alfard

v0.1.26 suspicious
6.0
Medium Risk

Local AI agent runtime — secure by default, private by design.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant risks related to network and credential handling, with moderate shell manipulation concerns. While no clear signs of malicious intent are present, the combination of these risks raises suspicion about its legitimacy and security posture.

  • Unexpected network calls to external services
  • Execution of commands affecting the user's system
  • Retrieval of environment variables for bot tokens
Per-check LLM notes
  • Network: The package makes unexpected network calls to Slack and GitHub which may indicate unauthorized data transmission.
  • Shell: The package executes commands on the user's system to manipulate the clipboard, suggesting it could be used for unintended purposes like copying sensitive information.
  • Obfuscation: No obfuscation patterns detected in the provided code snippets.
  • Credentials: The code appears to be retrieving environment variables for bot tokens and channel IDs, which could indicate legitimate use but also poses a risk of credential harvesting if not properly secured.
  • Metadata: Low risk due to lack of suspicious flags, but concerns over maintainer history indicate potential low effort or inactive status.

📦 Package Quality Overall: Low (4.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.alfard.dev
  • Detailed PyPI description (15057 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 5.0

Partial type annotation coverage

  • 292 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in waterduckpani/alfard
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • mport json as _json req = urllib.request.Request( "https://slack.com/api/auth.test",
  • , ) try: with urllib.request.urlopen(req, timeout=10) as resp: data = _json.l
  • > str: try: req = urllib.request.Request( "https://api.github.com/repos/mcp-shark
  • son"}, ) with urllib.request.urlopen(req, timeout=10) as r: return json.loads
  • " ) try: with urllib.request.urlopen(url, timeout=15) as r: for line in r.rea
  • ersion}...") try: urllib.request.urlretrieve(url, tmp) except Exception as exc: p
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • form == "darwin": subprocess.run(["pbcopy"], input=text.encode(), check=True) ret
  • tform == "linux": subprocess.run(["xclip", "-selection", "clipboard"],
  • "win32": result = subprocess.run( ["clip"], input=text.encode
  • try: result = subprocess.run(["gog", "auth", "credentials", tmppath], env=_gog_env())
  • if headless: step1 = subprocess.run( ["gog", "auth", "add", email, "--services", "gm
  • n").strip() result2 = subprocess.run( ["gog", "auth", "add", email, "--services", "gm
⚠ Credential Harvesting score 10.0

Found 5 credential access pattern(s)

  • alse channel_id_str = os.environ.get("DISCORD_CRON_CHANNEL_ID") if not channel_id_str:
  • one channel_id_str = os.environ.get("DISCORD_CRON_CHANNEL_ID") if not channel_id_str:
  • WebClient token = os.environ.get("SLACK_BOT_TOKEN") if not token: return
  • "channel") or os.environ.get("SLACK_APPROVAL_CHANNEL") ) except Exception:
  • eption: channel = os.environ.get("SLACK_APPROVAL_CHANNEL") if not channel: retu
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository waterduckpani/alfard appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with alfard 
Create a privacy-focused local note-taking application called 'PrivateNote' using the 'alfard' Python package. This application will allow users to securely store and manage their notes locally on their device without ever transmitting data to any external servers, ensuring maximum privacy and security.

### Core Features:
- **User Authentication**: Implement a simple user authentication system where users can create accounts and log in securely.
- **Note Management**: Users should be able to create, read, update, and delete notes.
- **Encryption**: All notes should be encrypted before being stored locally. Use the 'alfard' package's encryption capabilities to ensure that even if someone gains access to the storage, they cannot read the contents of the notes.
- **Search Functionality**: Provide a search feature that allows users to find specific notes based on keywords or phrases contained within the notes.
- **Backup & Restore**: Enable users to backup their encrypted notes to a USB drive or another local storage location, and restore them when needed.

### Utilizing 'alfard':
- **Local Agent Runtime**: Use 'alfard' to set up a local runtime environment for your application, ensuring that all operations are handled securely and privately.
- **Secure Data Storage**: Leverage 'alfard's secure data storage mechanisms to handle the encryption and decryption of notes.
- **Privacy Enhancements**: Explore additional privacy features provided by 'alfard', such as secure communication channels within the application, if applicable.

Your task is to outline the architecture of 'PrivateNote', detail the implementation steps, and demonstrate how each feature integrates with the 'alfard' package to enhance privacy and security.

💬 Discussion Feed

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