相关论文: Harvey: A Greybox Fuzzer for Smart Contracts

Fuzzing has become the de facto standard technique for finding software vulnerabilities. However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger software bugs. Most popular fuzzers use evolutionary guidance…

Smart contract is the building block of blockchain systems that enables automated peer-to-peer transactions and decentralized services. With the increasing popularity of smart contracts, blockchain systems, in particular Ethereum, have been…

Remote Procedure Call (RPC) is a communication protocol to support client-server interactions among services over a network. RPC is widely applied in industry for building large-scale distributed systems, such as Microservices. Modern RPC…

The increased adoption of smart contracts in many industries has made them an attractive target for cybercriminals, leading to millions of dollars in losses. Thus, deploying smart contracts with detected vulnerabilities (known to…

NIST is standardizing Post Quantum Cryptography (PQC) algorithms that are resilient to the computational capability of quantum computers. Past works show malicious subversion with cryptographic software (algorithm subversion attacks) that…

Smart contract technology facilitates self-executing agreements on the blockchain, eliminating dependency on an external trusted authority. However, smart contracts may expose vulnerabilities that can lead to financial losses and…

Buffer-overruns are a prevalent vulnerability in software libraries and applications. Fuzz testing is one of the effective techniques to detect vulnerabilities in general. Greybox fuzzers such as AFL automatically generate a sequence of…

Program analysis and automated testing have recently become an essential part of SSDLC. Directed greybox fuzzing is one of the most popular automated testing methods that focuses on error detection in predefined code regions. However, it…

Recently, many Deep Learning fuzzers have been proposed for testing of DL libraries. However, they either perform unguided input generation (e.g., not considering the relationship between API arguments when generating inputs) or only…

Fuzzing is a popular dynamic program analysis technique used to find vulnerabilities in complex software. Fuzzing involves presenting a target program with crafted malicious input designed to cause crashes, buffer overflows, memory errors,…

Modern compilers, such as LLVM, are complex pieces of software. Due to their complexity, manual testing is unlikely to suffice, yet formal verification is difficult to scale. End-to-end fuzzing can be used, but it has difficulties in…

With the increasing popularity of blockchain, different blockchain platforms coexist in the ecosystem (e.g., Ethereum, BNB, EOSIO, etc.), which prompts the high demand for cross-chain communication. Cross-chain bridge is a specific type of…

As hardware design complexity increases, hardware fuzzing emerges as a promising tool for automating the verification process. However, a significant gap still exists before it can be applied in industry. This paper aims to summarize the…

The purpose of continuous fuzzing platforms is to enable fuzzing for software projects via \emph{fuzz harnesses} -- but as the projects continue to evolve, are these harnesses updated in lockstep, or do they run out of date? If these…

Fuzzing has become a commonly used approach to identifying bugs in complex, real-world programs. However, interpreters are notoriously difficult to fuzz effectively, as they expect highly structured inputs, which are rarely produced by most…

Fuzzing has proven to be a highly effective approach to uncover software bugs over the past decade. After AFL popularized the groundbreaking concept of lightweight coverage feedback, the field of fuzzing has seen a vast amount of scientific…

Patch fuzzing is a technique aimed at identifying vulnerabilities that arise from newly patched code. While researchers have made efforts to apply patch fuzzing to testing JavaScript engines with considerable success, these efforts have…

Code reuse in software development frequently facilitates the spread of vulnerabilities, making the scope of affected software in CVE reports imprecise. Traditional methods primarily focus on identifying reused vulnerability code within…

Ethereum smart contracts are public, immutable and distributed and, as such, they are prone to vulnerabilities sourcing from programming mistakes of developers. This paper presents SAFEVM, a verification tool for Ethereum smart contracts…

Fuzzing is an automated application vulnerability detection method. For genetic algorithm-based fuzzing, it can mutate the seed files provided by users to obtain a number of inputs, which are then used to test the objective application in…