• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.587-604
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• 2021

Because the library cannot be run independently and used by many applications, it is important to detect vulnerabilities in the library. Fuzzing, which is a dynamic analysis, is used to discover vulnerabilities for the library. Although this fuzzing technique shows excellent results in terms of code coverage and unique crash counts, it is difficult to apply its effects to library fuzzing. In particular, a fuzzing executable and a seed corpus are needed that execute the library code by calling a specific function sequence and passing the input of the fuzzer to reproduce the various states of the library. Generating the fuzzing environment such as fuzzing executable and a seed corpus is challenging because it requires both understanding about the library and fuzzing knowledge. We propose a novel method to improve the ease of library fuzzing and enhance code coverage and crash detection performance by using a test framework. The systems's performance in this paper was applied to nine open-source libraries and was verified through comparison with previous studies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.231-242
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• 2013

Recently, automated software testing methods such as fuzzing have been researched to find software vulnerabilities. The purpose of fuzzing is to disclose software vulnerabilities by providing a software with malformed data. In order to increase the probability of vulnerability discovery by fuzzing, we must solve the test suite reduction problem because the probability depends on the test case quality. In this paper, we propose a new method to solve the test suite reduction problem which is suitable for the long test case such as file. First, we suggested the length of test case as a measure in addition to old measures such as coverage and redundancy. Next we designed a test suite reduction algorithm using the new measure. In the experimental results, the proposed algorithm showed better performance in the size and length reduction ratio of the test suite than previous studies. Finally, results from an empirical study suggested the viability of our proposed measure and algorithm for file fuzzing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1989-2009
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• 2013

How to discover router vulnerabilities effectively and automatically is a critical problem to ensure network and information security. Previous research on router security is mostly about the technology of exploiting known flaws of routers. Fuzzing is a famous automated vulnerability finding technology; however, traditional Fuzzing tools are designed for testing network applications or other software. These tools are not or partly not suitable for testing routers. This paper designs a framework of discovering router protocol vulnerabilities, and proposes a mathematical model Two-stage Fuzzing Test Cases Generator(TFTCG) that improves previous methods to generate test cases. We have developed a tool called RPFuzzer based on TFTCG. RPFuzzer monitors routers by sending normal packets, keeping watch on CPU utilization and checking system logs, which can detect DoS, router reboot and so on. RPFuzzer' debugger based on modified Dynamips, which can record register values when an exception occurs. Finally, we experiment on the SNMP protocol, find 8 vulnerabilities, of which there are five unreleased vulnerabilities. The experiment has proved the effectiveness of RPFuzzer.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.573-582
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• 2020

Fuzzing is a method of testing software by randomly generating test cases. Since its introduction, a variety of fuzzing techniques have been studied. Among them, mutation-based fuzzing is an efficient method that finds real-world bugs even though it uses a simple approach such as probabilistic bit-flipping and character substitution. However, the interpreter fuzzing has difficulty in applying general mutation techniques because the interpreter requires grammar and semantic correctness input values. In this paper, we present a novel mutation-based fuzzing on JavaScript interpreters with a dynamic data flow analysis. To this end, we implement JMFuzzer that can generate various types of mutated test cases that operate normally without runtime errors in JavaScript interpreter considering syntax and semantics. As a result, we found numerous unknown vulnerabilities in the latest JavaScript interpreters. We reported all of them to the vendors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.807-819
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• 2019

Greybox fuzzing is known as an effective method to discover unknown security flaws reside in software and has been actively researched today. However, most of greybox fuzzing tools require an executable file. Because of this, a library, which cannot be executed by itself requires an additional executable file for greybox fuzzing. Generating such an executable file is challengeable because it requires both understanding of the library and fuzzing. In this research, we suggest the approach to generate an executable file automatically for a library and implement this approach as a tool based on the LLVM framework. This tool shows that executable files and seed files can be generated automatically by static/dynamic analysis of a unit test in the target project. A generated executable file is compatible with various greybox fuzzers like AFL because it has a common interface for greybox fuzzers. We show the performance of this tool as code coverage and discovered unknown security bugs using generated executable files and seed files from open source projects through this tool.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.443-454
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• 2020

The JavaScript engine is a module that receives JavaScript code as input and processes it, among many functions that are loaded into web browsers and display web pages. Many fuzzing test studies have been conducted as vulnerabilities in JavaScript engines could threaten the system security of end-users running JavaScript through browsers. Some of them have increased fuzzing efficiency by guiding test coverage in JavaScript engines, but no coverage guided fuzzing of optimized, dynamically generated machine code was attempted. Optimized JavaScript codes are difficult to perform sufficient iterative testing through fuzzing due to the function of runtime guards to free the code in the event of exceptional control flow. To solve these problems, this paper proposes a method of performing fuzzing tests on optimized machine code by avoiding deoptimization. In addition, we propose a method to measure the coverage of runtime-guards by the dynamic binary instrumentation and to guide increment of runtime-guard coverage. In our experiment, our method has outperformed the existing method at two measures: runtime coverage and iteration by time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3885-3906
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• 2020

Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3511-3532
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• 2019

Coverage-guided fuzzing is an efficient solution that has been widely used in software testing. By guiding fuzzers through the coverage information, seeds that generate new paths will be retained to continually increase the coverage. However, we observed that most samples follow the same few high-frequency paths. The seeds that exercise a high-frequency path are saved for the subsequent mutation process until the user terminates the test process, which directly affects the efficiency with which the low-frequency paths are tested. In this paper, we propose a fuzzing solution, ER-Fuzz, that truncates the recording of a high-frequency path to influence coverage. It utilizes a deep learning-based classifier to locate the high and low-frequency path transfer points; then, it instruments at the transfer position to promote the probability low-frequency transfer paths while eliminating subsequent variations of the high-frequency path seeds. We implemented a prototype of ER-Fuzz based on the popular fuzzer AFL and evaluated it on several applications. The experimental results show that ER-Fuzz improves the coverage of the original AFL method to different degrees. In terms of the number of crash discoveries, in the best case, ER-Fuzz found 115% more unique crashes than did AFL. In total, seven new bugs were found and new CVEs were assigned.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.31-37
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• 2015

As the forms of cyberattacks become diverse, there has been reported another case of exploiting vulnerabilities revealed while processing either a document or multimedia file that was distributed for attacking purpose, which would replace the traditional method of distributing malwares directly. The attack is based upon the observation that the softwares such as document editer or multimedia player may reveal inherent vulnerabilities on some specific inputs. The fuzzing methods that provide invalid random inputs for test purpose could discover such exploits. This paper suggests a new fuzzing method on document applications that could work in mobile environments, in order to resolve the drawback that the existing methods run only in PC environments. Our methods could effectively discover the exploits of mobile applications, and thus could be utilized as a means of dealing with APT attacks in mobile environments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1225-1234
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• 2019

The security of the firmware is more important because embedded devices have become popular. Network devices such as routers can be attacked by attackers through web application vulnerabilities in embedded firmware. Therefore, they must be found and removed quickly. The Firmadyne framework proposes a dynamic analysis method to find vulnerabilities after emulating firmware. However, it only performs vulnerability checks according to the analysis methods defined in the tool, thus limiting the scope of vulnerabilities that can be found. In this paper, fuzzing is performed in emulation-based environment through fuzzing, one of the software security test techniques. We also propose a Fabfuzz tool for efficient emulation based fuzzing. Experiments have shown that in addition to the vulnerabilities identified in existing tools, other types of vulnerabilities have been found.