
Research
2025 Report: Destructive Malware in Open Source Packages
Destructive malware is rising across open source registries, using delays and kill switches to wipe code, break builds, and disrupt CI/CD.
verifyTelegram
Advanced tools
This Python module securely validates and extracts user data from a URL-encoded string, using HMAC and SHA-256 for data integrity. It features a User class to structure user information and a Data class for validation and data parsing. Ideal for web applications needing secure user authentication and data management, it's easy to integrate and use.
This Python module is designed to handle the validation and extraction of user data from a URL-encoded string. It uses HMAC and SHA-256 hashing to ensure data integrity and security. The module provides a simple way to validate input data and parse it into a structured User object.
This module requires Python 3.6+ and uses the following standard libraries:
hmachashliburllibjsondataclassesNo external libraries are required for this module. Simply include the code in your Python project.
The User class is a data class that holds the following information about a user:
id: The user's unique identifier (integer).first_name: The user's first name (string).last_name: The user's last name (string).username: The user's username (string).language_code: The language code of the user (string).is_premium: A boolean indicating if the user has a premium account.allows_write_to_pm: A boolean indicating if the user allows writing to private messages.The Data class is responsible for validating input data and extracting user information from a URL-encoded string.
To create an instance of the Data class, you need to provide a bot token:
data_instance = Data(BOT_TOKEN="your_bot_token_here")
This method checks if the provided data is valid by comparing the generated hash with the initial data hash.
is_valid = data_instance.is_valid_data(INIT_DATA_HASH="your_init_data_hash", DATA_CHECK_STRING="your_data_check_string")
This static method extracts user data from the data check string and returns a User object.
user = Data.GetData(DATA_CHECK_STRING="your_data_check_string")
Here's an example of how to use the module:
BOT_TOKEN = "1231212:sdsadasdsadasd231ec"
INIT_DATA_HASH = "90677c2f2e1326cdb4d5cd781905c375f5397b8f6dbee501487385aa3faf3e0e"
DATA_CHECK_STRING = "auth_date=1721578504&chat_instance=-5432073769796079823&chat_type=private&user=%7B%22id%22%3A6195030789%2C%22first_name%22%3A%22._.%22%2C%22last_name%22%3A%22%22%2C%22username%22%3A%22ksdaskdnc2w%22%2C%22language_code%22%3A%22en%22%2C%22allows_write_to_pm%22%3Atrue%7D"
data_instance = Data(BOT_TOKEN)
if data_instance.is_valid_data(INIT_DATA_HASH, DATA_CHECK_STRING):
user = Data.GetData(DATA_CHECK_STRING)
print(f"User {user.first_name} ({user.username}) is authenticated.")
else:
print("Invalid data provided.")
This module is licensed under the MIT License. Feel free to use and modify it as needed.
FAQs
This Python module securely validates and extracts user data from a URL-encoded string, using HMAC and SHA-256 for data integrity. It features a User class to structure user information and a Data class for validation and data parsing. Ideal for web applications needing secure user authentication and data management, it's easy to integrate and use.
We found that verifyTelegram demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Research
Destructive malware is rising across open source registries, using delays and kill switches to wipe code, break builds, and disrupt CI/CD.

Security News
Socket CTO Ahmad Nassri shares practical AI coding techniques, tools, and team workflows, plus what still feels noisy and why shipping remains human-led.

Research
/Security News
A five-month operation turned 27 npm packages into durable hosting for browser-run lures that mimic document-sharing portals and Microsoft sign-in, targeting 25 organizations across manufacturing, industrial automation, plastics, and healthcare for credential theft.