QID 981463

QID 981463: Python (pip) Security Update for tensorflow (GHSA-hjmq-236j-8m87)

Security update has been released for tensorflow to fix the vulnerability.

Note: The preceding description block is extracted directly from the security advisory. Using automation, we have attempted to clean and format it as much as possible without introducing additional issues.

In TensorFlow Lite models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/segment_sum.cc#L39-L44

CVSS V3 rated as Medium - 4 severity.

CVSS V2 rated as Medium - 4.3 severity.

Solution

We have patched the issue in 204945b and will release patch releases for all affected versions.

We recommend users to upgrade to TensorFlow 2.2.1, or 2.3.1.Workaround:
A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps.

However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.

Vendor References

GHSA-hjmq-236j-8m87 - github.com/advisories/GHSA-hjmq-236j-8m87

CVEs related to QID 981463

CVE-2020-15213 |

Software Advisories

Advisory ID	Software	Component	Link
GHSA-hjmq-236j-8m87	tensorflow		github.com/advisories/GHSA-hjmq-236j-8m87

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