BlackBird – OSINT Tool To Search Fast For Online Accounts By Username Across 574 Sites



This or previous program is for Educational purpose ONLY. Do not use it without permission. 
The usual disclaimer applies, especially the fact that me (P1ngul1n0) is not liable for any 
damages caused by direct or indirect use of the information or functionality provided by these 
programs. The author or any Internet provider bears NO responsibility for content or misuse 
of these programs or any derivatives thereof. By using these programs you accept the fact 
that any damage (dataloss, system crash, system compromise, etc.) caused by the use of these 
programs is not P1ngul1n0's responsibility.


Clone the repository

git clone
cd blackbird

Install requirements

pip install -r requirements.txt


Search by username

python -u username

Run WebServer

python --web

Access on the browser

Read results file

python -f username.json

List supported sites

python --list-sites

Use proxy

python -u crash --proxy

Show all results

By default only found accounts will be shown, however you can use the argument below to see them.

python -u crash --show-all


Blackbird can also be used with Docker.

Pull Image

docker pull p1ngul1n0/blackbird:v2

Run Webserver

docker run -p 9797:9797 p1ngul1n0/blackbird:v2 "--web"

Supported Social Networks

Most of the sites on this list were obtained through the incredible @whatsmynameproj project, don’t forget to visit and follow them . love_you_gesture

Export Report

The results can be exported as a PDF Report.


Metadata Extraction

When possible Blackbird will extract the user’s metadata, bringing data such as name, bio, location and profile picture.


Random UserAgent

Blackbird uses a random UserAgent from a list of 1000 UserAgents in each request to prevent blocking.

Supersonic speed rocket

Blackbird sends async HTTP requests, allowing a lot more speed when discovering user accounts.

JSON Template

Blackbird uses JSON as a template to store and read data.

Contributors medal_sports

I’m grateful to all contributors who improved and bugfixed the project.

Planned features

  • Implement Flask Web Server to optimize UX
  • Export results in PDF
  • Implement metadata extraction
  • Publish a docker image
  • Add unit test (Change ID to Appname, add “invalid-user” and “valid-user” params in JSON.)
  • Export results in CSV
  • Deploy on Cloud


Feel free to contact me on Twitter


Please follow and like us:

Leave a Reply

Your email address will not be published. Required fields are marked *