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With the advances in machine learning, there is a growing interest in AI-enabled tools for autocompleting source code. GitHub Copilot, also referred to as the "AI Pair Programmer", has been trained on billions of lines of open source GitHub…
Users are demanding increased data security. As a result, security is rapidly becoming a first-order design constraint in next generation computing systems. Researchers and practitioners are exploring various security technologies to meet…
Writing secure code is challenging and so it is expected that, following the release of code-generative AI tools, such as ChatGPT and GitHub Copilot, developers will use these tools to perform security tasks and use security APIs. However,…
Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do…
The disconnect between distributed software artifacts and their supposed source code enables attackers to leverage the build process for inserting malicious functionality. Past research in this field focuses on compiled language ecosystems,…
AI-based code assistants are promising tools that can facilitate and speed up code development. They exploit machine learning algorithms and natural language processing to interact with developers, suggesting code snippets (e.g., method…
Context: AI code generators are revolutionizing code writing and software development, but their training on large datasets, including potentially untrusted source code, raises security concerns. Furthermore, these generators can produce…
Recent advancements in large language models, including GPT-4 and its variants, and Generative AI-assisted coding tools like GitHub Copilot, ChatGPT, and Tabnine, have significantly transformed software development. This paper analyzes how…
The rapid growth of Artificial Intelligence (AI) models and applications has led to an increasingly complex security landscape. Developers of AI projects must contend not only with traditional software supply chain issues but also with…
Following the recent release of AI assistants, such as OpenAI's ChatGPT and GitHub Copilot, the software industry quickly utilized these tools for software development tasks, e.g., generating code or consulting AI for advice. While recent…
Generative Artificial Intelligence (AI) tools have been used to generate human-like content across multiple domains (e.g., sound, image, text, and programming). However, their reliability in terms of correctness and functionality in novel…
Sonatype's 2023 report found that 97% of developers and security leads integrate generative Artificial Intelligence (AI), particularly Large Language Models (LLMs), into their development process. Concerns about the security implications of…
As the role of information and communication technologies gradually increases in our lives, source code security becomes a significant issue to protect against malicious attempts Furthermore with the advent of data-driven techniques, there…
The rapid proliferation of Large Language Models (LLMs) has heightened concerns regarding their exposure to jailbreak attacks, which craft adversarial inputs designed to elicit unsafe content. Although proprietary models such as GPT-4 have…
AI coding assistants are now central to professional software development, yet their impact on how developers think about and practice security remains poorly understood. While prior work has documented vulnerability rates in AI-generated…
Artificial intelligence (AI) tools based on large language models have acheived human-level performance on some computer programming tasks. We report several experiments using GPT-4 to generate computer code. These experiments demonstrate…
The area of software development and secure coding can benefit significantly from advancements in virtual assistants. Research has shown that many coders neglect security in favor of meeting deadlines. This shortcoming leaves systems…
API misuse introduces security vulnerabilities, system failures, and increases maintenance costs, all of which remain critical challenges in software development. Existing detection approaches rely on static analysis or machine…
As large language models (LLMs) become more powerful and are deployed more autonomously, it will be increasingly important to prevent them from causing harmful outcomes. Researchers have investigated a variety of safety techniques for this…
Artificial Intelligence (AI) tools such as GitHub Copilot and ChatGPT are increasingly used in software engineering (SE) for tasks such as code, test, and documentation generation. However, engineers often face uncertainty about when to…