From Logs to Defense: Building AI Enhanced XDR Pipelines for Application Level Threats track 1

Author: OWASP Foundation - Bewertung: 0x - Views:2

Security teams collect huge volumes of application logs every day, yet many organizations struggle to turn those logs into timely and meaningful security actions. This talk introduces a simple, approachable way to think about how logs can evolve into real defenses using AI-enhanced XDR pipelines.

Starting from the basics, we will explore what application logs are, why they matter for security, and how they can be used as signals to detect potential threats. The session then walks through how AI can help identify unusual behavior in logs and how those insights can flow into an XDR pipeline to support detection and response at the application level.

This talk focuses on concepts and practical understanding rather than complex algorithms or advanced security theory. No prior experience with AI or XDR is required. Attendees will leave with a clear mental model of how logs, AI, and XDR work together, and a practical understanding of how organizations can begin moving from raw log data to proactive defense.

Ramya Ganesh
XDR Automation space
Cybersecurity and AI professional

Ramya Ganesh is a cybersecurity and AI professional with over 20 years of experience building, testing, and securing large-scale cloud and SaaS applications. She works in the XDR Automation space, where she focuses on transforming raw application logs into actionable security signals using Python, AI, and agentic workflows.

Her work spans AI-enhanced threat detection, automation pipelines, and practical security engineering, with a strong emphasis on making complex concepts accessible to beginners. Ramya is a finalist for the Women in Tech 2025 Awards and has been featured in Times Square for her contributions to technology and community impact. She is also an active speaker, mentor, and advocate for diversity in cybersecurity and AI.
-

Managed by the OWASP® Foundation
https://owasp.org/