AI Analysis
The package shows signs of potential code obfuscation and unusual coding practices, raising concerns about its intentions. However, there's no concrete evidence of malicious activity.
- High obfuscation risk due to use of random seeding and byte manipulation
- Maintainer has only one package, indicating possible lack of community or history
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external API interactions.
- Shell: No shell execution patterns detected, indicating no immediate risk of command execution.
- Obfuscation: The use of random seeding and byte manipulation with pickle.loads() suggests potential for code obfuscation or hiding functionality, which could be used maliciously.
- Credentials: No direct evidence of credential harvesting is present, but the unusual code patterns may warrant further investigation.
- Metadata: The maintainer has only one package, suggesting a new or less active account which may warrant further investigation.
Package Quality Overall: Medium (6.2/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Detailed PyPI description (6679 chars)
Some contribution signals present
Separate author ("Opentensor Foundation") and maintainer ("Latent Holdings") listedDevelopment Status classifier >= Beta
Partial type annotation coverage
161 type-annotated function signatures detected in source
Active multi-contributor project
4 unique contributor(s) across 100 commits in opentensor/async-substrate-interfaceSmall but multi-author team (3–4 contributors)
Heuristic Checks
No suspicious network call patterns found
Found 2 obfuscation pattern(s)
y payloads _rng = __import__("random") _rng.seed(42) _bare_bytes = [es everything else. Why: pickle.loads() on disk-backed data is an arbitrary-code-execution vec
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: latent.to>
All external links appear legitimate
Repository opentensor/async-substrate-interface appears legitimate
1 maintainer concern(s) found
Author "Opentensor Foundation" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a decentralized finance (DeFi) portfolio tracker using the 'async-substrate-interface' Python package. This application will allow users to monitor their assets across various Substrate-based blockchain networks. The app should support real-time asset value tracking, balance checking, and transaction history retrieval for any wallet address provided by the user. **Features to Include:** 1. **User Authentication:** Implement a simple login system where users can create accounts or log in using email/password. Store credentials securely. 2. **Wallet Address Input:** Users should be able to input one or multiple wallet addresses associated with different Substrate-based blockchains. 3. **Real-Time Asset Tracking:** Fetch and display the current value of assets held in each wallet address from the connected blockchain(s). Use the 'async-substrate-interface' package to interact with the blockchain APIs. 4. **Balance Checking:** Provide a feature to check the balance of all supported tokens/coins within the specified wallet addresses. 5. **Transaction History:** Allow users to view recent transactions made from/to their wallet addresses. Display relevant details like timestamp, amount, recipient/sender, etc. 6. **Notifications:** Implement push notifications or alerts when significant changes occur in the value of assets (e.g., price drop by more than 5%). 7. **Graphical Representation:** Offer visual graphs to show the performance of each asset over time. 8. **API Documentation:** Create comprehensive documentation for the API endpoints used within the application. **Utilizing 'async-substrate-interface':** - Use the package's asynchronous capabilities to efficiently fetch data from the blockchain without blocking the main thread. - Leverage its compatibility with 'py-substrate-interface' to ensure seamless integration with existing Substrate-based projects. - Explore advanced functionalities such as querying specific blocks, decoding extrinsics, and handling custom types if necessary. This project aims to showcase the versatility and power of 'async-substrate-interface' while providing practical utility for DeFi enthusiasts.
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