202 matches found
angr 9.2.212
angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...
angr 9.2.211
angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...
AndroScanner: Automated Backend Vulnerability Detection for Android Applications
Mobile applications rely on complex backends that introduce significant security risks, yet developers often lack the tools to assess these risks effectively. This paper presents AndroScanner, an automated pipeline for detecting vulnerabilities in Android application backends through combined...
RansomTrack: A Hybrid Behavioral Analysis Framework for Ransomware Detection
Ransomware poses a serious and fast-acting threat to critical systems, often encrypting files within seconds of execution. Research indicates that ransomware is the most reported cybercrime in terms of financial damage, highlighting the urgent need for early-stage detection before encryption is...
An Empirical Comparison of Security and Privacy Characteristics of Android Messaging Apps
Mobile messaging apps are a fundamental communication infrastructure, used by billions of people every day to share information, including sensitive data. Security and Privacy are thus critical concerns for such applications. Although the cryptographic protocols prevalent in messaging apps are...
Synopsys Coverity Connect 安全漏洞
Synopsys Coverity Connect is a web-based platform provided by Synopsys, Inc. It primarily consists of static code analysis tools and dynamic code analysis tools. Synopsys Coverity Connect has security vulnerabilities; one of these vulnerabilities stems from the identity verification logic in the...
Cross-Ecosystem Vulnerability Analysis for Python Applications
Python applications depend on native libraries that may be vendored within package distributions or installed on the host system. When vulnerabilities are discovered in these libraries, determining which Python packages are affected requires cross-ecosystem analysis spanning Python dependency...
Transparent COM instrumentation for malware analysis
COM automation is a core Windows technology that allows code to access external functionality through well-defined interfaces. It is similar to traditionally loading a DLL, but is class-based rather than function-based. Many advanced Windows capabilities are exposed through COM, such as Windows...
Ransomware and Artificial Intelligence: A Comprehensive Systematic Review of Reviews
This study provides a comprehensive synthesis of Artificial Intelligence AI, especially Machine Learning ML and Deep Learning DL, in ransomware defense. Using a "review of reviews" methodology based on PRISMA, this paper gathers insights on how AI is transforming ransomware detection, prevention,...
APFuzz: Towards Automatic Greybox Protocol Fuzzing
Greybox protocol fuzzing is a random testing approach for stateful protocol implementations, where the input is protocol messages generated from mutations of seeds, and the search in the input space is driven by the feedback on coverage of both code and state. State model and message model are th...
Mopri - an Analysis Framework for Unveiling Privacy Violations in Mobile Apps
Everyday services of society increasingly rely on mobile applications, resulting in a conflicting situation between the possibility of participation on the one side and user privacy and digital freedom on the other. In order to protect users' rights to informational self-determination, regulatory...
Realworld-for-Application_FUGIO_FirstFrameworkFuzzingDetectPOI
FUGIO Production Guide Introduction FUGIO is the firs...
AI-Powered Algorithms for the Prevention and Detection of Computer Malware Infections
The rise in frequency and complexity of malware attacks are viewed as a major threat to modern digital infrastructure, which means that traditional signature-based detection methods are becoming less effective. As cyber threats continue to evolve, there is a growing need for intelligent systems t...
injection-research
injection-research A study comparing injection vulnerabilities...
Towards Classifying Benign and Malicious Packages Using Machine Learning
Recently, the number of malicious open-source packages in package repositories has been increasing dramatically. While major security scanners focus on identifying known Common Vulnerabilities and Exposures CVEs in open-source packages, there are very few studies on detecting malicious packages...
Pack-A-Mal: A Malware Analysis Framework for Open-Source Packages
The increasingly sophisticated environment in which attackers operate makes software security an even greater challenge in open-source projects, where malicious packages are prevalent. Static analysis tools, such as Malcontent, are highly useful but are often incapable of dealing with obfuscated...
Hybrid Fuzzing with LLM-Guided Input Mutation and Semantic Feedback
Software fuzzing has become a cornerstone in automated vulnerability discovery, yet existing mutation strategies often lack semantic awareness, leading to redundant test cases and slow exploration of deep program states. In this work, I present a hybrid fuzzing framework that integrates static an...
BlueCodeAgent: A Blue Teaming Agent Enabled by Automated Red Teaming for CodeGen AI
As large language models LLMs are increasingly used for code generation, concerns over the security risks have grown substantially. Early research has primarily focused on red teaming, which aims to uncover and evaluate vulnerabilities and risks of CodeGen models. However, progress on the blue...
Security Analysis of Ponzi Schemes in Ethereum Smart Contracts
The rapid advancement of blockchain technology has precipitated the widespread adoption of Ethereum and smart contracts across a variety of sectors. However, this has also given rise to numerous fraudulent activities, with many speculators embedding Ponzi schemes within smart contracts, resulting...
