Enabling Sophisticated Analysis of x86 Binaries with RevGen

Current state-of-the-art static analysis tools for binary software operate on ad-hoc intermediate representations (IR) of the machine code. Therefore, even though IRs facilitate program analysis by abstracting away the source language, it is hard to reuse existing implementations of analysis tools in new endeavors. Recently, a new compiler framework — LLVM— has emerged, together with many analysis tools that use its IR. However, these tools rely on a compiler to generate the IR from source code. We propose RevGen, a tool that automatically converts existing binary programs to the standard LLVM IR, making an increasingly large number of static and dynamic analysis frameworks, as well as run-time instrumentation tools, applicable to legacy software. We show the potential of RevGen by converting several programs and device drivers to LLVM and checking the resulting code with off-the-shelf analysis tools

Reverse Engineering of Binary Device Drivers with RevNIC

This paper presents a technique that helps automate the reverse engineering of device drivers. It takes a closed-source binary driver, automatically reverse engineers the driver’s logic, and synthesizes new device driver code that implements the exact same hardware protocol as the original driver. This code can be targeted at the same or a different OS. No vendor documentation or source code is required. Drivers are often proprietary and available for only one or two operating systems, thus restricting the range of device support on all other OSes. Restricted device support leads to low market viability of new OSes and hampers OS researchers in their efforts to make their ideas available to the “real world.” Reverse engineering can help automate the porting of drivers, as well as produce replacement drivers with fewer bugs and fewer security vulnerabilities. Our technique is embodied in RevNIC, a tool for reverse engineering network drivers. We use RevNIC to reverse engineer four proprietary Windows drivers and port them to four different OSes, both for PCs and embedded systems. The synthesized network drivers deliver performance nearly identical to that of the original drivers

Lightweight Snapshots and System-level Backtracking

We propose a new system-level abstraction, the lightweight immutable execution snapshot, which combines the immutable characteristics of checkpoints with the direct integration into the virtual memory subsystem of standard mutable address spaces. The abstraction can give arbitrary x86 programs and libraries system-level support for backtracking (akin to logic programming) and the ability to manipulate an entire address space as an immutable data structure (akin to functional programming). Our proposed implementation leverages modern x86 hardware-virtualization support

S2E: A Platform for In-Vivo Multi-Path Analysis of Software Systems

This paper presents S2E, a platform for analyzing the properties and behavior of software systems. We demonstrate S2E's use in developing practical tools for comprehensive performance profiling, reverse engineering of proprietary software, and bug finding for both kernel-mode and user-mode binaries. Building these tools on top of S2E took less than 770 LOC and 40 person-hours each. S2E's novelty consists of its ability to scale to large real systems, such as a full Windows stack. S2E is based on two new ideas: selective symbolic execution, a way to automatically minimize the amount of code that has to be executed symbolically given a target analysis, and relaxed execution consistency models, a way to make principled performance/accuracy trade-offs in complex analyses. These techniques give S2E three key abilities: to simultaneously analyze entire families of execution paths, instead of just one execution at a time; to perform the analyses in-vivo within a real software stack—user programs, libraries, kernel, drivers, etc.—instead of using abstract models of these layers; and to operate directly on binaries, thus being able to analyze even proprietary software. Conceptually, S2E is an automated path explorer with modular path analyzers: the explorer drives the target system down all execution paths of interest, while analyzers check properties of each such path (e.g., to look for bugs) or simply collect information (e.g., count page faults). Desired paths can be specified in multiple ways, and S2E users can either combine existing analyzers to build a custom analysis tool, or write new analyzers using the S2E API

Testing Closed-Source Binary Device Drivers with DDT

DDT is a system for testing closed-source binary device drivers against undesired behaviors, like race conditions, memory errors, resource leaks, etc. One can metaphorically think of it as a pesticide against device driver bugs. DDT combines virtualization with a specialized form of symbolic execution to thoroughly exercise tested drivers; a set of modular dynamic checkers identify bug conditions and produce detailed, executable traces for every path that leads to a failure. These traces can be used to easily reproduce and understand the bugs, thus both proving their existence and helping debug them. We applied DDT to several closed-source Microsoft-certified Windows device drivers and discovered 14 serious new bugs. DDT is easy to use, as it requires no access to source code and no assistance from users. We therefore envision DDT being useful not only to developers and testers, but also to consumers who want to avoid running buggy drivers in their OS kernels

Selective Symbolic Execution

Symbolic execution is a powerful technique for analyzing program behavior, finding bugs, and generating tests, but suffers from severely limited scalability: the largest programs that can be symbolically executed today are on the order of thousands of lines of code. To ensure feasibility of symbolic execution, even small programs must curtail their interactions with libraries, the operating system, and hardware devices. This paper introduces selective symbolic execution, a technique for creating the illusion of full-system symbolic execution, while symbolically running only the code that is of interest to the developer. We describe a prototype that can symbolically execute arbitrary portions of a full system, including applications, libraries, operating system, and device drivers. It seamlessly transitions back and forth between symbolic and concrete execution, while transparently converting system state from symbolic to concrete and back. Our technique makes symbolic execution practical for large software that runs in real environments, without requiring explicit modeling of these environments

Harvey: A Greybox Fuzzer for Smart Contracts

We present Harvey, an industrial greybox fuzzer for smart contracts, which are programs managing accounts on a blockchain. Greybox fuzzing is a lightweight test-generation approach that effectively detects bugs and security vulnerabilities. However, greybox fuzzers randomly mutate program inputs to exercise new paths; this makes it challenging to cover code that is guarded by narrow checks, which are satisfied by no more than a few input values. Moreover, most real-world smart contracts transition through many different states during their lifetime, e.g., for every bid in an auction. To explore these states and thereby detect deep vulnerabilities, a greybox fuzzer would need to generate sequences of contract transactions, e.g., by creating bids from multiple users, while at the same time keeping the search space and test suite tractable. In this experience paper, we explain how Harvey alleviates both challenges with two key fuzzing techniques and distill the main lessons learned. First, Harvey extends standard greybox fuzzing with a method for predicting new inputs that are more likely to cover new paths or reveal vulnerabilities in smart contracts. Second, it fuzzes transaction sequences in a targeted and demand-driven way. We have evaluated our approach on 27 real-world contracts. Our experiments show that the underlying techniques significantly increase Harvey's effectiveness in achieving high coverage and detecting vulnerabilities, in most cases orders-of-magnitude faster; they also reveal new insights about contract code.Comment: arXiv admin note: substantial text overlap with arXiv:1807.0787

Reverse-Engineering Drivers for Safety and Portability

Device drivers today lack two important properties: guaranteed safety and cross-platform portability. We present an approach to incrementally achieving these properties in drivers, without requiring any changes in the drivers or operating system kernels. We describe RevEng, a tool for automatically reverse-engineering a binary driver and synthesizing a new, safe and portable driver that mimics the original one. The operating system kernel runs the trusted synthetic driver instead of the original, thus avoiding giving untrusted driver code kernel privileges. Initial results are promising: we reverseengineered the basic functionality of network drivers in Linux and Windows based solely on their binaries, and we synthesized safe drivers for Linux. We hope RevEng will eventually persuade hardware vendors to provide verifiable formal specifications instead of binary drivers; such specifications can be used to automatically synthesize safe drivers for every desired platform