AI Analysis
Final verdict: SUSPICIOUS
The package exhibits some suspicious characteristics including an anonymous author and minimal activity in its git repository, which raises concerns about its legitimacy and origin.
- Anonymous author
- Low activity in the git repository
Per-check LLM notes
- Network: Network calls to check API status and health endpoints are typical for legitimate software checking service availability.
- Shell: No shell execution patterns detected, indicating no direct system command execution risk.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows some red flags such as an anonymous author and low activity in the git repository, but no clear evidence of malicious intent.
Heuristic Checks
Outbound Network Calls
score 3.0
Found 2 network call pattern(s)
| None: try: with urllib.request.urlopen(f"{api_url.rstrip('/')}/openapi.json", timeout=5) asURL) try: resp = httpx.get(f"{url}/health", timeout=10.0) resp.raise_for_status
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: agencycore.dev>
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 shortAuthor "" 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 agencycore-cli
Create a command-line interface (CLI) tool named 'AgencyHelper' using the 'agencycore-cli' Python package. This tool will streamline tasks related to customer relationship management (CRM), email outreach, and data analysis for marketing agencies. Your goal is to build a user-friendly and efficient tool that can be integrated into daily workflows. ### Features: 1. **User Management**: Allow users to create, read, update, and delete their profiles. 2. **Campaign Management**: Enable users to create, edit, and track marketing campaigns. Each campaign should have details like start date, end date, budget, and performance metrics. 3. **Email Outreach**: Provide functionality to draft, send, and schedule emails. Users should be able to attach templates and customize emails before sending. 4. **Data Analysis**: Implement basic data analysis tools to help users understand campaign performance. Include features like generating reports, visualizing data, and identifying trends. 5. **Integration**: Ensure seamless integration with popular CRMs and email services. ### Steps to Build 'AgencyHelper': 1. **Setup Project Structure**: Initialize a new Python project and install 'agencycore-cli'. Organize your project structure to include modules for each feature. 2. **User Authentication**: Implement a simple authentication system to secure user profiles. 3. **CRUD Operations for Campaigns**: Develop functions to perform CRUD operations on campaigns within the CRM. 4. **Email Drafting and Scheduling**: Utilize 'agencycore-cli' to facilitate email drafting and scheduling. Ensure users can attach templates and customize emails. 5. **Data Visualization**: Use libraries like matplotlib or seaborn to visualize campaign performance data. Generate reports based on user-defined criteria. 6. **Testing and Documentation**: Write tests to ensure all functionalities work as expected. Document the code and provide usage instructions for new users. 7. **Deployment**: Package your CLI tool as a standalone executable and deploy it for use by marketing professionals. ### How 'agencycore-cli' is Utilized: - **For User Management**: Leverage 'agencycore-cli' to authenticate users and manage their profiles. - **For Campaign Management**: Use 'agencycore-cli' to interact with the CRM API, allowing users to manage campaigns efficiently. - **For Email Outreach**: Integrate 'agencycore-cli' for email handling, including drafting, sending, and scheduling emails. - **For Data Analysis**: While 'agencycore-cli' might not directly handle data visualization, its integration capabilities can be used to fetch necessary data for analysis. Your task is to design and implement these features using best practices in Python development and ensure the application is robust, scalable, and user-friendly.