How to Compare the Security of Code Written by Humans to LLM-Generated Code

Large language models LLMs are rapidly transforming how software is created and maintained. Comparing LLM-generated code against human-written standards is essential to determine whether these new tools uphold or erode the security baselines established by professional developers. Yet, we lack a...

angr 9.2.219

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 9.2.216

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...

FuzzingBrain V2: A Multi-Agent LLM System for Automated Vulnerability Discovery and Reproduction

Software vulnerabilities pose critical security threats, with nearly 50,000 CVEs reported in 2025. While Large Language Models LLMs show promise for automated vulnerability detection, three key challenges remain. First, LLM-generated vulnerability reports suffer from high false positive rates and...

angr 9.2.215

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...

ethical-hacking-lab-reports

Ethical Hacking & Information Security Lab Reports !Security...

angr 9.2.214

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...

Exploit for Embedded Malicious Code in Tukaani Xz

Security Review: CVE-2024-3094 XZ Utils Backdoor Автор:...

angr 9.2.213

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...

EDySec: A Deep Learning-Based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem

The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multiphase malware execution, remote access activation, and dynamic payload generation. Traditional Machine Learning ML detectors struggle to detect these...

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...