Showcase
S²E is used by many scientific projects across the world. This page lists some of them. We’ll be happy to list yours as well, just drop us a line!
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Hiding in Plain Sight: An Empirical Study of Web Application Abuse in Malware at Georgia Institute of Technology CyFI Lab and United States Military Academy (Mingxuan Yao, et al).
Web applications provide a wide array of utilities that are abused by malware as a replacement for traditional attacker-controlled servers. Thwarting these Web App-Engaged (WAE) malware requires rapid collaboration between incident responders and web app providers. We developed Marsea, an automated malware analysis pipeline that uses S2E to study WAE malware and enables rapid remediation. Given 10K malware samples, Marsea revealed 893 WAE malware in 97 families abusing 29 web apps. This research uncovered a 226% increase in the number of WAE malware since 2020. To date, we have used Marsea to collaborate with the web app providers to take down 80% of the malicious web app content.
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Automated Reasoning and Detection of Specious Configuration in Large Systems with Symbolic Execution at Johns Hopkins University (Yigong Hu, Gongqi Huang, and Peng Huang).
This paper introduces Violet — a tool that uses symbolic execution in order to detect software misconfigurations that lead to extremely poor performance. Violet makes symbolic the configuration parameters of the program under test, which allows the tool to automatically explore the program along paths that depend on these parameters. In addition to that, Violet runs a benchmark on each path, making it possible to determine paths that perform poorly, while showing users which combinations of parameters actually cause the problem. Violet helped identify problematic configurations for MySQL, Postgres, Apache, and Squid, which prompted the maintainers of these systems to clarify the documentation.
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BinRec: Dynamic Binary Lifting and Recompilation at University of California (Irvine), Vrije Universiteit Amsterdam, KU Leuven (Anil Altinay, Joseph Nash, Taddeus Kroes, et al.).
BinRec [is a] a new approach to heuristic-free binary recompilation which lifts dynamic traces of a binary to a compiler-level intermediate representation (IR) and lowers the IR back to a “recovered” binary. This enables BinRec to apply rich program transformations, such as compiler-based optimization passes, on top of the recovered representation. [BinRec] can accurately disassemble and lift binaries without heuristics, and can successfully recover obfuscated code and all SPEC INT 2006 benchmarks including C++ applications.
[The] dynamic lifting engine is built on top of S2E, a framework that facilitates symbolic execution of a single process running in the QEMU virtual machine. Code is translated to LLVM IR in order to be symbolically executed by the KLEE symbolic executor. S2E automatically provides multi-architecture support and sandboxing of input binaries, since it is based on QEMU.
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MALPITY: Automatic Identification and Exploitation of Tarpit Vulnerabilities in Malware at Saarland University (Sebastian Walla and Christian Rossow).
This paper proposes techniques to automatically find network inputs that would slow down malware to the point of making it unusable (tarpit vulnerabilities). MALPITY uses S2E in single-path mode, taking advantage of its powerful instrumentation capabilities in order to monitor malware network activity. This allowed MALPITY to find 12 previously unknown vulnerabilities, e.g., in Pushdo, SalityP2P, or bashlite.
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Unleashing Use-Before-Initialization Vulnerabilities in the Linux Kernel Using Targeted Stack Spraying at Georgia Institute of Technology, DFKI, MPI-SWS, CISPA, and Saarland University (Kangjie Lu et al.).
Kernel stack spraying consists in running syscalls in such a way that their invocation leaves user-controlled data on the stack, which can then be used to trigger vulnerabilities from the use of uninitialized variables. The implementation of the stack sprayer uses S2E to find as many code paths as possible that have user-controlled data on the kernel stack. That data is then matched against subsequent syscalls that happen to have uninitialized data at the controlled locations.
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POTUS: Probing Off-The-Shelf USB Drivers with Symbolic Fault Injection (slides) at Royal Holloway, University of London (James Patrick-Evans, Lorenzo Cavallaro, and Johannes Kinder). Awarded Best Paper.
USB client device drivers are a haven for software bugs, due to the sheer variety of devices and the tendency of maintenance to slip as devices age. At the same time, the high privilege level of drivers makes them a prime target for exploitation. We present the design and implementation of POTUS, a system for automatically finding vulnerabilities in USB device drivers for Linux, which is based on fault injection, concurrency fuzzing, and symbolic execution.
Built on the S2E framework, POTUS exercises the driver under test in a complete virtual machine. It includes a generic USB device that can impersonate arbitrary devices and implements a symbolic fault model. With our prototype implementation, we found and confirmed two previously undiscovered zero-days in the mainline Linux kernel [CVE-2016-5400, CVE-2017-15102]. Furthermore, we show that one of these vulnerabilities can lead to a data-only exploit affecting even hardened systems protected with the latest software and hardware defenses.
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CAB-Fuzz: Practical Concolic Testing Techniques for COTS Operating Systems at Georgia Tech, Purdue University (Su Yong Kim et al.)
CAB-FUZZ exploits real programs interacting with COTS OSes to construct proper contexts to explore deep and complex kernel states without debug information. We applied CAB-FUZZ to Windows 7 and Windows Server 2008 and found 21 undisclosed unique crashes, including two local privilege escalation vulnerabilities (CVE-2015-6098 and CVE-2016-0040) and one information disclosure vulnerability in a cryptography driver (CVE-2016-7219). CAB-FUZZ found vulnerabilities that are non-trivial to discover; five vulnerabilities have existed for 14 years, and we could trigger them even in the initial version of Windows XP (August 2001).
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Symbolic Execution for BIOS Security at Intel Corporation (Oleksandr Bazhaniuk, John Loucaides, Lee Rosenbaum, Mark R. Tuttle, and Vincent Zimmer).
We are building a tool that uses symbolic execution to search for BIOS security vulnerabilities including dangerous memory references (call outs) by SMM interrupt handlers in UEFI-compliant implementations of BIOS. Given a snapshot of SMRAM, the base address of SMRAM, and the address of the variable interrupt handler in SMRAM, the tool uses S2E to run the KLEE symbolic execution engine to search for concrete examples of a call to the interrupt handler that causes the handler to read memory outside of SMRAM. We discuss our approach, our current status, our plans for the tool, and the obstacles we face.
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Testing Linux Device Drivers at University of Wisconsin-Madison (Matthew J. Renzelmann, Asim Kadav, and Michael M. Swift). SymDrive is a system for testing Linux and FreeBSD drivers without their devices. The system uses symbolic execution to remove the need for hardware, and provides three new features beyond prior symbolic-testing tools. First, SymDrive greatly reduces the effort of testing a new driver with a static-analysis and source-to-source transformation tool. Second, SymDrive allows checkers to be written as ordinary C and execute in the kernel, where they have full access to kernel and driver state. Finally, SymDrive provides an execution-tracing tool to identify how a patch changes I/O to the device and to compare device driver implementations. In applying SymDrive to 21 Linux drivers and 5 FreeBSD drivers, we found 39 bugs.
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Chef at EPFL (Stefan Bucur and George Candea). Chef is a platform for obtaining symbolic execution engines for interpreted languages. It works by reusing the interpreter itself as an executable language specification, thus reducing the effort of obtaining an engine to a matter of days. The resulting engines can be used like any other engine for finding bugs, generating high-coverage test suites, assisting in debugging, and more.
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Finding Trojan Message Vulnerabilities in Distributed Systems at EPFL (Radu Banabic, George Candea, and Rachid Guerraoui). Achilles helps developers discover Trojan Messages in distributed systems, i.e., messages that are accepted as valid by receiver nodes, but cannot be generated by any correct sender node. Achilles uses S2E to analyze both the client and server nodes of a target distributed system. It extracts predicates that define the messages that can be generated and accepted, respectively. In a sense, one can think of these predicates as representations of the grammar of messages in the protocol, as implemented in the client and in the server. The predicates are stored in the form of symbolic expressions and constraints. After extracting the server and client predicates, Achilles computes the predicate that defines Trojan messages as the difference between the two. In our evaluation, we show how Achilles can discovered Trojan messages in FSP, a file transfer system, and PBFT, a Byzantine-Fault-Tolerant State Machine Replication library. The Trojan messages discovered by Achilles lead to subtle bugs in the respective distributed systems.
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File Systems Equivalence Checking at Max Planck Institute for Software Systems (Carreira João, Rodrigo Rodrigues, Rupak Majumdar). The goal of this project is to find functional bugs in systems code by checking the equivalence of multiple implementations that obey the same specification. Checking the equivalence of the different systems is performed by comparing the outputs and the logical state of different systems after executing the operations in their specification. Symbolic execution will allows us to reason about all possible executions and results of these operations. We specifically intend to apply this approach to find functional bugs in file systems.
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Corruption Impact Analysis at University of Wisconsin (Subramanian Sriram, Sundararaman Swaminathan, Andrea C. Arpaci-Dusseau, Remzi Arpaci-Dusseau). Corruption Impact Analysis is a novel technique to understand the impact of memory corruptions in file systems. We employ selective symbolic execution to exhaustively explore the impact of memory corruptions on other in-memory data structures, disk and the user. Our technique emphasizes the importance of the location of corruption in addition to the corrupted data structure. We present a detailed case study of applying our technique to Ext2. We identify the data structures and code regions most sensitive to corruption and present corruption spectrums for each scenario. Thus, our technique offers developers the opportunity to improve file system reliability without sacrificing performance.
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KleeNet project at Chair of Communication and Distributed Systems (ComSys), RWTH Aachen University (Raimondas Sasnauskas, Klaus Wehrle). Within KleeNet project, we are symbolically executing unmodified sensornet applications to generate distributed execution paths at high-coverage. However, the symbolic execution of Internet communication protocols is difficult since the software is not self-contained and hence heavily interacts with its surrounding environment (OS, libraries). Using S2E, we are able to switch between symbolic and native execution in a flexible way with low manual effort. Therefore, it allows us to drive the analysis towards interesting software parts.
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Improving Automation in Developer Testing: Cooperative Developer Testing at North Carolina State University (Xie Tao). Developer testing, a common step in software development, involves generating sufficient test inputs and checking the behavior of the program under test during the execution of the test inputs. This project develops novel techniques and tools for improving automation in developer testing focusing on improving automation in test generation and test oracles. This project also investigates the methodology of cooperative developer testing: developers and tools cooperate in effectively accomplishing challenging tasks in software testing.
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Exploiting Parallelism for Effective Low-Level Software Analysis at Institute of Software Chinese Academy of Sciences (Jian Liu, Bin Li, Sunlv Wang). In this project, one goal is to analyze typical application software and system code such as embedded OS or hypervisor. For example, we use S2E to analyze hypercalls in the Xen hypervisor. This project also plans to improve performance of S2E. We introduce concurrency algorithms and build a framework of scheduling rules to maximize the multi-path processing efficiently using multi-threading and multi-core processors. We are also devising heuristics to reduce the search time and to enhance efficiency.