activity
20242026
collaborators

5 papers

cs.CR2026

SecMate: Multi-Agent Adaptive Cybersecurity Troubleshooting with Tri-Context Personalization

Yair Meidan, Omri Haller, Yulia Moshan +4

Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMate, a multi-agent VCA for cyber…

cs.CR2025

KubeGuard: LLM-Assisted Kubernetes Hardening via Configuration Files and Runtime Logs Analysis

Omri Sgan Cohen, Ehud Malul, Yair Meidan +3

The widespread adoption of Kubernetes (K8s) for orchestrating cloud-native applications has introduced significant security challenges, such as misconfigured resources and overly p…

cs.AI2025

ImpReSS: Implicit Recommender System for Support Conversations

Omri Haller, Yair Meidan, Dudu Mimran +2

Following recent advancements in large language models (LLMs), LLM-based chatbots have transformed customer support by automating interactions and providing consistent, scalable se…

cs.AI2025

ProfiLLM: An LLM-Based Framework for Implicit Profiling of Chatbot Users

Shahaf David, Yair Meidan, Ido Hersko +4

Despite significant advancements in conversational AI, large language model (LLM)-powered chatbots often struggle with personalizing their responses according to individual user ch…

cs.CR2024

GenKubeSec: LLM-Based Kubernetes Misconfiguration Detection, Localization, Reasoning, and Remediation

Ehud Malul, Yair Meidan, Dudu Mimran +2

A key challenge associated with Kubernetes configuration files (KCFs) is that they are often highly complex and error-prone, leading to security vulnerabilities and operational set…