Securing LLM-Powered Applications - Overcoming Security and Privacy Challenges
Explore the security and privacy challenges of LLM-powered applications in this 51-minute conference talk from Devoxx. Delve into common issues like prompt injection, key leakage, and misuse of private customer data for model training. Gain insights on l…
Words as Weapons - The Dark Arts of Prompt Engineering
Explore the dark arts of Prompt Engineering in this eye-opening 43-minute conference talk from Devoxx. Delve into the evolving landscape of AI integration in organizations, focusing on the risks associated with Large Language Models (LLMs) and their appl…
Pushing LLMs over the Edge: Exploring the Limits of the Possible
Explore LLM limits through outrageous applications using LangChain4j and Quarkus. Witness complex tasks, potential havoc, and self-evaluating models in this thrilling journey of AI possibilities.
Demystifying LLMs and Their Security Implications - A Business-Friendly Overview
Explore GenAI and LLMs, understanding their operations, security implications, and deployment scenarios. Learn to manage risks, prevent data leakage, and implement practical strategies for safe AI integration.
The Journey of Building a Leading Open Source LLM Security Toolkit
Explore the development of LLM Guard, an open-source toolkit for securing LLM applications in production. Learn about challenges, solutions, and real-world implementations for confident LLM deployment.
Defense Against Prompt Injection Attacks in LLM-Integrated Applications
Explore effective strategies for securing LLM applications against prompt injection attacks through structured queries and specialized instruction tuning techniques.
Hacking Neural Networks - Introduction and Current Techniques
Einführung in Angriffsmethoden auf neuronale Netze: Funktionsweise, Schwachstellen und Verteidigungsstrategien. Praxisnahe Beispiele verdeutlichen Risiken und Limitierungen moderner KI-Systeme.
Securing AI Systems in Real-World Deployments
Explore critical security challenges and defensive strategies for deploying AI systems in production, including insights from running the world's largest AI Red Team and handling emerging threats.
Considerations on AI Security
Explore key considerations for AI security in this TROOPERS24 conference talk, covering potential risks, vulnerabilities, and strategies for safeguarding AI systems.
Guarding LLM and NLP APIs: A Trailblazing Odyssey for Enhanced Security - Podcast #190
Explore LLM and NLP API security challenges, threat modeling, and defense strategies. Gain insights on OWASP Top 10 for LLM Applications and the AI Village's 'Hack the Future' event at Defcon31.
OWASP Top 10 Security Risks for Large Language Models
Explore OWASP Top 10 LLM security risks, learn mitigation strategies, and understand the impact of Generative AI on cybersecurity in various industries.
Building an LLM Vulnerability Scanner to Secure AI Applications
Develop an LLM vulnerability scanner to audit and secure AI applications. Learn about LLM security risks and build a CLI tool for detecting vulnerabilities in AI systems.
Red Teaming of LLM Applications - From Prototype to Production
Explore techniques to detect vulnerabilities in LLM applications, focusing on automated safety assessments and benchmarking methods for secure GenAI system deployment.
Mastering Large Language Model Evaluations - Techniques for Ensuring Generative AI Reliability
Explore techniques for evaluating Large Language Models, addressing challenges like hallucinations and toxicity, and learn essential metrics and tools for assessing AI reliability in generative applications.
AI CTF Solutions - DEFCon31 Hackathon and Kaggle Competition
Comprehensive walkthrough of AI hacking techniques used in DEFCon31 CTF competition, covering various attacks on machine learning models, including adversarial examples, prompt injection, and model inversion.
Securing AI and LLM-based Applications: Best Practices
Explore security challenges in AI and LLM applications, learn attack scenarios, and discover best practices for mitigating risks and maintaining application integrity.
From Text to Flaws: Vulnerabilities in Applications with Generative AI and LLMs
Explore vulnerabilities in generative AI applications, understand LLM functionality, and learn practical countermeasures to protect your AI-powered software from potential attacks.
AI Prompt Injection Attacks - Understanding Risks and Real-World Examples
Explore the fascinating world of AI prompt injection attacks, understanding key vulnerabilities, real-world examples, and defensive strategies for Large Language Model implementations.
Securing Generative AI: Threats Old and New
Explore essential security concepts for generative AI and LLMs, understanding both traditional cybersecurity approaches and emerging threats in this evolving technological landscape.
The Simple Yet Lethal Anatomy of an AI Attack
Dive into the anatomy of AI security threats through live demonstrations, exploring attack strategies from reconnaissance to LLM poisoning, and learn to defend against emerging vulnerabilities in AI systems.
Attacking and Defending Large Language Models in Production Environments
Explore essential security strategies and potential vulnerabilities of Large Language Models in production, covering attack vectors, defense mechanisms, and implementation best practices based on leading AI research.