Webinar Description
Key Takeaways
- Explores the security challenges of deploying AI features and models in AWS cloud environments
- Highlights the limitations of traditional Web Application Firewalls (WAFs) for AI-generated traffic
- Introduces behavioral detection and machine learning-driven security models as alternatives
- Provides frameworks for evaluating and adapting runtime security tools for AI-first applications
- Targets security professionals, cloud architects, and IT leaders responsible for AI deployments
The webinar “Runtime AI Governance on AWS: Deployment to Control” brings together experts from Wallarm and AWS to address a rapidly emerging challenge: securing AI-driven applications and APIs in the cloud. As organizations accelerate their adoption of AI features, the security landscape is shifting, exposing new blind spots that traditional defenses struggle to cover.
Why AI Security Demands a New Approach
AI-generated traffic often bypasses the detection capabilities of signature-based Web Application Firewalls. These legacy tools were designed for predictable attack patterns, but AI models can generate novel, context-aware requests that evade conventional rules. This creates a significant gap in runtime protection, especially for organizations integrating AI into customer-facing products or internal systems.
Behavioral Detection and Machine Learning in Practice
The session delves into the operational realities of defending AI-first environments. Rather than relying on static signatures, behavioral detection and positive security models are presented as more adaptive solutions. Machine learning-driven approaches can identify anomalous activity in real time, offering a path forward for teams seeking to secure dynamic, AI-powered APIs and applications.
Evaluating and Evolving Runtime Security Tools
Security professionals are encouraged to critically assess their current runtime defenses. The discussion covers practical frameworks for identifying gaps, justifying new investments, and moving beyond rules-based protection. Attendees gain actionable steps to strengthen AI governance and close the visibility gap in production environments.
Industry Context and Audience
This event sits at the intersection of application security, cloud security, and AI governance. It is tailored for security architects, DevSecOps teams, product managers, and IT leaders—particularly those in organizations with advanced digital infrastructure and a commitment to cloud-native development. The content is especially relevant for professionals responsible for deploying and protecting AI models in production.
Format and Experience
Delivered as a live, virtual webinar, the session features expert speakers from Wallarm and AWS. Participants benefit from real-world insights, practical frameworks, and the opportunity to engage with leaders in AI security. All registrants receive access to a recording, supporting ongoing learning and reference.
Commercial and Strategic Relevance
While the event is educational in nature, it also serves as a platform for Wallarm to showcase its AI Control Platform and expertise in runtime AI security. The session positions Wallarm as a thought leader in the space, with a focus on actionable solutions and partnership opportunities for organizations navigating the complexities of AI governance on AWS.