6 papers
Adversarial Hubness Detector: Detecting Hubness Poisoning in Retrieval-Augmented Generation Systems
Idan Habler, Vineeth Sai Narajala, Stav Koren +2
Retrieval-Augmented Generation (RAG) systems are essential to contemporary AI applications, allowing large language models to obtain external knowledge via vector similarity search…
Cisco Integrated AI Security and Safety Framework Report
Amy Chang, Tiffany Saade, Sanket Mendapara +2
Artificial intelligence (AI) systems are being readily and rapidly adopted, increasingly permeating critical domains: from consumer platforms and enterprise software to networked s…
Death by a Thousand Prompts: Open Model Vulnerability Analysis
Amy Chang, Nicholas Conley, Harish Santhanalakshmi Ganesan +1
Open-weight models provide researchers and developers with accessible foundations for diverse downstream applications. We tested the safety and security postures of eight open-weig…
A Framework for Rapidly Developing and Deploying Protection Against Large Language Model Attacks
Adam Swanda, Amy Chang, Alexander Chen +3
The widespread adoption of Large Language Models (LLMs) has revolutionized AI deployment, enabling autonomous and semi-autonomous applications across industries through intuitive l…
Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report
Paul Kassianik, Baturay Saglam, Alexander Chen +15
As transformer-based large language models (LLMs) increasingly permeate society, they have revolutionized domains such as software engineering, creative writing, and digital arts.…
Extracting Memorized Training Data via Decomposition
Ellen Su, Anu Vellore, Amy Chang +4
The widespread use of Large Language Models (LLMs) in society creates new information security challenges for developers, organizations, and end-users alike. LLMs are trained on la…