Third-party libraries like Log4j accelerate software application development but introduce substantial risk. Vulnerabilities in these libraries have led to Software Supply Chain (SSC) attacks that compromised resources within the host system. These attacks benefit from current application permissions approaches: third-party libraries are implicitly trusted in the application runtime. An application runtime designed with ZeroTrust Architecture (ZTA) principles - secure access to resources, continuous monitoring, and least-privilege enforcement - could mitigate SSC attacks, as it would give zero implicit trust to these libraries. However, no individual security defense incorporates these principles at a low runtime cost. This paper proposes Zero-Trust Dependencies to mitigate SSC vulnerabilities: we apply the NIST ZTA to software applications. First, we assess the expected effectiveness and configuration cost of Zero-Trust Dependencies using a study of third-party software libraries and their vulnerabilities. Then, we present a system design,$\text{ZTD}_{\text{Sys}}$, that enables the application of Zero-Trust Dependencies to software applications and a prototype,$\text{ZTD}_{\text{JAVA}}$, for Java applications. Finally, with evaluations on recreated vulnerabilities and realistic applications, we show that$\text{ZTD}_{\text{JAVA}}$can defend against prevalent vulnerability classes, introduces negligible cost, and is easy to configure and use.

Embedded Network Stacks (ENS) enable low-resource devices to communicate with the outside world, facilitating the development of Internet of Things and Cyber-Physical Systems. Some defects in ENS are thus high-severity cybersecurity vulnerabilities: they are remotely triggerable and can impact the physical world. While prior research has shed light on the characteristics of defects in many classes of software systems, no study has described the properties of ENS defects nor identified a systematic technique to expose them. The most common automated approach to detecting ENS defects is feedback-driven randomized dynamic analysis (“fuzzing”), a costly and unpredictable technique. This paper provides the first systematic characterization of cybersecurity vulnerabilities in ENS. We analyzed 61 vulnerabilities across 6 open-source ENS. Most of these ENS defects are concentrated in the transport and network layers of the network stack, require reaching different states in the network protocol, and can be triggered by only 1–2 modifications to a single packet. We therefore propose a novel systematic testing framework that focuses on the transport and network layers, uses seeds that cover a network protocol's states, and systematically modifies packet fields. We evaluate this framework on 4 ENS and replicated 12 of the 14 reported IP/TCP/UDP vulnerabilities. On recent versions of these ENSs, it discovered 7 novel defects (6 assigned CVES) during a bounded systematic test that covered all protocol states and made up to 3 modifications per packet. We found defects in 3 of the 4 ENS we tested that had not been found by prior fuzzing research. Our results suggest that fuzzing should be deferred until after systematic testing is employed.

Failure studies are important in revealing the root causes, behaviors, and life cycle of defects in software systems. These studies either focus on understanding the characteristics of defects in specific classes of systems, or the characteristics of a specific type of defect in the systems it manifests in. Failure studies have influenced various software engineering research directions, especially in the area of software evolution, defect detection, and program repair.