🤖 AI Analysis

Final verdict: SAFE

The package appears to be primarily focused on serving as an API server with legitimate features and does not show strong indicators of malicious intent. The presence of base64 decoding and encryption might suggest some level of obfuscation but does not necessarily imply malicious activity.

moderate obfuscation risk due to use of encryption
low credential risk
non-HTTPS links to local addresses

Per-check LLM notes

Obfuscation: The use of base64 decoding and encryption with an IV suggests data is being decrypted, which could be legitimate for secure data handling but also might indicate obfuscation to hide code logic.
Credentials: No clear patterns indicating credential harvesting were found, suggesting low risk.
Metadata: The maintainer has a single package and there are non-HTTPS links present, but they appear to be local addresses which might not pose an immediate risk.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

_value"]} response = requests.get(path, headers=headers) response.raise_for_status()
} response = requests.post(path, headers=headers, data=body) response.raise_for
} response = requests.put(path, headers=headers, data=body) response.raise_for
=eternal" response = requests.post(path) response.raise_for_status() return Sso
"Token": token} with httpx.Client() as client: response = client.post(url, headers
earer {token}"} with httpx.Client() as client: response = client.get(url, headers=

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

encrypted_bytes = base64.b64decode(encrypted_data) iv = encrypted_bytes[:16]
None metadata = pickle.loads(data[b'metadata']) if data.get(b'metadata') else None

✓ 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: advantech.com.cn

⚠ Suspicious Page Links score 8.0

Found 4 suspicious link(s) on the package page

Non-HTTPS external link: http://127.0.0.1:10053
Non-HTTPS external link: http://127.0.0.1:8080/api/v1`
Non-HTTPS external link: http://127.0.0.1:8080/docs`
Non-HTTPS external link: http://127.0.0.1:8080/site`

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Zijie Zhang" 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 agent-api-server

Create a personalized chatbot assistant using the 'agent-api-server' Python package. This project will serve as a versatile tool for users to interact with through a simple command-line interface (CLI). The chatbot will be capable of performing various tasks such as setting reminders, providing weather updates, answering general knowledge questions, and more.

Step 1: Setup your development environment
- Ensure Python is installed on your system.
- Install the 'agent-api-server' package using pip.
- Set up a virtual environment for your project.

Step 2: Initialize the Agent API Server
- Start the 'agent-api-server' to enable interaction with the chatbot backend.
- Configure the server to connect to external APIs for functionalities like weather updates and general knowledge queries.

Step 3: Develop the CLI Interface
- Use Python's built-in modules or a library like Click to create a user-friendly CLI.
- Implement commands for initiating conversations, sending messages, and handling responses from the chatbot.

Step 4: Integrate Functionality
- Add a feature for setting reminders using the chatbot. Users should be able to specify dates, times, and details for their reminders.
- Incorporate a weather update module where users can ask about the current weather conditions in any location.
- Allow the chatbot to answer general knowledge questions by integrating it with an appropriate API.

Step 5: Enhance User Experience
- Implement error handling for invalid inputs or requests.
- Provide clear instructions and help messages within the CLI.
- Ensure the chatbot's responses are natural and context-aware.

The 'agent-api-server' package is central to this project as it provides the necessary infrastructure for the chatbot's web capabilities. It handles the communication between the CLI and the chatbot's backend, allowing for seamless interaction and the execution of various tasks based on user commands. By leveraging 'agent-api-server', you can focus on enhancing the chatbot's functionality and user experience without worrying about the underlying web server implementation.