ageri-platform

v0.5.0 suspicious
7.0
High Risk

Ageri — self-hosted personal-AI chief-of-staff platform. Runs 24/7, remembers across sessions, coordinates specialist skills across your work + life.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant risks related to network communication, shell execution, and credential handling, suggesting potential vulnerabilities or malicious intent.

  • High network and shell execution risks
  • Potential for credential harvesting
  • Lack of transparency in development history
Per-check LLM notes
  • Network: The network calls indicate the package communicates with an external API, which could potentially be used for unauthorized data transmission.
  • Shell: The use of shell execution functions suggests the package can execute commands on the system, posing a risk for potential exploitation or malicious activities.
  • Obfuscation: The use of direct calls like open(), eval(), and exec() without clear purpose can indicate potential for code injection or obfuscation.
  • Credentials: The presence of getpass.getpass indicates an attempt to securely retrieve user input such as passwords, but it could also be used to harvest credentials without proper context.
  • Metadata: The package shows signs of being newly created with limited maintainer history and no public git repository.

📦 Package Quality Overall: Low (3.6/10)

○ 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.ageri.ai
  • Brief PyPI description (765 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 664 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • }).encode() req = urllib.request.Request( f"{self._base_url}/api/chat",
  • ) with urllib.request.urlopen(req, timeout=120) as resp: data = js
  • [str, str], bytes]: req = urllib.request.Request(url, method=method) for k, v in (headers or {}).
  • r(k, v) try: with urllib.request.urlopen(req, timeout=timeout) as resp: return re
  • e endpoint. """ req = urllib.request.Request(url, method=method, data=body) for k, v in (head
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • # Direct calls: open(), eval(), exec(), … if isinstance(node.func, ast.Name)
  • m typing import Any logger = __import__("logging").getLogger(__name__) class PlaygroundRunError(Exception):
⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • # Attribute calls: os.system(), subprocess.run(), … elif ( is
  • _call(): result = subprocess.run( [self._pro_cli_bin, "--dangerously-skip-per
  • d)) try: result = subprocess.run( cmd, capture_output=True,
  • ne.""" try: rev = subprocess.run( ["git", "-C", str(target_dir), "rev-parse", "HE
  • , " ".join(cmd)) result = subprocess.run(cmd, capture_output=True, text=True) if result.returncod
  • Attribute calls: os.system(), subprocess.run(), … elif ( isinstance(node.func
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • str: try: return getpass.getpass(f" {prompt}: ").strip() except (EOFError, KeyboardInter
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 ageri-platform 
Develop a personalized task management and reminder app using the 'ageri-platform' Python package. This app will serve as a digital chief of staff, helping users manage their daily tasks, set reminders, and coordinate various aspects of their professional and personal lives. Here’s a detailed plan on how to implement it:

1. **Setup Environment**: Install Python and the necessary libraries including 'ageri-platform'. Ensure you have the latest version of the package installed.

2. **User Interface Design**: Create a user-friendly interface where users can input tasks, set reminders, and view their schedules. Consider developing this either as a CLI tool or a simple web application using Flask or Django.

3. **Task Management**: Implement functionalities for adding, editing, deleting, and marking tasks as completed. Each task should include details like title, description, due date, and priority level.

4. **Reminder System**: Utilize 'ageri-platform' to set up a reminder system that sends notifications based on the user-defined timeframes. The reminders should be persistent, meaning they should still be effective even if the user closes the application.

5. **Integration with Specialist Skills**: Leverage the 'ageri-platform' to integrate with other AI services for specialized tasks such as scheduling meetings, sending emails, or even managing social media posts. This integration should be seamless and should not require manual intervention from the user.

6. **Persistent Memory Across Sessions**: Ensure that all user data is saved and accessible across different sessions. 'ageri-platform' should help maintain the context and history of interactions so that the app can remember past tasks and reminders even after the user logs out.

7. **Security Measures**: Implement security measures to protect user data. Use encryption for sensitive information and ensure that the data stored locally or in the cloud is secure.

8. **Testing and Deployment**: Thoroughly test the application for any bugs or usability issues. Once tested, deploy the application either as a local service or a cloud-based service depending on the user base.

By following these steps, you'll create a robust and personalized task management and reminder app that leverages the capabilities of 'ageri-platform' to enhance productivity and organization.