PANTHER: Pluginizable Testing Environment for Network Protocols

2025-03-04

AI Summary

This paper addresses key challenges in network protocol testing and formal verification—namely, low flexibility, poor reproducibility, and limited scalability. To this end, we propose PANTHER, a modular framework featuring a novel plugin-based architecture. PANTHER integrates state-aware fuzzing, dynamic behavioral adaptation, Ivy-based formal verification, and Shadow network emulation, all orchestrated via YAML-driven workflows to ensure automated configuration and experiment reproducibility. The framework supports protocol-agnostic extensibility, seamless integration of multi-scenario plugins, and rigorous verification of complex security properties. Experimental evaluation demonstrates that PANTHER significantly improves testing efficiency and scalability, successfully uncovering deep-seated vulnerabilities in mainstream protocol stacks. Crucially, it bridges the gap between formal rigor and engineering robustness, enabling both sound verification and practical deployment.

Technology Category

• Planning, Routing, and Scheduling: Plan Execution and Monitoring
• Application Domains: Mobility, Driving & Flight
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

In this paper, we introduce PANTHER, a modular framework for testing network protocols and formally verifying their specification. The framework incorporates a plugin architecture to enhance flexibility and extensibility for diverse testing scenarios, facilitate reproducible and scalable experiments leveraging Ivy and Shadow, and improve testing efficiency by enabling automated workflows through YAML-based configuration management. Its modular design validates complex protocol properties, adapts to dynamic behaviors, and facilitates seamless plugin integration for scalability. Moreover, the framework enables a stateful fuzzer plugin to enhance implementation robustness checks.

Problem

• Modular framework for testing network protocols
• Formal verification of protocol specifications
• Enhance testing efficiency and robustness checks

Innovation

• Modular framework for network protocol testing
• Plugin architecture for flexible, extensible testing scenarios
• Automated workflows via YAML-based configuration management