# Threat Modeling Thursday: Machine Learning

DevFeed: [Threat Modeling Thursday: Machine Learning](<https://devfeed.tech/articles/threat-modeling-thursday-machine-learning-37081.md>)

Original publisher: [Read original article](<https://shostack.org/blog/tmt-machine-learning/>)

Author: Adam

Published: 2020-01-02T00:00:00Z

Content type: opinion

Language: en

Sources: [Shostack & Friends Blog](<https://devfeed.tech/sources/shostack-friends-blog.md>)

Topics: [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [Security](<https://devfeed.tech/topics/security.md>), [Adversarial attacks](<https://devfeed.tech/topics/adversarial-attacks.md>), [Reverse Dependencies](<https://devfeed.tech/topics/reverse-dependencies.md>)

Tags: [analysis](<https://devfeed.tech/tags/analysis.md>), [dependencies](<https://devfeed.tech/tags/dependencies.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml-supply-chain](<https://devfeed.tech/tags/ml-supply-chain.md>), [security](<https://devfeed.tech/tags/security.md>), [sensitive-data](<https://devfeed.tech/tags/sensitive-data.md>)

## AI overview

The article reviews Microsoft documents on threat modeling AI and machine learning systems, including their engineering challenges, categorized attacks, failure modes, and dependencies. It supports combining attacks and failures into a framework while arguing that additional ways to distinguish different security concerns are needed.

## Source excerpt

For my first blog post of 2020, I want to look at threat modeling machine learning systems.