aria-agent

v1.0.0 suspicious
5.0
Medium Risk

ARIA — Autonomous Reasoning and Intelligent Agent. Your project-aware coding partner.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network activity, shell execution, obfuscation, and credential harvesting. However, significant metadata risks, such as an untraceable repository and lack of author details, raise concerns about potential malicious intent.

  • Untraceable repository
  • No author details provided
Per-check LLM notes
  • Network: No network calls detected, indicating low risk.
  • Shell: Shell execution commands are primarily for initializing environments and setting up projects, which could be legitimate but require scrutiny to ensure no unintended actions.
  • Obfuscation: No obfuscation patterns detected, suggesting low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows several red flags including an untraceable repository, a single release from a possibly new or inactive account, and no author details.

📦 Package Quality Overall: Low (3.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (3411 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

  • 33 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

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • nts=True, exist_ok=True) subprocess.run("git init", shell=True, cwd=workspace, capture_output=True)
  • fastapi", "django"]): subprocess.run("python3 -m venv .venv", shell=True, cwd=workspace, capture_
  • ess", "typescript"]): subprocess.run("npm init -y", shell=True, cwd=workspace, capture_output=Tru
  • tr: try: result = subprocess.run( command, shell=True, capture_output=True,
  • subprocess.run("git init", shell=True, cwd=workspace, capture_output=True) (workspace / ".gi
  • .run("python3 -m venv .venv", shell=True, cwd=workspace, capture_output=True) (workspace / "
✓ Credential Harvesting

No credential harvesting patterns detected

✓ 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 aria-agent 
Create a Python-based task management application called 'TaskMaster' that leverages the 'aria-agent' package to assist in automating and optimizing daily tasks. TaskMaster should allow users to create, edit, delete, and manage various types of tasks such as reminders, appointments, and recurring events. Additionally, it should integrate with popular calendar services like Google Calendar or Outlook to synchronize tasks seamlessly.

Key Features:
1. User Authentication: Implement secure user authentication using OAuth2 for logging in and managing multiple accounts.
2. Task Management: Enable users to create, view, update, and delete tasks directly within the app. Tasks can include details such as title, description, due date, priority level, and tags.
3. Scheduling & Reminders: Automatically schedule tasks based on user preferences and set reminders via email or push notifications.
4. Integration with External Services: Sync tasks with Google Calendar or Outlook for cross-platform task management.
5. AI-Powered Suggestions: Utilize the 'aria-agent' package to provide intelligent suggestions for task prioritization, deadline adjustments, and time management tips based on historical data and user behavior.
6. Reporting & Analytics: Generate reports and analytics on task completion rates, average time spent per task, and other relevant metrics.

How to Use 'aria-agent':
- For task prioritization and scheduling, use 'aria-agent' to analyze task descriptions and user inputs to suggest optimal times and priorities for each task.
- To enhance user experience, implement an AI-driven feature where 'aria-agent' learns from user interactions and provides personalized recommendations for improving productivity.
- Integrate 'aria-agent' into the reporting module to offer insights based on machine learning analysis of user data.

Your goal is to develop a robust, user-friendly task management application that not only streamlines daily routines but also enhances efficiency through intelligent automation and personalized insights.

💬 Discussion Feed

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