ainfera

v1.1.0 suspicious
6.0
Medium Risk

The Inference of AI Agents. Drain-proof wallets, signed AgentCards (JWS), hash-chained AuditChains — out of the box.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to its network and shell command execution activities, despite having no signs of obfuscation or credential harvesting.

  • Moderate network risk due to outbound HTTP requests.
  • High shell risk due to interaction with GitHub's API and retrieval of authentication tokens.
Per-check LLM notes
  • Network: The package makes outbound HTTP requests, which could be for legitimate purposes but also might indicate an attempt to communicate with external servers for commands or data exfiltration.
  • Shell: The package executes shell commands that interact with GitHub's API and retrieve authentication tokens, which could pose a risk if not properly authorized, potentially leading to unauthorized access or data leakage.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting the package is not attempting to steal secrets.
  • Metadata: The package shows some red flags such as an author with no details and a new or inactive account, but lacks clear indicators of malicious intent.

📦 Package Quality Overall: Medium (6.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://ainfera.ai/docs/sdk-python
  • Detailed PyPI description (3029 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 64 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 41 commits in ainfera-ai/sdk
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • return try: r = httpx.post( f"{api_base.rstrip('/')}/v1/agents/install-from
  • imeout self._client = httpx.Client( base_url=base_url, timeout=timeout,
  • imeout self._client = httpx.AsyncClient( base_url=base_url, timeout=timeout,
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • """ try: handle = subprocess.check_output( ["gh", "api", "user", "-q", ".login"],
  • ).strip() token = subprocess.check_output( ["gh", "auth", "token"], text=True,
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: ainfera.ai>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 ainfera 
Create a secure financial tracking application using the Python package 'ainfera'. This application will allow users to securely manage their financial transactions and maintain a transparent audit trail. Here's a detailed breakdown of the requirements:

1. **User Registration**: Implement user registration where each user gets a unique AgentCard (JWS). This card will serve as a digital identity for the user within the application.

2. **Transaction Management**: Users should be able to add, edit, and delete transactions. Each transaction must be associated with the user's AgentCard and must include details like date, amount, category, and description.

3. **Audit Chain**: Maintain a hash-chained AuditChain for each user to ensure transparency and immutability of the transaction records. This chain should be updated every time a new transaction is added or an existing one is modified.

4. **Drain-Proof Wallets**: Integrate drain-proof wallets to secure user funds. These wallets should be resistant to unauthorized withdrawals, ensuring that only legitimate transactions are processed.

5. **Security Features**: Implement robust security measures such as encryption for sensitive data and two-factor authentication for enhanced security.

6. **Reporting**: Provide users with the ability to generate reports on their financial activities. Reports should be exportable in CSV format and should include a summary of all transactions along with the AuditChain.

7. **Integration with 'ainfera'**: Utilize the 'ainfera' package to handle the creation and management of AgentCards, the generation of AuditChains, and the implementation of drain-proof wallets. Ensure that all operations involving these components leverage the functionalities provided by 'ainfera'.

The application should be designed with a clean, user-friendly interface and should provide comprehensive documentation for both end-users and developers.

💬 Discussion Feed

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