Docker has been one of the most widely used DevOps tools in the last decade, enabling fast development of personalized services. Indeed, the common practice is to reuse already available containers and customize them based on the developer's needs. DockerHub is the leading platform for uploading and downloading Docker containers. Unfortunately, reusing code and infrastructure exposes developers to security and privacy threats, as the original developer might have had malicious intent to collect sensitive data or create backdoors in a victim's system. The existing literature has raised concerns about this security and privacy threats, and performed a mass vulnerability scans of Docker images. However, currently existing studies are mostly based on static analysis, which has been proved to be insufficient for a complete security assessment.

In this thesis we present a novel framework for the en-masse identification of vulnerabilities in Docker Containers. Additionally, as part of the framework, we document and implement a component which sorts and downloads images based on their popularity, which improves on the current fuzzy-search based state-of-the-art. Using this framework we found vulnerabilities in 2.44% of the containers we scanned. The framework also succeeded in finding novel vulnerabilities, resulting in two new reserved CVE numbers in the social network software Friendica.

The upcoming IEEE 802.1CB standard aims to solve performance and reliability issues in Time-Sensitive Networking (TSN). Mission-critical systems often use these standards for communication in automotive, industrial, and avionic networks. However, researchers did not sufficiently investigate the security risks and possible mitigation solutions to this introduced standard. This limited knowledge is a problem as Cyber-Physical Systems (CPS) are mission-critical and time-sensitive, and any unexpected failure of these systems could endanger lives.

To attain a complete overview of the security risks of IEEE 802.1CB, we use an improved STRIDE model for Cyber-Physical Systems. We then design and create a hardware test-bed for Time-Sensitive Networking to prove the feasibility of the identified security risks. Finally, we implement attacks for the identified security risks in IEEE 802.1CB and analyze their impact by running experiments on the hardware test-bed. The results show that some of the identified security risks significantly impact the network’s reliability as we successfully execute a Replay attack and a Denial of Service attack. However, the hardware switches provide only limited functionality of the IEEE 802.1CB specification. Therefore, we could not verify the attacks against all identified security risks.

These results show that this networking standard is not ready to be used in Cyber-Physical Systems as the impact of the identified security risks is too significant. On this basis, we recommend additional research and improvements to the IEEE 802.1CB standard and mitigation solutions.