🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant obfuscation and uses network calls with custom headers, raising concerns about its true intentions and functionality.

High obfuscation risk
Custom network headers

Per-check LLM notes

Network: The presence of network calls with custom headers suggests the package may be interacting with an external service, which is not inherently suspicious but should be reviewed to ensure it aligns with the package's intended functionality.
Shell: No shell execution patterns were detected.
Obfuscation: The use of base64 decoding without clear purpose suggests potential obfuscation or hiding of code/data.
Credentials: No direct evidence of credential harvesting patterns found.
Metadata: The maintainer has only one package, which might indicate a new or less active account, but no other suspicious activities are flagged.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

: self._session = aiohttp.ClientSession( headers={ "Cookie": sel

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

as bytes. """ return base64.b64decode(fix_base64_padding(payload)) def extract_ref_id(payload: s

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository TheBrainAir/afragment appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "TheBrainAir" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with afragment

Create a command-line tool using Python that allows users to manage their Telegram account via the Fragment.com API. This tool will utilize the 'afragment' package, which provides asynchronous functions to interact with the API for purchasing Telegram Stars, upgrading to Premium status, and performing TON top-ups. The application should offer the following functionalities:

1. User Authentication: Implement a secure method for users to authenticate their Telegram account credentials. Use these credentials to fetch the user's current account status.
2. Account Status: Display the current status of the user's Telegram account including details such as whether they have Telegram Stars, their premium subscription status, and their TON balance.
3. Purchase Telegram Stars: Allow users to purchase Telegram Stars from a pre-defined list of available packages. Users should be able to select the number of stars they wish to buy and confirm the transaction.
4. Upgrade to Premium: Provide functionality for users to upgrade their Telegram account to Premium. Include options for different duration subscriptions and allow users to choose based on their preferences.
5. TON Top-Up: Enable users to top-up their Telegram TON wallet. Users should be able to specify the amount they want to add, and the tool should facilitate the payment process.
6. Transaction History: Maintain a history of all transactions made through the tool, including purchases of Telegram Stars, upgrades to Premium, and TON top-ups. This history should be stored locally and accessible within the application.
7. Help and Documentation: Include a help menu that explains how to use each feature of the application. Additionally, provide documentation on how to set up the application and troubleshoot common issues.

To achieve these functionalities, you will need to utilize the 'afragment' package effectively. Start by installing the package using pip and then explore its documentation to understand how to authenticate users, make API calls for purchasing Telegram Stars, upgrading to Premium, and topping up TON. Ensure that your application handles errors gracefully and provides informative feedback to users at every step.