CVE-2021-29582: TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequanti
Summary
TensorFlow, a popular machine learning platform, has a vulnerability in its `Dequantize` operation where the code doesn't check that two input values (called `min_range` and `max_range` tensors, which are multi-dimensional arrays of data) have matching dimensions before using them together, allowing an attacker to read memory from outside the intended area. This is a type of memory safety bug that could let attackers access sensitive data or crash the system.
Solution / Mitigation
The fix will be included in TensorFlow 2.5.0. The vulnerability will also be patched in earlier versions: TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.
Vulnerability Details
2.5(low)
EPSS: 0.0%
Classification
Affected Vendors
Related Issues
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CVE-2022-21727: Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulne
Original source: https://nvd.nist.gov/vuln/detail/CVE-2021-29582
First tracked: February 15, 2026 at 08:39 PM
Classified by LLM (prompt v3) · confidence: 95%