AI Analysis
Final verdict: SUSPICIOUS
The package has no immediate signs of malicious behavior such as network calls, shell executions, or obfuscation. However, the metadata risk score is high due to suspicious activity patterns, suggesting potential malicious intent.
- Metadata risk score is high at 7/10
- No other direct malicious activities detected
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution detected, which is typical and indicates the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
- Metadata: The package shows signs of being newly created with suspicious activity patterns indicative of potential malicious intent.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
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: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 7.5
Git history flags: Repository created very recently: 0 day(s) ago (2026-06-05T09:34:50Z)
Repository created very recently: 0 day(s) ago (2026-06-05T09:34:50Z)Repository appears empty (size = 0)All 6 commits happened within 24 hours
Maintainer History
score 8.0
4 maintainer concern(s) found
Only one version has ever been released — brand new packagePackage uploaded less than 24 hours ago (2026-06-05T10:01:56.000Z)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 pull-cli
Create a command-line utility named 'ConfluenceExtractor' using the Python package 'pull-cli'. This utility aims to streamline the process of extracting content from Atlassian Confluence pages into structured data formats such as JSON or CSV. The utility should support multiple user authentication methods including API tokens and OAuth2, and it should be able to handle large volumes of data efficiently. Additionally, include an option for users to specify which parts of the page content they want to extract, such as only images, attachments, or specific sections of text. The application should also feature a preview mode where users can see a sample of the extracted data before saving it to disk. Finally, implement error handling and logging to ensure robustness and ease of debugging.