PyPI: tensorflow

CVE-2021-29614

Safety vulnerability ID: SFTY-20210514-01203

Safety legacy ID: pyup.io-40472

Tensorflow 2.5.0, 2.4.2, 2.3.3, 2.2.3, and 2.1.4 include a fix for CVE-2021-29614: The implementation of 'tf.io.decode_raw' produces incorrect results and crashes the Python interpreter when combining 'fixed_length' and wider datatypes. The implementation of the padded version (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the 'fixed_length' value to the size of the type argument. The 'fixed_length' argument is also used to determine the size needed for the output tensor (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the 'out_data' pointer by 'fixed_length * sizeof (T)' bytes whereas it only copied at most 'fixed_length' bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory.

Created at: Jul 5, 2026Updated at: Jul 5, 2026

Overview

Interpreter crash from `tf.io.decode_raw`

Advisory

Tensorflow 2.5.0, 2.4.2, 2.3.3, 2.2.3, and 2.1.4 include a fix for CVE-2021-29614: The implementation of 'tf.io.decode_raw' produces incorrect results and crashes the Python interpreter when combining 'fixed_length' and wider datatypes. The implementation of the padded version (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the 'fixed_length' value to the size of the type argument. The 'fixed_length' argument is also used to determine the size needed for the output tensor (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the 'out_data' pointer by 'fixed_length * sizeof (T)' bytes whereas it only copied at most 'fixed_length' bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory.

Affected Package

Affecting tensorflow package, versions>=2.4.0rc0,<2.4.2>=2.3.0rc0,<2.3.3>=2.2.0rc0,<2.2.3>=2.1.0rc0,<2.1.4>=2.5.0rc0,<2.5.0

Also affects

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How to Fix

Upgradetensorflowto2.4.22.3.32.2.32.1.42.5.0or higher.

Mitigation and Workarounds

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Vulnerable Functions

Functions linked to known vulnerabilities.

Vulnerable function data is available for Enterprise customers

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Safety

Verified by Safety

Our Cybersecurity Intelligence Team reviewed this vulnerability. We combine public data with our own research to find issues not yet reported to public sources.

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