CVE-2021-29536: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing i...

Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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.

Metrics

CVSS 3.1

7.8/10

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

EPSS Probability

0.21%

11.3th percentile

Probability of exploitation in the next 30 days. Learn more

Weakness Enumeration

Affected Software

Vendor	Product	Versions
Google	Tensorflow	< 2.1.4
Google	Tensorflow	>= 2.2.0, < 2.2.3
Google	Tensorflow	>= 2.3.0, < 2.3.3
Google	Tensorflow	>= 2.4.0, < 2.4.2

References

https://github.com/tensorflow/tensorflow/commit/a324ac84e573fba362a5e53d4e74d5de6729933ePatch, Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2gfx-95x2-5v3xExploit, Patch, Third Party Advisory
https://github.com/tensorflow/tensorflow/commit/a324ac84e573fba362a5e53d4e74d5de6729933ePatch, Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2gfx-95x2-5v3xExploit, Patch, Third Party Advisory

Timeline

Published: May 14, 2021
Last Modified: Jun 17, 2026
Status: Modified

Frequently Asked Questions

What is CVE-2021-29536?

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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.

How severe is CVE-2021-29536?

CVE-2021-29536 has a CVSS score of 7.8/10 (HIGH severity). The EPSS model estimates a 0.21% probability of exploitation in the next 30 days.

How do I fix CVE-2021-29536?

Check the vendor references and advisories linked above for patched versions and mitigation guidance. You can also run a Strix scan to test if your systems are affected.