Twitter OSiNT (Ethical Hacking)
Summary
TLDRThis video introduces a Python-based tool called Twint, which allows users to scrape Twitter data without an API, login, or rate limits. The host provides a step-by-step guide on setting up Twint, demonstrating its use via CLI and within Python scripts. Emphasizing ethical hacking, the host explores various commands for collecting tweets, searching by user, keyword, location, and more. The video also delves into advanced features like saving data to JSON files, and using the tool in real-world investigations, encouraging viewers to explore its potential for educational purposes.
Takeaways
- π Twint is a powerful Python hacking tool used to gather information from Twitter without API, rate limits, or login.
- π» The tool works via CLI and can also be imported into Python code for deeper functionality.
- β οΈ The tool is legal, but intent matters β it should only be used for educational purposes and ethical hacking.
- β±οΈ Setup is quick and can be done in five minutes using any Linux system or the free Google Cloud Console.
- π οΈ Essential commands for setup include installing Git, Python 3, and Pip, followed by cloning the Twint repository.
- π Twint can scrape tweets, filter results by username, keyword, date, location, popularity, and more.
- π Results can be exported to JSON files for further analysis or storage.
- π¨βπ» Twint can be used programmatically within Python scripts, allowing for advanced search and automation.
- π The tool supports searching by geolocation, helping find tweets near specific locations or within a defined radius.
- π‘ Twint is a valuable tool for Open-Source Intelligence (OSINT) investigations, making information gathering easier.
Q & A
What is the purpose of the video?
-The video demonstrates how to use a Python hacking tool called Twint to gather information from Twitter without the need for API access, login, or rate limits.
Is Twint an illegal tool?
-No, Twint is not illegal. However, the user's intent when using the tool is important, and the video stresses the importance of using it for educational purposes only.
What does Twint stand for?
-Twint stands for Twitter Intelligence, a powerful Python tool for scraping information from Twitter.
What are the main features of Twint?
-Twint allows users to scrape Twitter data without using the Twitter API, login, or facing rate limits. It can gather tweets based on usernames, search terms, locations, and more. It can also output data in JSON format and be integrated into Python code.
How can Twint be installed?
-Twint can be installed by cloning the tool from GitHub using 'git clone,' navigating to the Twint directory, and installing the required dependencies using 'pip3 install -r requirements.txt'.
What are some common uses of Twint via the command line?
-Some common uses include searching for tweets from a specific user, limiting the number of tweets retrieved, searching by keyword, and exporting results to a file.
Can Twint be used programmatically within Python scripts?
-Yes, Twint can be imported as a Python module, and its functionality can be customized in Python scripts, allowing for more complex and dynamic queries.
How can you search for tweets near a specific location using Twint?
-You can use the '--near' option followed by the name of a city or '--geo' followed by latitude and longitude coordinates, along with a radius, to search for tweets near a specific location.
How can you filter tweets based on their popularity using Twint?
-You can use the '--min-likes' option followed by a number to filter tweets that have received at least that number of likes.
What is one practical use case of Twint demonstrated in the video?
-One practical use case is searching for tweets about coffee near a user's location or for popular tweets about Raspberry Pi in different cities. The video also demonstrates gathering tweets and exporting them to JSON files for further analysis.
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