The web is now being used as a general platform for hosting distributed applications like wikis, bulletin board messaging systems and collaborative editing environments. Data from multiple applications originating at multiple sources all intermix in a single web browser, making sensitive data stored in the browser subject to a broad milieu of attacks (cross-site scripting, cross-site request forgery and others). The fundamental problem is that existing web infrastructure provides no means for enforcing end-to-end security on data. To solve this we design an architecture using mandatory access control (MAC) enforcement. We overcome the limitations of traditional MAC systems, implemented solely at the operating system layer, by unifying MAC enforcement across virtual machine, operating system, networking and application layers. We implement our architecture using Xen virtual machine management, SELinux at the operating system layer, labeled IPsec for networking and our own label-enforcing web browser, called FlowwolF. We tested our implementation and find that it performs well, supporting data intermixing while still providing end-to-end security guarantees.

Programs trusted with secure information should not release that information in ways contrary to system policy. However, when a program contains an illegal flow of information, current information-flow reporting techniques are inadequate for determining the cause of the error. Reasoning about information-flow errors can be difficult, as the flows involved can be quite subtle. We present a general model for information-flow blame that can explain the source of such security errors in code. This model is implemented by changing the information-flow verification procedure to: (1) generate supplementary information to reveal otherwise hidden program dependencies; (2) modify the constraint solver to construct a blame dependency graph; and (3) develop an explanation procedure that returns a complete and minimal error report. Our experiments show that information-flow errors can generally be explained and resolved by viewing only a small fraction of the total code.

This paper presents an approach to statically retrofit legacy servers with mechanisms for authorization policy enforcement. The approach is based upon the observation that security-sensitive operations performed by a server are characterized by idiomatic resource manipulations, called fingerprints. Candidate fingerprints are automatically mined by clustering resource manipulations using concept analysis. These fingerprints are then used to identify security-sensitive operations performed by the server. Case studies with three real-world servers show that the approach can be used to identify security-sensitive operations with a few hours of manual effort and modest domain knowledge.