AI Analysis
Final verdict: SAFE
The package AbstractRuntime has a low risk score due to its minimal interaction with external systems and lack of shell execution. The absence of network calls and shell commands does not indicate any signs of a supply-chain attack.
- No network calls detected.
- No shell execution patterns observed.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communications.
- Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized system command execution.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 2.0
Found 1 obfuscation pattern(s)
try: return base64.b64decode(value), artifact_ref, {k: _jsonable(v) for k, v in raw.items
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
Repository lpalbou/abstractruntime appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Laurent-Philippe Albou" 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 AbstractRuntime
Your task is to create a small but powerful utility application using the 'AbstractRuntime' package. This utility will serve as a simple workflow automation tool that can execute complex processes defined by users in a graphical interface. Here’s a step-by-step guide on how to build it: 1. **Project Setup**: Start by setting up your Python environment. Ensure you have Python installed, then install the 'AbstractRuntime' package along with any necessary dependencies. 2. **Define Workflow Components**: Use 'AbstractRuntime' to define basic components of workflows such as tasks, triggers, and conditions. These components should be modular and reusable. 3. **Graphical Interface**: Develop a simple GUI where users can drag and drop these workflow components to design their own custom workflows. The GUI should allow for easy connection between components, specifying input/output parameters, and setting execution conditions. 4. **Execution Engine**: Implement an execution engine that leverages 'AbstractRuntime' to run workflows as defined by the user in the GUI. This engine should support both synchronous and asynchronous execution modes. 5. **Persistence & Durability**: Utilize 'AbstractRuntime' to ensure that workflows can be saved and loaded from disk, allowing users to resume work at any point without losing progress. 6. **Monitoring & Logging**: Add functionality to monitor the status of running workflows and log details about their execution, including start/end times, duration, and any errors encountered. 7. **Testing & Validation**: Finally, thoroughly test your application to ensure it handles various scenarios correctly, including error recovery and handling unexpected inputs gracefully. Suggested Features: - Support for a wide range of workflow types (e.g., data processing, notification sending). - Integration with external services (via API calls). - Ability to pause/resume workflows. - Detailed documentation and tutorials for new users. How to Utilize 'AbstractRuntime': - For defining and managing workflow components, use 'AbstractRuntime' to create abstract representations of tasks and connections. - When executing workflows, leverage 'AbstractRuntime's capabilities to manage state and ensure durability across runs. - To save/load workflows, utilize 'AbstractRuntime's persistence features. - For monitoring and logging, integrate 'AbstractRuntime's logging mechanisms into your application.