Overview
The Cyber AI & Automation Summit explores the implications and use of predictive artificial intelligence, machine learning, and automation in cybersecurity. This event provides insights into how AI-powered tools are reshaping threat landscapes and defenses. Attendees will learn about practical use-cases for AI-enabled security and strategies to combat AI-powered cybercrime.
Speakers
6
Schedule
Model Red-Teaming: Dynamic Security Analysis for LLMs
The rise of Large Language Models has many organizations rushing to integrate AI-powered tools into existing products, but they introduce significant new risk. OWASP has recently introduced the LLM Top 10 to highlight these novel threat vectors, including prompt injection and data exfiltration. However, existing AppSec tools are not designed to detect and remediate these vulnerabilities. In particular, static analysis (SAST), one of the most common tools, cannot be used since there is no code: m
Demystifying the AI SOC with intelligent workflows
Security teams are overwhelmed by alert fatigue, skill shortages, and burnout. AI is well-positioned to address these challenges, yet security leaders are split on whether a truly autonomous SOC is achievable. The truth is: the future of the SOC isn’t fully autonomous - it’s intelligent. In this session, we’ll explore: The evolution of workflows, from python and scripts, to agentic workflows, and everything in between Why flexible, intelligent workflows that combine deterministic logic, AI agen
Malicious vs. Defensive: How to Stay Ahead of AI-Powered Cybercrime
The widespread adoption of generative AI has led to increased productivity for employees, but also for adversaries. Threat actors are using AI to craft email attacks that are polished, typo-free, hyper-personalized, and are doing so at scale. From convincing business email compromise (BEC) attacks to credential phishing and even deepfake videos that mimic executives, these machine-speed threats are breaching defenses faster than ever. So how do you stay ahead? Join this session to explore how ge
BREAK
Please visit our sponsors in the Exhibit Hall and explore their resources. They're standing by to answer your questions.
Presentation by Okta
Model Red-Teaming: Dynamic Security Analysis for LLMs
The rise of Large Language Models has many organizations rushing to integrate AI-powered tools into existing products, but they introduce significant new risk. OWASP has recently introduced the LLM Top 10 to highlight these novel threat vectors, including prompt injection and data exfiltration. However, existing AppSec tools are not designed to detect and remediate these vulnerabilities. In particular, static analysis (SAST), one of the most common tools, cannot be used since there is no code: m