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minimaxir/big-list-of-naughty-strings

Analysis updated 2026-06-20

47,629PythonAudience · developerComplexity · 1/5Setup · easy

TLDR

A curated list of text strings known to cause crashes, bugs, or unexpected behavior in software, used to stress-test any app that accepts user input, from sign-up forms to search boxes to database queries.

Mindmap

mindmap
  root((repo))
    What it does
      Problematic string list
      Bug and crash triggers
      Security test data
    File formats
      Plain text blns.txt
      JSON version
      Language packages
    Use cases
      Manual QA testing
      Automated test suites
      Form input stress tests
    Audience
      QA engineers
      Developers
      Security testers
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Code map

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filefunction / class

What do people build with it?

USE CASE 1

Paste strings from the list into a web form's input fields to find encoding errors, layout breaks, or crashes before shipping.

USE CASE 2

Load the JSON file in an automated test suite to run all naughty strings through any function that processes user text and catch regressions.

USE CASE 3

Test a database or search feature against SQL injection, Unicode edge cases, and null byte crashes using the categorized string data.

USE CASE 4

Validate that a chat app, comment field, or file upload field handles unusual or malicious text gracefully before launch.

What is it built with?

PythonJSON

How does it compare?

minimaxir/big-list-of-naughty-stringsoobabooga/textgenlllyasviel/fooocus
Stars47,62946,94548,399
LanguagePythonPythonPython
Setup difficultyeasymoderatemoderate
Complexity1/53/52/5
Audiencedeveloperdevelopervibe coder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

In plain English

The Big List of Naughty Strings is a curated collection of text strings specifically chosen because they are likely to cause bugs, crashes, or unexpected behavior when a program uses them as user input. The problem it solves is that developers often test their applications with normal, well-behaved input but forget to check what happens with unusual or edge-case text. Real users, and especially malicious ones, can submit things like empty strings, strings containing only spaces, very long strings, strings with special Unicode characters, strings that look like code injections, strings in right-to-left languages, strings with null bytes, and strings that have historically tripped up databases or web applications. The project provides a plain text file called blns.txt where each line is one of these problematic strings, organized into labeled categories. There is also a JSON version for loading the list programmatically in your own test scripts. A small Python helper script generates the JSON from the text file. Third-party packages for Node.js.NET, PHP, and C++ let you import the list directly into automated test suites without copying files manually. You would use this when building any application that accepts text input from users, a sign-up form, a search box, a comment field, a file upload field, a chat app, and you want to stress-test it against the kinds of inputs that commonly break software. QA engineers paste these strings into forms during manual testing, and automated test suites loop through the JSON file to catch regressions. The list is language-agnostic, the strings are the test data, and your application under test handles them in whatever language it is written in.

Copy-paste prompts

Prompt 1
Using the big-list-of-naughty-strings JSON file, write a Python pytest fixture that feeds each string as input to my text sanitization function and checks it never raises an exception.
Prompt 2
Load blns.json in Node.js and write a test that POSTs each naughty string to my Express API endpoint and logs any that return a 500 error.
Prompt 3
Using the big-list-of-naughty-strings, write a script that runs each string through my database query function and reports which ones cause errors or unexpected output.
Prompt 4
Which categories from the big-list-of-naughty-strings are highest priority for finding security vulnerabilities in a sign-up form with email and username fields?

Frequently asked questions

What is big-list-of-naughty-strings?

A curated list of text strings known to cause crashes, bugs, or unexpected behavior in software, used to stress-test any app that accepts user input, from sign-up forms to search boxes to database queries.

What language is big-list-of-naughty-strings written in?

Mainly Python. The stack also includes Python, JSON.

How hard is big-list-of-naughty-strings to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is big-list-of-naughty-strings for?

Mainly developer.

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