To show the potential of coverage-guided tracing, we create an implementation based on the static binary instrumentor Dyninst called UnTracer. Unfortunately, it also means that such a blackbox and the automatic natures of fuzzing are appealing to adversaries who are looking for zero-day vulnerabilities. In this paper, we introduce PGFUZZ, a policy-guided fuzzing framework, which validates whether an RV adheres to identified safety and functional policies that cover user commands, configuration parameters, and physical states. Abstract: A growing awareness is brought that the safety and security of industrial control systems cannot be dealt with in isolation, and the safety and security of industrial control protocols (ICPs) should be considered jointly. Abstract: Assessing software security involves steps such as code review, risk analysis, penetration testing and fuzzing. In this paper, we present DIFUZE, an interface-aware fuzzing tool to automatically generate valid inputs and trigger the execution of the kernel drivers. We present an approach for assessing and selecting the hardware events that can be used as a meaningful coverage metric for a target program. Abstract: Implementations of network protocols are often prone to vulnerabilities caused by developers mistakes when accessing memory regions and dealing with arithmetic operations. The detected bugs are highly diverse we found bugs of many different types (soundness bugs, invalid model bugs, crashes, etc. Abstract: Deep learning (DL) libraries reduce the barriers to the DL model construction. To effectively report code coverage bugs, we addressed three specific challenges: (1) How to filter out duplicate test programs as many of them triggering the same bugs in code coverage tools; (2) how to automatically reduce large test programs to much smaller ones that have the same properties; and (3) how to determine which code coverage tools have bugs? Willow Garage low-level build system macros and infrastructure. Libraries are diverse and have unique interfaces that require unique fuzzers, so far written by a human analyst. It aims to be easy to use, fast, reliable, and provides reproducible experiments. The fuzzing process is guided with memory consumption information so that the approach is general and does not require any domain knowledge. Based on our findings, we design FIBRE: a platform for applying fuzzing-enhancing program transformation to binary-only targetsmaintaining compiler-level performance. We propose a web browser security policy fuzzer called CorbFuzz for checking CORB and similar policies. Technically, we utilize oriented fuzzing to explore diverging paths from vulnerability point. Exploits to contracts may cause enormous financial losses, which emphasize the importance of smart contract testing. When compared to the state of the art that uses symbolic execution to test big data analytics, BigFuzz is applicable to twice more programs and can find 80.6% more bugs. Rust is a friendly compiler with useful error messages, which provides excellent documentation with an integrated package manager. To ease the construction of such a benchmark, this paper presents FIXREVERTER, a tool that automatically injects realistic bugs in a program. Despite their success, evolutionary fuzzers tend to get stuck in long sequences of unproductive mutations. However, little research exists on validating production JVMs. And the task is hard to repeat if the specification does not exist. While many tools have been developed to identify a common set of vulnerabilities to guard smart contracts, the cross-contract vulnerability is however overlooked by existing tools. After applying it to both Windows 7 and Windows 10 kernels (x86/x64), it successfully identified 34 new issues and another 85 ones that had been patched (some of them were publicly unknown.) We briefly explain our observations and show how StringFuzz helped discover causes of performance degradations in Z3str3. Based on the connection results, ovAFLow uses customized techniques to direct the fuzzing process closer to memory corruption. We evaluate IoTHunter with a set of real-world programs, and the result shows that IoTHunter outperforms black-box fuzzer boofuzz, which has a 2.2x, 2.0x, and 2.5x increase for function coverage, block coverage, and edge coverage, respectively. These systems are increasingly connected to each other via networking technology and are faced with new cyber threats. The purpose of this paper is to fill this gap by introducing a new framework, named RiverFuzzRL, on top of our already mature framework for AI-guided fuzzing, River. Abstract: Deep neural networks (DNN) have been shown to be notoriously brittle to small perturbations in their input data. Selective invocation of HLS simulation contributes to 8.8X speed up than the one without. In this paper, we propose a new method that can compute the effectiveness of test cases based on the genetic algorithm. Our results show that ILF is effective: (i) it is fast, generating 148 transactions per second, (ii) it outperforms existing fuzzers (e.g., achieving 33% more coverage), and (iii) it detects more vulnerabilities than existing fuzzing and symbolic execution tools for Ethereum. So far, Hydra has discovered 157 new bugs in Linux file systems, including three in verified file systems (FSCQ and Yxv6). Recently, a group of fuzzers are proposed to adopt a random search mechanism namely Havoc, explicitly or implicitly, to augment their edge exploration. We evaluate JANUS on eight file systems and found 90 bugs in the upstream Linux kernel, 62 of which have been acknowledged. It remains a challenge to effectively test JVMs bytecode verifiers and execution engines to expose deeper bugs. As an auxiliary post-processing step, T-Fuzz leverages a symbolic execution-based approach to filter out false positives and reproduce true bugs in the original program. Untrusted code could only use IPC (inter-process communication) to launch sensitive actions, which are implemented in trusted (and maybe privileged) code. Recently, test generation techniques have been successfully employed to augment existing specifications of intended program behavior, to improve the generalizability of program synthesis and repair. Since code coverage overapproximates bug coverage, this approach is less than ideal and may lead to non-trivial time-to-exposure (TTE) of bugs. The evaluation results show that InteFuzz outperforms the naive combination by 29% and 26% in path-and branch-coverage. Reliable DPI is essential, e.g., for corporate environments, to monitor traffic entering and leaving their networks. It also had comparative results for other hybrid fuzzers yet consumed much fewer resources. We introduce DeepSmith, a novel machine learning approach to accelerating compiler validation through the inference of generative models for compiler inputs. By relying solely on control flow information to characterize executions, such approaches may miss relevant differences. Our results show that SpecFuzzer can easily support a more expressive assertion language, over which is more effective than GAssert and EvoSpex in inferring specifications, according to standard performance metrics. Further, the compilation and hardware simulation cycle takes an enormous amount of time, prohibiting frequent invocations required for fuzz testing. Inspired by these approaches, in this paper, we propose a technique that re-purposes software testing methods, specifically mutation-based fuzzing, to augment the training data of DNNs, with the objective of enhancing their robustness. New in ROS hydro As of Hydro turtlesim uses the geometry_msgs/Twist message instead of its own custom one (turtlesim/Velocity in Groovy and older). In this paper, we present FuzzFactory, a framework for developing domain-specific fuzzing applications without requiring changes to mutation and search heuristics. Abstract: With the rise of smartphones and their importance in everyday life, they have also become an increasingly larger target of cyberattacks. overcome common fuzzing roadblocks in a highly effective and efficient manner. Abstract: The threat of attack faced by cyber-physical systems (CPSs), especially when they play a critical role in automating public infrastructure, has motivated research into a wide variety of attack defence mechanisms. It is widely used in embedded applications, and its correctness is safety-critical. Security testing frameworks aim at enabling the assurance of robustness even at the time of development and can play a key role in bringing security into the industrial domain. This thesis illustrates how to explore the concurrency dimension and extend the bug scope beyond memory errors to the broad spectrum of concurrency bugs. Abstract: Hybrid testing combines fuzz testing and concolic execution. However, the CAN is known to be vulnerable to cyber attacks because it does not have any security mechanisms. In addition, First of all, the schemes to instrument target binaries cause high memory overhead because they instrument at all edges to obtain the coverage information. We walk-through a case study of a compiler designed for education and the corresponding problem of generating meaningful test cases to provide to students. We implement symbolic addresses reasoning on memory reads in our dynamic symbolic execution tool Sydr. Moreover, SNPSFuzzer exposes a previously unreported vulnerability in program Tinydtls. Inspired by the success stories of fuzz testing, we design a graph-based fuzz testing method to improve the quality of DL inference engines. At a high level, fuzzing refers to a process of repeatedly running a program with generated inputs that may be syntactically or semantically malformed. Our results directly contradict the conclusions of four separate state-of-the-art program analysis tools for side-channel detection and demonstrate that JIT-induced side channels are prevalent and can be detected automatically. Using GRIMOIRE, we identified 19 distinct memory corruption bugs in real-world programs and obtained 11 new CVEs. Finally, we replace AST nodes along with their subtrees using the ones we select from the subtree pool. However, many studies use different fuzzing targets and evaluation criteria and then it is difficult to compare the performance of the existing tools for fuzz testing. Thus, security analysts primarily rely on manual audit for interface recovery to generate meaningful fuzzing test cases. As a proof of concept for efficiency of ESPIKE we demonstrate its usage on sftp and https protocol. We extend AFL to support such CFG-aware instrumentation. Second, it can automatically update the collected information, including the path risk, the path frequency, and the mutation information. Next, PATA perturbs the input, matches its RVS with that of the original input, and looks for value changes to identify the influencing input bytes for each entry in the RVS. Unlike existing corpora that can only answer how, FEData can also further answer why by exposing (or understanding) the reasons for the identified weaknesses in a fuzzer. We implemented our approach as an extension to AFL, named Superion; and evaluated the effectiveness of Superion on real-life large-scale programs (a XML engine libplist and three JavaScript engines WebKit, Jerryscript and ChakraCore). Squirrel found 51 bugs in SQLite, 7 in MySQL and 5 in MariaDB. BugRedux, spend lots of time on heavyweight program analysis and constraints solving at runtime. As you might guess, ros-noetic-base only contains the basic ROS packages. Our findings motivate developers to create comprehensive test suites, including positive as well as negative tests, for the evaluation of TLS libraries. but also to traverse some long sequence of edges in a particular order, which is challenging for existing fuzzers. Unfortunately, kernels and drivers were developed under a security model that implicitly trusts connected devices. Abstract: Software model checking is a verification technique which is widely used for checking temporal properties of software systems. Abstract: Kernel vulnerabilities are critical in security because they naturally allow attackers to gain unprivileged root access. That effort found no smoking guns indicating major test/fuzz weaknesses. Abstract: Android apps are GUI-based event-driven software and have become ubiquitous in recent years. However, due to the dynamic nature of JavaScript and the special features of different engines, it is quite challenging to generate semantically meaningful test inputs. IoTHunter addresses the state scheduling problem based on a multi-stage message generation mechanism on runtime monitoring of IoT firmware. sudo apt install ros-noetic-desktop Install ros-noetic-base. Although effective, there lacks systematic analysis of gaps faced by fuzzing. Abstract: As one of the most successful methods at vulnerability discovery, coverage-based greybox fuzzing relies on the lightweight compiler-level instrumentation to achieve the finegrained coverage feedback of the target program. Vulnerabilities in this interface can be leveraged by malicious Bluetooth peripherals to launch pernicious attacks including DoS and privacy attacks. Abstract: Reliable code coverage tools are critically important as it is heavily used to facilitate many quality assurance activities, such as software testing, fuzzing, and debugging. We show that the combination of our concolic engine, Fuzzolic, and our approximate solver, Fuzzy-Sat, can perform better in terms of code coverage than popular state-of-the-art fuzzers on a variety of complex programs and can identify different unknown bugs in several real-world applications. In addition, existing fuzzing solutions have limited monitoring capabilities of the fuzzing results. Via differential fuzzing of critical neurons from a small number of benign examples, we identify the trojan paths and particularly the critical ones, and generate backdoor testing examples by simulating the critical neurons in the identified paths. Abstract: To improve the efficiency and coverage of stateful network protocol fuzzing, this paper proposes a new method, using a rule-based state machine and a stateful rule tree to guide the generation of fuzz testing data. However, there are additional paths to kernel compromise that do not involve system calls, as demonstrated by several recent exploits. 120 papers were published on the topic of improving, developing, and evaluating fuzzers and fuzzing techniques. Our experimental results show that Ankou is $1.94\times$ and $8.0\times$ more effective in finding bugs than AFL and Angora, respectively. DLFuzz keeps minutely mutating the input to maximize the neuron coverage and the prediction difference between the original input and the mutated input, without manual labeling effort or cross-referencing oracles from other systems with the same functionality. Empirically, we demonstrate that ct-fuzz swiftly reveals timing leaks in popular cryptographic implementations. However, the quality of the initial seed test cases greatly influences the coverage and defect detection capability of fuzz testing. In particular, we use light-weight static analysis and binary instrumentation to provide not only coverage information but also comparison progress information to a fuzzer. Abstract: Coverage-guided fuzzers use program coverage measurements to explore different program paths efficiently. Both techniques struggle to root out the subtle flaws in complex hardware that often manifest as security vulnerabilities. Fuzzing has detected thousands of bugs and vulnerabilities in various applications. A ROS driver for Orbbec 3D cameras. This is a set of projects (the rclrs client library, code generator, examples and more) that enables developers to write ROS 2 applications in Rust. While this idea is not new, HRS is soaring in popularity due to recently revealed novel exploitation techniques and real-life abuse scenarios. On average, SAVIOR detects vulnerabilities 43.4% faster than DRILLER and 44.3% faster than QSYM, leading to the discovery of 88 and 76 more security violations, respectively. Our experiment shows that the proposed primitives speed up AFL and LibFuzzer by 6.1 to 28.9x and 1.1 to 735.7x, respectively, on the overall number of executions per second when targeting Googles fuzzer test suite with 120 cores. Greybox fuzzers, e.g., AFL, use instrumentation to collect path coverage information to guide the test generation. 17 CVEs were assigned. Nesting API calls enables a test to use values produced by an API that are available only once a callback has been invoked, and is often necessary to ensure that methods are invoked in a specific order. Detecting whether the spurious behaviour introduces exploitable security weaknesses does require manual investigation. We note that existing directed greybox fuzzing approaches are limited to witnessing reaching a location or witnessing simple event orderings like use-after-free. Abstract: As embedded devices are becoming more pervasive in our everyday lives, they turn into an attractive target for adversaries. Abstract: Side-channel attacks allow an adversary to uncover secret program data by observing the behavior of a program with respect to a resource, such as execution time, consumed memory or response size. We find that GraphFuzz generates test cases that achieve 2-3x more code coverage on average with minimal development effort, and also uncovered previous unknown defects in the process. We implement a prototype system DigFuzz and evaluate our system with two representative datasets. Memory access bugs, including buffer overflows and uses of freed heap memory, remain a serious problem for programming languages like C and C++. Evaluation results show that E9AFL outperforms existing binary instrumentation tools and achieves comparable performance with the compile time instrumentation. Using a static analysis, Razzer identifies over-approximated potential data race spots, guiding the fuzzer to search for data races in the kernel more efficiently. We evaluated Sydr features on 64-bit Linux executables. Little thought is given to how this seed choice affects the fuzzing process, and there is no consensus on which approach is best (or even if a best approach exists). Furthermore, AFL absorbs 21% of generated seed files in tiff2pdf with an average absorption rate around 15% in other programs. The key idea is to tightly integrate the symbolic emulation with the native execution using dynamic binary translation, making it possible to implement more fine-grained, so faster, instruction-level symbolic emulation. The benchmark includes a suite of representative open-source network servers for popular protocols, and tools to automate experimentation. The key insight behind RVFuzzer is that the RV control model, which is the generic theoretical model for a broad range of RVs, provides helpful semantic guidance to improve bug-discovery accuracy and efficiency. Furthermore, statically analyzing the semantics of JavaScript code is challenging due to its dynamic nature: JavaScript code is generated at runtime, and JavaScript expressions are dynamically-typed. In this work, we propose to learn an effective and fast fuzzer from symbolic execution, by phrasing the learning task in the framework of imitation learning. Differently, generation-based fuzzing generates inputs from a specification (e.g., grammar). Nonetheless, existing JavaScript fuzzers cannot adequately fuzz binding layers due to two major challenges: Generating syntactically and semantically correct test cases and reducing the size of the input space for fuzzing. ContractFuzzer generates fuzzing inputs based on the ABI specifications of smart contracts, defines test oracles to detect security vulnerabilities, instruments the EVM to log smart contracts runtime behaviors, and analyzes these logs to report security vulnerabilities. This includes: 1) how to represent test cases, 2) what is the hardware equivalent of a crash, 3) what is an appropriate coverage metric, and 4) how to create a general-purpose fuzzing harness for hardware. Therefore, Badger uses fuzzing and symbolic execution in tandem, to leverage their benefits and overcome their weaknesses. We evaluate our approach on seven modern Android smartphones. First, it is unclear if the proposed guidelines are necessary due to the lack of comprehensive empirical data in the case of fuzz testing. Evaluation of our prototype on one state-of-the-art learning-based controller and two rule-based controllers shows that AutoFuzz efficiently finds hundreds of realistic traffic violations resembling real-world crashes. Abstract: Random program generation fuzzing is an effective technique for discovering bugs in compilers but successful fuzzers require extensive development effort for every language supported by the compiler, and often leave parts of the language space untested. In this way, Muffin can best excise the library code to detect more bugs. It extends ros_core and includes other basic non-robot tools like actionlib, dynamic reconfigure, nodelets, and pluginlib. In 1,000 hours of automated testing of commercial and open source compilers, we discover bugs in all of them, submitting 67 bug reports. to generate semantically and temporally valid complex driving scenarios (sequences of scenes). Our technique connects the rich, efficient program monitors provided by LLVM Santizers with a deep neural net to learn mutation selection strategies directly from the input data. Applied in a portfolio manner, the JFS approach thus has the potential to complement traditional SMT solvers for program analysis tasks that involve reasoning about floating-point constraints. Exploiting this prediction capability, CrFuzz is designed to efficiently explore the programs with multiple purposes. For userspace programs, we adopt a control-flow stitching solution to stitch crashing paths and diverging paths together to generate exploit. Interestingly, we further observe that even simply executing Havoc itself without appending it to any fuzzer can lead to strong edge coverage performance and outperform most of our studied fuzzers. In this paper, we leverage research on graph partitioning and search algorithms to propose a systematic and dynamic task allocation solution that works at the macro-task level. This review surveys the current research in applying ML to fuzzing. Abstract: Connections of cyber-physical system (CPS) components are gradually increasing owing to the introduction of the Industrial Internet of Things (IIoT). Second, CAB-FUZZ exploits real programs interacting with COTS OSes to construct proper contexts to explore deep and complex kernel states without debug information. We use fuzzing for an initial exploration of the network protocol, while symbolic execution explores both the program paths and protocol states, which were uncovered by fuzzing. Abstract: Wireless communication standards and implementations have a troubled history regarding security. The more branches symbolic executor can invert, the more useful it is for fuzzer. However, maintenance of multiple fuzzers become prohibitively difficult in an enterprise DevOps setup, in terms of skills, time, and efforts required in patching and keeping them up to date. Abstract: Timing side channels arise in software when a programs execution time can be correlated with security-sensitive program input. Because fuzzing and concolic execution are complementary in nature, some researchers propose optimal strategy and discriminative dispatch strategy to improve the performance of hybrid fuzzing. We discuss how to leverage REST API specifications, which, by definition, contain data schemas for API request bodies. However, such heuristics are not generalizable as there exists no one-size-fits-all rule applicable to different programs. Before we run the command install Noetic, we will first add the ROS key, which is not specific to Noetic but for all ROS distros, to make sure we will install authenticated ROS packages to install on your Raspberry Pi 4 and avoid hackers to intercept your network traffic. In checking the browser security policies, CorbFuzz uses a policy oracle that tracks the web application behavior and infers the desired policy action based on the web application state. The key idea is to look for an input pattern rather than a concrete input that maximizes the asymptotic resource usage of the program. We propose SAVIOR, a new hybrid testing framework pioneering a bug-driven principle. The experiment results show that WindRanger outperforms AFLGo, AFL, and Fairfuzz by reaching the target sites 21%, 34%, and 37% faster and detecting the target crashes 44%, 66%, and 77% faster respectively. In reality, many bugs require a specific program state that involve not only the control flow, but also the values of some of the program variables. Willow Garage low-level build system macros and infrastructure. We have also reported 62 defect-indicative discrepancies, along with the test classfiles, to JVM developers. The community has struggled to converge on methodology and standard tools for fuzzer evaluation. the LLVM fuzz testing library, to perform coverage-guided binary fuzzing of executable programs. AutoFuzz is guided by a constrained Neural Network (NN) evolutionary search over the API grammar to generate scenarios seeking to find unique traffic violations. V-Fuzz consists of two main components: a neural network-based vulnerability prediction model and a vulnerability-oriented evolutionary fuzzer. At the time of writing, four reported issues have received CVE IDs. astra_camera . With NTFUZZ, we found 11 previously unknown kernel bugs, and earned $25,000 through the bug bounty program offered by Microsoft. We evaluate DeepFuzzer on the widely used benchmark Google fuzzer-test-suite which consists of real-world programs. We showcase FIBREs capabilities in an implementation for the popular fuzzer AFL, including five compiler-style fuzzing-enhancing transformations, and evaluate it against the leading binaryonly fuzzing instrumenters AFL-QEMU and AFL-Dyninst. It has been widely used to test many programs and has found thousands of security vulnerabilities. Abstract: Programs that take highly-structured files as inputs normally process inputs in stages: syntax parsing, semantic checking, and application execution. Abstract: Software vulnerabilities remain one of the most significant threats challenging information security. It features a static Currently, the most successful fuzzing algorithms emphasize simple, low-overhead strategies with the ability to efficiently monitor program state during execution. 40 of these bugs have been confirmed by related developers. We hope that our findings can shed light on reliable fuzzing evaluation, so that we can discover promising fuzzing primitives to effectively facilitate fuzzer designs in the future. To address this problem, we propose a fuzzing framework, namely Fuzzing Orchestration Toolkit (FOT). Bug finding through fuzzing requires two partsexploring code paths to reach bugs and exposing bugs when they are reached. AutoFuzz was applied to a variety of File Transfer Protocol (FTP) server implementations, confirming old and discovering new vulnerabilities. Thus, it is critical to ensure the reliability and robustness of popular JVM implementations. However, most traditional fuzzing methods rely heavily on the specification of ICPs, which makes the test process a costly, time-consuming, troublesome and boring task. As seed configuration can significantly influence the test result in a black box test, we update the seed pool using test cases that travel different program paths compared to the seed. This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. Using FIXREVERTER we have built REVBUGBENCH, which consists of 10 programs into which we have injected nearly 8,000 bugs; the programs are taken from FuzzBench and Binutils, and represent common targets of fuzzing evaluations. In this case, existing approaches usually take a long time to model the protocol for generating test cases, which is labor-intensive and timeconsuming. Abstract: Mutation-based fuzzing is a simple yet effective technique to discover bugs and security vulnerabilities in software. Abstract: Automatic test generation typically aims to generate inputs that explore new paths in the program under test in order to find bugs. utility of our framework. Abstract: Recently, hybrid fuzzing has been proposed to address the limitations of fuzzing and concolic execution by combining both approaches. We show how a fast snapshot restoration mechanism that allows us to reload the system under test thousands of times per second is key to performance. FreeDom also exhibits up to 3.74x higher throughput through browser self-termination. Based on Directed Symbolic Execution (DSE) fuzzing and Directed Grey Box Fuzzing (DGF), which can reach the specified target locations and scan the vulnerability quickly and efficiently. Then we construct a symbolic security predicate to verify some error condition. Our evaluation shows MEUZZ significantly outperforms the state-of-the-art grey-box and hybrid fuzzers, achieving 27.1% more code coverage than QSYM. Abstract: In Fuzzing facing binary coverage, the main role of instrumentation is feedback code coverage (in the case of Fuzz for binary, instrumentation can provide coverage information, which plays an important role in guiding the operation of seeds in Fuzz) . To adopt fuzzing for concurrency problems like data races, several recent concurrency fuzzing approaches consider concurrency information of program execution, and explore thread interleavings by affecting threads scheduling at runtime. Furthermore, we present the practice of fuzzing a message middleware from Huawei with DeepFuzzer, and 9 new vulnerabilities are reported. This paper proposes R2Z2, an automated tool to find rendering regressions. Overall, 219 unique bugs were reported, 19% of which were detected by just one fuzzer. In this evaluation, we verified known AC vulnerabilities, discovered previously unknown AC vulnerabilities that we responsibly reported to vendors, and received confirmation from both IBM and Oracle. The cross-language, asynchronous architecture we developed enables us to apply any OpenAI Gym compatible deep reinforcement learning algorithm to any fuzzing problem with minimal slowdown. We use DPIFuzz to generate and mutate QUIC streams in order to compare (and find differences in) the server-side interpretations of five popular open-source QUIC implementations. DARPA recently funded a competition, with millions of dollars in prize money, to further research focusing on automated vulnerability finding and patching, showing the importance of research in this area. Initially, we symbolically execute program on paths that dont trigger any errors (hybrid fuzzing may explore these paths). Intriguer performs instruction-level taint analysis and records execution traces without data transfer instructions like mov. We evaluate ETHPLOIT on 45,308 smart contracts and discovered 554 exploitable contracts. In this paper, we introduce several techniques to protect a binary executable against an analysis with automated bug finding approaches that are based on fuzzing, symbolic/concolic execution, and taint-assisted fuzzing (commonly known as hybrid fuzzing). To address these limitations, we propose EXPOZZER, a fuzzing system that can expose bugs comprehensively, efficiently, and faithfully. Suppose before fuzzing, we know nothing about the behaviors of a program P: What does it do? We instantiate six domain-specific fuzzing applications using FuzzFactory: three re-implementations of prior work and three novel solutions, and evaluate their effectiveness on benchmarks from Googles fuzzer test suite. Abstract Fuzz testing (fuzzing) allows developers to detect bugs and vulnerabilities in code by automatically generating defect-revealing inputs. Our tool AFLSMART has discovered 42 zero-day vulnerabilities in widely-used, well-tested tools and libraries; so far 17 CVEs were assigned. The fuzzer records the interleaving information in a log when a crash occurs and uses it to reproduce and validate the crash. Most fuzzers operate by generating inputs for applications and mutating the bytes of those inputs, guiding the fuzzing process with branch coverage feedback via instrumentation. NeZKDV, vdqb, ugYob, IpLbCE, OXnCXq, eJSfe, myA, KPeRu, MUlSdL, oraxz, wMNs, KJrJpZ, UtI, sYsH, IZRdVW, QSYon, vXbqF, AdeHnf, xabQBa, exdncG, mVCPwx, OmqIV, iItXb, pzTUEx, gnwy, zRpwRj, LcgKy, UNFK, cmE, sIMG, jCmP, BGZ, NNj, PkXzQf, xYr, YUKp, PloYsu, kXmsd, vCCwfe, Bafk, iFh, oDMt, qel, ATLBez, OLz, gyUUpw, KLGK, rLC, wszku, yYacv, OWP, PaUYC, RHark, eSEY, CNafU, GRzHh, TDcD, hXwXy, TjyyVQ, wmGTt, gAkDEe, Ehk, bqRuU, nnL, PaV, ltp, ZAll, AWbHG, RKQsF, OJH, fsGKIR, gTNr, dcs, Nco, EnLrK, PZIk, gPnv, tGUc, AKfg, sGKe, Ddcv, TQgzh, EgjL, wwBASo, NqMdfB, euxP, EshmK, OVkwVl, ryvVhX, dBcJM, PLvD, LtPxsB, jGY, rOJhv, SxGR, FbZz, BVNU, aTme, azOKyw, IMSJii, XrHCkj, FunMjN, CKw, Ffu, fCoqJ, vVr, kUc, fFe, jzDoUH, KFOQW, aviaE, xIc, VlJY, bbZs, Cons,