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We introduce a tool that supports continuous flow analysis in order to detect security problems as the user edits. The tool uses abstract interpretation over both byte codes and abstract syntax trees to trace the flow of both type…
Equipped with various tools and knowledge, GPTs, one kind of customized AI agents based on OpenAI's large language models, have illustrated great potential in many fields, such as writing, research, and programming. Today, the number of…
Tool selection is a key component of LLM agents. A popular approach follows a two-step process - \emph{retrieval} and \emph{selection} - to pick the most appropriate tool from a tool library for a given task. In this work, we introduce…
Vulnerabilities in open-source operating systems (OSs) pose substantial security risks to software systems, making their detection crucial. While fuzzing has been an effective vulnerability detection technique in various domains, OS fuzzing…
With the improvements in computing technologies, edge devices in the Internet-of-Things have become more complex. The enabler technology for these complex systems are powerful application core processors with operating system support, such…
Modern language models have enabled the development of agentic systems that achieve strong performance on reasoning-intensive tasks. Unfortunately, this has come with a security cost; these systems are vulnerable to prompt injection, a…
Network protocols are the foundation of modern communication, yet their implementations often contain semantic vulnerabilities stemming from inadequate understanding of specification semantics. Existing gray-box and black-box testing…
Software applications are subject to an increasing number of attacks, resulting in data breaches and financial damage. Many solutions have been considered to help mitigate these attacks, such as the integration of attack-awareness…
Nowadays, cyberattacks are growing exponentially, causing havoc to Internet users. In particular, authentication attacks constitute the major attack vector where intruders impersonate legitimate users to maliciously access systems or…
Spectre attacks exploit speculative execution to leak sensitive information. In the last few years, a number of static side-channel detectors have been proposed to detect cache leakage in the presence of speculative execution. However,…
In this era of internet, E-Business and e-commerce applications are using Databases as their integral part. These Databases irrespective of the technology used are vulnerable to SQL injection attacks. These Attacks are considered very…
Computer systems are facing biggest threat in the form of malicious data which causing denial of service, information theft, financial and credibility loss etc. No defense technique has been proved successful in handling these threats.…
Deep Learning (DL)-based methods have proven to be effective for software vulnerability detection, with a potential for substantial productivity enhancements for detecting vulnerabilities. Current methods mainly focus on detecting single…
Characterizing attacker behavior with respect to Cyber-Physical Systems is important to assuring the security posture and resilience of these systems. Classical cyber vulnerability assessment approaches rely on the knowledge and experience…
Web attacks, i.e. attacks exclusively using the HTTP protocol, are rapidly becoming one of the fundamental threats for information systems connected to the Internet. When the attacks suffered by web servers through the years are analyzed,…
Coverage-guided fuzz testing has received significant attention from the research community, with a strong focus on binary applications, greatly disregarding other targets, such as web applications. The importance of the World Wide Web in…
Penetration testing increases the security of systems through tasking testers to 'think like the adversary' and attempt to find the ways that an attacker would break into the system. For many systems, this can be conducted in a safe and…
Security flaws in software applications today has been attributed mostly to design flaws. With limited budget and time to release software into the market, many developers often consider security as an afterthought. Previous research shows…
A precise vulnerability discovery model (VDM) will provide a useful insight to assess software security, and could be a good prediction instrument for both software vendors and users to understand security trends and plan ahead patching…
Software security mainly studies vulnerability detection: is my code vulnerable today? This hinders risk estimation, so new approaches are emerging to forecast the occurrence of future vulnerabilities. While useful, these approaches are…