AI-era slang dictionary

AI Security / Supply Chain Slang

Slop
squatting

Slopsquatting is registering package names that AI models invent. How it works, how it differs from typosquatting, and how to verify packages.

$ pip install huggingface-cli # model-hallucinated package name
First recorded: 2025Habitat: package registries, agent workflows, supply-chain researchStatus: active threatUpdated:
The deadpan blob mascot holding an imaginary package box while a registry shelf rejects it

The short version

Attackers register packages that AI models invent.

Language models generate plausible package names that do not exist. Attackers claim those names on PyPI and npm, waiting for developers or agents to install them.

What slopsquatting actually is

Slopsquatting happens when attackers register package names that language models invent. When developers or autonomous coding agents ask for a library to solve a specific task, models frequently suggest plausible package names that do not exist. Attackers monitor these repeated hallucinations, publish malicious packages under those exact names on npm or PyPI, and wait for machines or humans to install them.

This mechanism differs from older registry attacks. Typosquatting waits for a person to misspell a real package name like lodash. Dependency confusion exploits build tools that mix private corporate registries with public ones. Slopsquatting targets the predictable token guesses of language models.

Cultural Context & Sighting

The prompt in the wild.

“Lasso Security registered a harmless huggingface-cli package on PyPI after models repeatedly recommended it as an installation command. It recorded more than 30,000 downloads in three months, showing how often fabricated names enter real workflows.”

Why it works so reliably

Language models do not query live package registries when generating text. They predict likely words, which leads them to invent intuitive package names for common tasks. When thousands of people ask similar questions, models generate the exact same phantom package names repeatedly.
Autonomous coding agents amplify the problem. When an agent runs package install commands directly without human review, a single hallucinated library name executes immediately in the local environment.

Useful Practical Framing

How to prevent slopsquatting infections

Verifying package authenticity before running AI-generated install commands.

01 / Inspect registry metadata

Check the package creation date, maintainer history, and linked source repository. Download counts do not establish provenance.

02 / Verify official docs

Confirm package names against official project documentation rather than trusting the install command inside chatbot responses.

03 / Constrain autonomous installs

Run coding agents with locked dependency files and restricted network access so agents cannot fetch arbitrary unvetted packages.

Tiny origin story

How Slopsquatting entered the chat.

Evolution from early observations to current AI-era usage.

  1. 2023

    Security researchers first demonstrate package hallucinations in language model coding output.

  2. 2024

    Lasso Security documents a repeatedly hallucinated PyPI package name by registering huggingface-cli as a benign experiment.

  3. 2025

    USENIX Security publishes benchmark results showing 19.7 percent of model package recommendations were nonexistent.

  4. Now

    Aikido and registry maintainers track autonomous agents running hallucinated npx and pip commands.

Keep reading

Same ecosystem, different specimen.

All field notes

What to say back

Verify the package in the official project documentation before running the install command. Then check the publisher, release history, and linked source repository. Download counts alone do not establish provenance.

Refer the speaker