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Severe, 6 weeks1496Projects326

1496 severe, 6 weeks · 326 projects

TensorFlowGHSA-h6fg-mjxg-hqq4

Integer truncation in Shard API usage

TensorFlow

CVE-2020-15202 · Published Sep 25, 2020 · updated Jul 8, 2026

High9.0
Fix: upgrade to 1.15.4 or later (5 fixed versions below)
GitHub advisory

Impact

The Shard API in TensorFlow expects the last argument to be a function taking two int64 (i.e., long long) arguments:

https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/util/work_sharder.h#L59-L60

However, there are several places in TensorFlow where a lambda taking int or int32 arguments is being used:

https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L204-L205

https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L317-L318

In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption.

Patches

We have patched the issue in 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575. We will release patch releases for all versions between 1.15 and 2.3.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

For more information

Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact...

Affected versions

PackageAffectedFixed in
tensorflow
PyPI
< 1.15.41.15.4
>= 2.0.0, < 2.0.32.0.3
>= 2.1.0, < 2.1.22.1.2
>= 2.2.0, < 2.2.12.2.1
>= 2.3.0, < 2.3.12.3.1
Details and references

### Impact The `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/util/work_sharder.h#L59-L60 However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L204-L205 https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L317-L318 In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. ### Patches We have patched the issue in 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575. We will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

CVSS 3.1
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
Severity from
GitHub (reviewed advisory)
Weakness
CWE-197, CWE-754
Also known as
BIT-tensorflow-2020-15202, CVE-2020-15202, PYSEC-2020-125, PYSEC-2020-282, PYSEC-2020-317

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