24 citations · 24 across the 8 of their papers we have counts for
8 papers
Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents
Paul Kassianik, Blaine Nelson, Yaron Singer
Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, exploit development, penetration testin…
FAPO: Fully Automated Prompt Optimization of Multi-Step LLM Pipelines
Paul Kassianik, Baturay Saglam, Huaibo Zhao +4
Multi-step LLM pipelines fail through interactions among retrieval, reasoning, and formatting steps, so prompt-only optimization can miss bottlenecks in the chain. We present Fully…
Llama-3.1-FoundationAI-SecurityLLM-Reasoning-8B Technical Report
Zhuoran Yang, Ed Li, Jianliang He +18
We present Foundation-Sec-8B-Reasoning, the first open-source native reasoning model for cybersecurity. Built upon our previously released Foundation-Sec-8B base model (derived fro…
Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report
Sajana Weerawardhena, Paul Kassianik, Blaine Nelson +14
Large language models (LLMs) have shown remarkable success across many domains, yet their integration into cybersecurity applications remains limited due to a lack of general-purpo…
Large Language Models Encode Semantics and Alignment in Linearly Separable Representations
Baturay Saglam, Paul Kassianik, Blaine Nelson +3
Understanding the latent space geometry of large language models (LLMs) is key to interpreting their behavior and improving alignment. Yet it remains unclear to what extent LLMs li…
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…
Tree of Attacks: Jailbreaking Black-Box LLMs Automatically
Anay Mehrotra, Manolis Zampetakis, Paul Kassianik +4
While Large Language Models (LLMs) display versatile functionality, they continue to generate harmful, biased, and toxic content, as demonstrated by the prevalence of human-designe…