🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious activity, but the presence of suspicious non-HTTPS links and a new maintainer account raises concerns about potential supply-chain risks.

Suspicious non-HTTPS links
New maintainer account

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no direct system command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating safe handling of secrets and credentials.
Metadata: Suspicious non-HTTPS links and new maintainer account increase suspicion but no clear malicious indicators.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (13259 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 7.0

Partial type annotation coverage

Classifier: Typing :: Typed
593 type-annotated function signatures detected in source

✦ High Multiple Contributors 8.0

Active multi-contributor project

3 unique contributor(s) across 100 commits in kaaass/opencode-sdk
Small but multi-author team (3–4 contributors)

🔬 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

No author email provided

⚠ Suspicious Page Links score 4.0

Found 2 suspicious link(s) on the package page

Non-HTTPS external link: http://my.test.server.example.com:8083
Non-HTTPS external link: http://my.test.proxy.example.com

✓ Git Repository History

Repository kaaass/opencode-sdk appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Opencode SDK" 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 ai4pa_opencode_sdk

Create a Python-based mini-application named 'AI4PAMonitor' which leverages the functionalities of the 'ai4pa_opencode_sdk' package to monitor and analyze patient data in real-time from various healthcare devices. This application will serve as a tool for healthcare professionals to quickly assess patient health status and detect any anomalies early on. Here’s a detailed breakdown of the project scope and features:

1. **Real-Time Data Collection**: Integrate the app to receive live data streams from multiple patient monitoring devices. Use the 'ai4pa_opencode_sdk' to establish secure connections and handle data transmission efficiently.
2. **Data Analysis**: Implement machine learning models using the 'ai4pa_opencode_sdk' to process and analyze incoming patient data. These models should be capable of identifying patterns indicative of potential health issues such as irregular heartbeat, sudden drops in blood pressure, etc.
3. **Alert System**: Develop an alert system within the application that triggers notifications (via email or SMS) to healthcare providers if any critical health conditions are detected based on the analysis performed by the ML models.
4. **User Interface**: Design a simple yet effective user interface where healthcare staff can view patient data in real-time, including historical trends and alerts. The UI should allow users to filter data based on different criteria like time periods, patient IDs, etc.
5. **Customizable Settings**: Allow users to customize the sensitivity levels of the alerts and the types of data they want to monitor closely. This feature will enable the system to adapt to the specific needs of different healthcare facilities.
6. **Reporting Tools**: Incorporate reporting tools that generate detailed reports on patient health statuses over specified time frames. These reports should include visualizations like graphs and charts to make the data more understandable.

The 'ai4pa_opencode_sdk' package plays a crucial role in enabling real-time data processing and analysis capabilities, making it possible to develop an efficient and reliable monitoring tool. Your task is to write clean, well-documented Python code, ensuring that each module of the application is modular and reusable.