FieldFuzz: In Situ Blackbox Fuzzing of Proprietary Industrial Automation Runtimes via the Network

TL;DR

FieldFuzz is a novel network-based fuzzing framework that analyzes proprietary industrial PLC runtimes, uncovering vulnerabilities and improving security assessment of critical infrastructure devices.

Contribution

The paper introduces FieldFuzz, a new framework for in situ blackbox fuzzing of industrial PLC runtimes, including reverse-engineering, automated command discovery, and coverage-guided testing.

Findings

Uncovered multiple security vulnerabilities in Codesys runtime

Reported three new CVEs affecting industrial PLCs

Demonstrated cross-platform effectiveness on diverse ICS devices

Abstract

Networked Programmable Logic Controllers (PLCs) are proprietary industrial devices utilized in critical infrastructure that execute control logic applications in complex proprietary runtime environments that provide standardized access to the hardware resources in the PLC. These control applications are programmed in domain-specific IEC 61131-3 languages, compiled into a proprietary binary format, and process data provided via industrial protocols. Control applications present an attack surface threatened by manipulated traffic. For example, remote code injection in a control application would directly allow to take over the PLC, threatening physical process damage and the safety of human operators. However, assessing the security of control applications is challenging due to domain-specific challenges and the limited availability of suitable methods. Network-based fuzzing is often the only way to test such devices but is inefficient without guidance from execution tracing. This work presents the FieldFuzz framework that analyzes the security risks posed by the Codesys runtime (used by over 400 devices from 80 industrial PLC vendors). FieldFuzz leverages efficient network-based fuzzing based on three main contributions: i) reverse-engineering enabled remote control of control applications and runtime components, ii) automated command discovery and status code extraction via network traffic and iii) a monitoring setup to allow on-system tracing and coverage computation. We use FieldFuzz to run fuzzing campaigns, which uncover multiple vulnerabilities, leading to three reported CVE IDs. To study the cross-platform applicability of FieldFuzz, we reproduce the findings on a diverse set of Industrial Control System (ICS) devices, showing a significant improvement over the state-of-the-art.