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The Lightweight Directory Access Protocol (LDAP) is the standard technology to query information stored in directories. These directories can contain sensitive personal data such as usernames, email addresses, and passwords. LDAP is also used as a central, organization-wide storage of configuration data for other services. Hence, it is important to the security posture of many organizations, not least because it is also at the core of Microsoft’s Active Directory, and other identity management and authentication services.
We report on a large-scale security analysis of deployed LDAP servers on the Internet. We developed LanDscAPe, a scanning tool that analyzes security-relevant misconfigurations of LDAP servers and the security of their TLS configurations. Our Internet-wide analysis revealed more than 10k servers that appear susceptible to a range of threats, including insecure configurations, deprecated software with known vulnerabilities, and insecure TLS setups. 4.9k LDAP servers host personal data, and 1.8k even leak passwords. We document, classify, and discuss these and briefly describe our notification campaign to address these concerning issues.
Due to the increasing connectivity of modern vehicles, collected data is no longer only stored in the vehicle itself but also transmitted to car manufacturers and vehicle assistant apps. This development opens up new possibilities for digital forensics in criminal investigations involving modern vehicles. This paper deals with the digital forensic analysis of vehicle assistant apps of eight car manufacturers. We reconstruct the driver’s activities based on the data stored on the smartphones and in the manufacturer’s backend.
For this purpose, data of the Android and iOS apps of the car manufacturers Audi, BMW, Ford, Mercedes, Opel, Seat, Tesla, and Volkswagen were extracted from the smartphone and examined using digital forensic methods following forensics guidelines. Additionally, manufacturer data was retrieved using Subject Access Requests. Using the extensive data gathered, we reconstruct trips and refueling processes, determine parking positions and duration, and track the locking and unlocking of the vehicle.
Our findings show that the digital forensic investigation of smartphone applications is a useful addition to vehicle forensics and should therefore be taken into account in the strategic preparation of future digital forensic investigations.
Today’s medical IT is more and more connected and network or IT system outages may impact the quality of patient treatment. IT outages from cyberattacks are particularly worrisome if attackers focus on those medical IT devices that are critical for medical processes. However, medical processes are primarily documented for the hospital employees and not for analyzing the criticality of any given human or medical IT resource. This paper presents a generic model for realistic, patient-focused simulation of medical processes. The model allows the simulation of cyber incidents, focusing on device outages or overload situations like mass casualty incidents. Furthermore, we present a proof-of-concept tool that implements the described model, enabling end-users to simulate their processes. The tool offers the ability to run with low detailed data for overview purposes and highly detailed data for fine-grained simulation results. We perform different scenario simulations for a sample hospital, including the acute phase of a ransomware attack, negative performance impacts due to the implementation of cybersecurity measures, and emergency plans for mass casualty incidents. In each scenario, the respective simulation resulted in a quantitative statement of how these scenarios affect overall process performance and show possible key factors supporting decision-making. We use real-world data from a German trauma room to optimize and evaluate the process simulation.
