The user received a scam text message offering a fake prize and decided to investigate how the scam worked. They discovered that scammers were testing credit card validity in real-time and decided to create a program to send numerous declined transactions, potentially incurring charges for the scammer. They used Python and threading to automate this process and successfully sent a large number of fake transaction requests, highlighting the importance of not engaging in scams.
1. The user received a scam text message claiming to offer a $130 Amazon bonus credit.
2. The scam message directed the user to a website, w1fbv.info, to claim the bonus.
3. Upon entering the website, the user encountered a fake survey and an offer for a free PlayStation 5.
4. The scam required providing shipping information and paying a $1 delivery fee, aiming to collect credit card details.
5. The user decided to punish the scammer by creating a program to flood the scammer's payment processor with declined transactions.
6. The user identified that the payment processing system used the Luhn's algorithm to check card validity.
7. The user found a valid test card number (4007000000000270) that satisfied the algorithm.
8. The user created a Python program using the requests library to simulate declined transactions.
9. The program utilized multithreading to send multiple requests simultaneously, increasing the rate of declined transactions.
10. The user executed the program to flood the scammer's system with transaction decline requests, aiming to incur charges on the scammer for each attempt.
11. The user observed a significant increase in transaction IDs during the execution of the program.
12. The user emphasized the moral of the story, discouraging scamming behavior.