CVE-2021-29521

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.

• CVE ID
• CVE-2021-29521

• Assigner
• security-advisories@github.com

• Vulnerability Status
• Analyzed

• Published Version
• 2021-05-14T20:15:11

• Last Modified Date
• 2021-05-20T17:19:30

• Version
• 2.0

• Vector String
• AV:L/AC:L/Au:N/C:N/I:N/A:P

• Access Vector
• LOCAL

• Access Compatibility
• LOW

• Authentication
• NONE

• Confidentiality Impact
• NONE

• Integrity Impact
• NONE

• Availability Impact
• PARTIAL

• Base Score
• 2.1

• Severity
• LOW

• Exploitability Score
• 3.9

• Impact Score
• 2.9

• Version
• 3.1

• Vector String
• CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

• Attack Vector
• LOCAL

• Attack Compatibility
• LOW

• Privileges Required
• LOW

• User Interaction
• NONE

• Scope
• UNCHANGED

• Confidentiality Impact
• NONE

• Availability Impact
• HIGH

• Base Score
• 5.5

• Base Severity
• MEDIUM

• Exploitability Score
• 1.8

• Impact Score
• 3.6