🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate risk profile due to network and shell execution risks, alongside questionable metadata suggesting it might originate from a less reputable source.

network risk of 5/10
shell risk of 8/10
metadata risk of 7/10

Per-check LLM notes

Network: Network calls to a backend server suggest potential for data exfiltration or C2 communication.
Shell: Executing shell commands can be high risk as it may lead to arbitrary command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating secure handling of sensitive information.
Metadata: The package shows signs of potentially being a throwaway account with minimal activity and contributions, raising concerns about its legitimacy.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

backend_url request = urllib.request.Request( f"{base_url}{path}", data=j
try: with urllib.request.urlopen(request, timeout=20) as response: ra
""" request = urllib.request.Request( f"{self.backend_url}{path}",
backend_url request = urllib.request.Request( f"{base_url}{path}", data=b

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

return True try: subprocess.run(command, check=True) except (FileNotFoundError, subproce

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: agentmemorylabs.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 5.0

Git history flags: Very few commits: 2 total

Very few commits: 2 total
Single contributor with only 2 commit(s) — possibly throwaway account

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

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 agentic-memory-hermes

Create a personalized task management application using the 'agentic-memory-hermes' package. This application will allow users to manage their daily tasks efficiently, with features such as adding new tasks, marking tasks as completed, setting reminders, and categorizing tasks into different projects or categories.

The application should have the following core functionalities:
1. Users can add new tasks with descriptions, deadlines, and priorities.
2. Tasks can be marked as completed, which will update the status of the task in the system.
3. Users can set reminders for upcoming tasks via email notifications.
4. Tasks can be categorized into different projects or categories for better organization.
5. A search function to find specific tasks based on keywords or dates.
6. Integration with 'agentic-memory-hermes' to streamline the setup process of any additional task-related plugins or services, ensuring that the user experience is seamless and efficient.

To utilize the 'agentic-memory-hermes' package effectively, follow these steps:
1. Begin by installing the 'agentic-memory-hermes' package using pip.
2. Use the package to install necessary plugins or services for task management, such as calendar integration, email reminder services, or project management tools.
3. Integrate these plugins and services into your application to enhance its functionality.
4. Ensure that the application can automatically configure and manage these plugins through the 'agentic-memory-hermes' package, reducing the need for manual setup and configuration.

Your goal is to create a fully-functional mini-app that not only manages tasks but also leverages the power of 'agentic-memory-hermes' to provide a seamless and efficient user experience.