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CONFU: Configuration Fuzzing Testing Framework for Software Vulnerability Detection.

Huning Dai¹, Christian Murphy, Gail Kaiser

¹Department of Computer Science Columbia University New York, NY 10027 USA.

International Journal of Secure Software Engineering

|November 2, 2010

Summary

This summary is machine-generated.

Configuration Fuzzing mutates application configurations during runtime to uncover hidden software vulnerabilities. This novel approach enhances security testing by exploring specific conditions that traditional fuzz testing may miss.

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Area of Science:

Software Engineering
Computer Security
System Testing

Background:

Software vulnerabilities often depend on specific configurations and runtime environments.
Traditional fuzz testing lacks guarantees on input validity and exploration coverage.
Detecting condition-dependent vulnerabilities remains a challenge.

Purpose of the Study:

Introduce a new testing methodology, Configuration Fuzzing, to address limitations in detecting condition-dependent software vulnerabilities.
Develop and evaluate a prototype framework, ConFu, for implementing Configuration Fuzzing.
Demonstrate the feasibility and performance of Configuration Fuzzing in identifying software security flaws.

Main Methods:

Configuration Fuzzing mutates the running application's configuration at specific execution points.
Testing is performed within the actual deployment environment.
Security invariants are continuously monitored; violations indicate vulnerabilities.

Main Results:

The ConFu framework successfully implements the Configuration Fuzzing methodology.
Case studies demonstrated the feasibility of detecting condition-dependent vulnerabilities.
Performance evaluation indicated the effectiveness of the approach.

Conclusions:

Configuration Fuzzing is a viable technique for uncovering software vulnerabilities missed by traditional methods.
The ConFu framework provides a practical tool for implementing this advanced testing approach.
This methodology enhances the robustness and security of software systems by testing under realistic, dynamic conditions.