Leveraging Textual Specifications for Grammar-Based Fuzzing of Network Protocols

Samuel Jero     Maria Leonor Pacheco     Dan Goldwasser     Cristina Nita-Rotaru    
Innovative Applications of Artificial Intelligence (IAAI), 2019


Grammar-based fuzzing is a technique used to find software vulnerabilities by injecting well-formed inputs generated following rules that encode application semantics. Most grammar-based fuzzers for network protocols rely on human experts to manually specify these rules. In this work we study automated learning of protocol rules from textual specifications (i.e. RFCs). We evaluate the automatically extracted protocol rules by applying them to a state-of-the-art fuzzer for transport protocols and show that it leads to a smaller number of test cases while finding the same attacks as the system that uses manually specified rules.

Bib Entry

    author = "Samuel Jero and Maria Leonor Pacheco and Dan Goldwasser and Cristina Nita-Rotaru",
    title = "Leveraging Textual Specifications for Grammar-Based Fuzzing of Network Protocols",
    booktitle = "Innovative Applications of Artificial Intelligence (IAAI)",
    year = "2019"