3 releases (breaking)
new 0.4.0 | Nov 17, 2024 |
---|---|
0.3.1 | Nov 16, 2024 |
0.2.3 | Nov 5, 2024 |
#166 in Text processing
125 downloads per month
455KB
933 lines
🤔 What
is this?
Imagine this: You come across some mysterious text 🧙♂️ 0x52908400098527886E0F7030069857D2E4169EE7
or dQw4w9WgXcQ
and you wonder what it is. What do you do?
Well, with what-rs
all you have to do is ask what-rs "0x52908400098527886E0F7030069857D2E4169EE7"
and what-rs
will tell you!
what-rs
's job is to identify what something is. Whether it be a file or text! Or even the hex of a file! What about text within files? We have that too! what-rs
is recursive, it will identify everything in text and more!
⚠️ The project is under active development and not yet feature complete with pyWhat ⚠️
⚙ Usage
🌌 Other Features
Anytime you have a file, and you want to find structured data in it that's useful, what-rs
is for you.
Or if you come across some piece of text, and you don't know what it is, what-rs
will tell you.
📁 File & Directory Handling
File Opening You can pass in a file path by what-rs 'this/is/a/file/path'
. what-rs
is smart enough to figure out it's a file!
What about a whole directory? what-rs
can handle that too! It will recursively search for files and output everything you need!
🔍 Filtering your output
Sometimes, you only care about seeing things which are related to AWS. Or bug bounties, or cryptocurrencies!
You can filter output by using what-rs --rarity 0.2:0.8 "thing/to/identify""
. Use what-rs --help
to get more information.
👽 Sorting, Exporting, and more!
Sorting You can sort the output by using what-rs -k rarity --reverse INPUT
.
Use what-rs --help
to get more information.
Exporting You can export to json using what-rs --format json
and results can be sent directly to a file using what-rs --format json > outport.json
.
Borderless mode what-rs
has a special mode to match identifiable information within strings.
By default, it is enabled in CLI but can be disabled using what-rs --disable-borderless INPUT
or what-rs -d INPUT
.
Use what --help
for more information.
💖 Acknowledgement
Big thanks to bee-san and everyone who worked on pyWhat for their amazing work on! Without them this project wouldn't exist.
Dependencies
~15–27MB
~426K SLoC