CVE-2021-29614 Interpreter crash from `tf.io.decode_raw`

What is CVE-2021-29614?

CVE-2021-29614 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 14 May 2021. It can only be exploited from the same machine or local network, with no action from the victim.

Official description

TensorFlow is an end-to-end open source platform for machine learning. 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. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Weakness: CWE-787, CWE-665

Which versions are affected by CVE-2021-29614?

28 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.

Products include Google Tensorflow.

How do I fix CVE-2021-29614?

Upgrade tensorflow to a fixed version for your release line: 2.1.4, 2.2.3, 2.3.3 or 2.4.2.

Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.

Is CVE-2021-29614 being exploited?

There is no known exploitation of CVE-2021-29614 in the wild and no public exploit code.

Other vulnerabilities in Google Tensorflow

• CVE-2023-25668 TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation Critical 9.8
• CVE-2018-7575 Integer Overflow or Wraparound in Google TensorFlow Critical 9.8
• CVE-2021-37678 Arbitrary code execution due to YAML deserialization Critical 9.3
• CVE-2021-35958 Path traversal in n/a Critical 9.1
• CVE-2020-15202 Integer truncation in Shard API usage Critical 9.0

All Google Tensorflow vulnerabilities

Sources

• CVE record
• NVD
• OSV
• GitHub advisory
• How this page is made

Also known as BIT-tensorflow-2021-29614, GHSA-8pmx-p244-g88h, PYSEC-2021-251, PYSEC-2021-542, PYSEC-2021-740.