AI Analysis
The package shows low risks across network, shell, obfuscation, and credential aspects. While there are some concerns about metadata and maintenance, these do not strongly indicate malicious activity.
- Low risk scores in network, shell, obfuscation, and credential checks.
- Metadata risk suggests potential maintenance issues but does not indicate malicious behavior.
Per-check LLM notes
- Network: The observed network calls align with typical interactions for managing Atlassian Jira issues, indicating legitimate API usage.
- Shell: No shell execution patterns detected, suggesting no immediate risk related to command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows some signs of low maintenance and potential lack of transparency, but lacks clear indicators of malicious intent.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (47841 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
Found 5 network call pattern(s)
try: response = requests.put( f"{server_url}/rest/api/3/issue/{ticket_key}",try: response = requests.put( f"{server_url}/rest/api/3/issue/{ticket_key}/ase": f} response = requests.post(url, headers=headers, auth=auth, files=files) except Filtry: response = requests.post( f"{server_url}/rest/api/3/issue/{ticket_key}/co) try: response = requests.post( f"{server_url}/rest/api/3/issue", j
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
2 maintainer concern(s) found
Author "Pavan Bhatt" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a mini-application named 'AtlassianTaskTracker' that integrates with Jira and Confluence using the 'atlassian-modules' Python package. This application will serve as a task management tool for teams, allowing them to track tasks directly from their Jira board and document related information on Confluence pages. ### Features: 1. **User Authentication:** Implement a secure way to authenticate users through OAuth2 or API keys to access Jira and Confluence services. 2. **Task Creation & Management:** Allow users to create, update, delete, and assign tasks within Jira. The app should also support searching for tasks based on various criteria such as status, assignee, and due date. 3. **Document Integration:** For each task created in Jira, automatically generate a corresponding Confluence page where team members can add notes, files, and other relevant documentation. 4. **Notifications:** Set up real-time notifications for task updates and changes, which can be delivered via email or Slack. 5. **Custom Reports:** Provide customizable reports that summarize task statuses, progress, and key metrics for project managers. 6. **Integration with Other Tools:** Enable integration with other tools like Slack for seamless communication and task updates. ### Utilizing 'atlassian-modules': - Use 'atlassian-jira' module to interact with Jira's REST APIs for creating, updating, deleting, and managing tasks. - Leverage 'atlassian-confluence' module to manage content in Confluence, including creating new pages, adding attachments, and editing existing pages. - Implement authentication mechanisms provided by 'atlassian-connect-express' for secure API access. - Explore 'atlassian-api' for handling common tasks across Atlassian products, such as error handling and rate limiting. ### Steps to Build the Application: 1. **Set Up Development Environment:** Install necessary Python packages including 'atlassian-modules'. Configure your environment to handle OAuth2 authentication. 2. **Design User Interface:** Develop a simple yet effective UI using Flask or Django for web-based interaction or use a CLI interface if preferred. 3. **Implement Core Functionality:** Focus on implementing the core features listed above, ensuring that interactions with Jira and Confluence are smooth and efficient. 4. **Testing:** Rigorously test the application to ensure it works as expected, especially focusing on edge cases and error handling. 5. **Deployment:** Deploy the application to a cloud service provider like AWS or Heroku for easy access. 6. **Documentation:** Write comprehensive documentation explaining how to install, configure, and use the application, including any setup steps required for OAuth2 authentication.
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