Windows access control demystified

In the Secure Internet Programming laboratory at Princeton University, we have been investigating network security management by using logic programming. We developed a rule based framework — Multihost, Multistage, Vulnerability Analysis(MulVAL) — to perform end-to-end, automatic analysis of multi-host, multi-stage attacks on a large network where hosts run different operating systems. The tool finds attack paths where the adversary will have to use one or more than one weaknesses (buffer overflows) in multiple software to attack the network. The MulVAL framework has been demonstrated to be modular, flexible, scalable and efficient [20]. We applied these techniques to perform security analysis of a single host with commonly used software. We have constructed a logical model of Windows XP access control, in a declarative but executable (Datalog) format. We have built a scanner that reads access-control configuration information from the Windows registry, file system, and service control manager database, and feeds raw configuration data to the model. Therefore we can reason about such things as the existence of privilege-escalation attacks, and indeed we have found several user-to-administrator vulnerabilities caused by misconfigurations of the access-control lists of commercial software from several major vendors. We propose tools such as ours as a vehicle for software developers and system administrators to model and debug the complex interactions of access control on installations under Windows.

Mulval: A logic-based network security analyzer

To determine the security impact software vulnerabilities have on a particular network, one must consider interactions among multiple network elements. For a vulnerability analysis tool to be useful in practice, two features are crucial. First, the model used in the analysis must be able to automatically integrate formal vulnerability specifications from the bug-reporting community. Second, the analysis must be able to scale to networks with thousands of machines. We show how to achieve these two goals by presenting MulVAL, an end-to-end framework and reasoning system that conducts multihost, multistage vulnerability analysis on a network. MulVAL adopts Datalog as the modeling language for the elements in the analysis (bug specification, configuration description, reasoning rules, operating-system permission and privilege model, etc.). We easily leverage existing vulnerability-database and scanning tools by expressing their output in Datalog and feeding it to our MulVAL reasoning engine. Once the information is collected, the analysis can be performed in seconds for networks with thousands of machines. We implemented our framework on the Red Hat Linux platform. Our framework can reason about 84 % of the Red Hat bugs reported in OVAL, a formal vulnerability definition language. We tested our tool on a real network with hundreds of users. The tool detected a policy violation caused by software vulnerabilities and the system administrators took remediation measures.