Analysis updated 2026-06-20
Paste strings from the list into a web form's input fields to find encoding errors, layout breaks, or crashes before shipping.
Load the JSON file in an automated test suite to run all naughty strings through any function that processes user text and catch regressions.
Test a database or search feature against SQL injection, Unicode edge cases, and null byte crashes using the categorized string data.
Validate that a chat app, comment field, or file upload field handles unusual or malicious text gracefully before launch.
| minimaxir/big-list-of-naughty-strings | oobabooga/textgen | lllyasviel/fooocus | |
|---|---|---|---|
| Stars | 47,629 | 46,945 | 48,399 |
| Language | Python | Python | Python |
| Setup difficulty | easy | moderate | moderate |
| Complexity | 1/5 | 3/5 | 2/5 |
| Audience | developer | developer | vibe coder |
Figures from each repo's GitHub metadata at analysis time.
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.
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.
Mainly Python. The stack also includes Python, JSON.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.