVSS v2
Base Score: |
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---|---|
Access Vector (AV): | LOCAL |
Access Complexity (AC): | LOW |
Authentication (AU): | NONE |
Confidentiality (C): | NONE |
Integrity (I): | NONE |
Availability (A): | PARTIAL |
Additional information: |