AI Analysis
Final verdict: SUSPICIOUS
The package shows low risk in terms of network, shell, obfuscation, and credential activities but has a high metadata risk due to recent creation and unusual commit patterns.
- High metadata risk
- Recent creation and low activity
Per-check LLM notes
- Network: The use of requests.Session() with retries is common for making network calls and handling HTTP requests, suggesting legitimate functionality rather than malicious intent.
- Shell: No shell execution patterns detected, indicating low risk for executing arbitrary commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting that the package does not engage in unauthorized secret or credential collection.
- Metadata: The recent creation, low activity, and suspicious commit pattern suggest potential risk.
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
agent self.session = requests.Session() retry = Retry( total=max_retries,
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 10.0
Git history flags: Repository created very recently: 5 day(s) ago (2026-06-01T10:44:23Z)
Repository created very recently: 5 day(s) ago (2026-06-01T10:44:23Z)Repository has zero stars and zero forksSingle contributor with only 3 commit(s) — possibly throwaway accountAll 3 commits happened within 24 hours
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "AgenticDome" 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 agenticdome-python-sdk
Create a mini-application that acts as a personal cybersecurity advisor using the 'agenticdome-python-sdk' package. This application will serve as a tool for individuals to monitor and manage their online security, leveraging the power of the AgentGuard Intelligence Engine and Action Firewall provided by the SDK. The application should include the following core functionalities: 1. **Security Assessment**: Users can input their current security settings and practices (e.g., password strength, firewall status, antivirus software). The application will then use the SDK to analyze these inputs against best practices and known threats, providing a detailed assessment report. 2. **Threat Detection**: The app will periodically check for potential threats using the SDK’s threat detection capabilities. It will notify users about any suspicious activities or potential breaches in real-time. 3. **Action Recommendations**: Based on the security assessment and threat detection results, the application will provide actionable recommendations to improve security. These recommendations could range from changing passwords to updating software. 4. **Custom Alerts**: Users should be able to set up custom alerts for specific types of threats or security events. When these conditions are met, the application will send notifications via email or SMS. 5. **Dashboard Interface**: Develop a simple yet intuitive dashboard where users can view their security status, recent alerts, and action history. To achieve these functionalities, you'll need to utilize key features of the 'agenticdome-python-sdk', such as initializing the SDK, performing security assessments, integrating threat detection services, and managing alerts. Your task is to design a fully functional prototype that demonstrates each feature effectively.