Webinar Description
Key Takeaways
- Webinar addresses security gaps in large language model applications and autonomous agents with tool access
- Covers why traditional web application firewalls fail against natural language payloads and indirect prompt injection
- Examines Model Context Protocol (MCP) integrations and excessive privilege risks for autonomous agents accessing internal APIs
- Includes live demonstration of prompt injection attack and defense using intent-based detection
- Relevant for security teams, application developers and enterprise architects deploying production applications
About the Event
AI-Native Firewalling for LLM and Agentic Applications is a webinar hosted by Prophaze on Wednesday, October 21, 2026 at 4:00 PM IST. The session runs for 45 minutes of technical walkthrough and live demonstration, followed by 15 minutes of open panel discussion.
Why Traditional WAFs Fall Short
The session examines a fundamental mismatch between conventional web application firewall architecture and the threat landscape for applications built on large language models. Standard WAFs rely on static signatures and pattern matching to identify malicious requests. Natural language payloads, indirect prompt injections and contextual attacks contain no recognizable malicious syntax, allowing them to bypass signature-based detection entirely. The webinar explores how this creates a visibility gap that security teams must address differently.
Agentic Applications and MCP Risk
Autonomous agents connected through Model Context Protocol integrations present a distinct security challenge. These agents call internal APIs independently, often operating with privileges originally granted for convenience rather than security. The session addresses how MCP integrations can grant excessive access to internal systems and discusses approaches to scope down agent permissions appropriately.
OWASP LLM Top 10 and Data Exposure
The webinar provides a technical walkthrough of the OWASP LLM Top 10, with particular focus on LLM01 Prompt Injection, supply chain exposure and data exfiltration vectors. A separate segment addresses data leakage risks when personally identifiable information and intellectual property are processed through public or third-party models, an area the session characterizes as an emerging blind spot for many organizations.
Live Demonstration
The session includes a real-time demonstration of a prompt injection attack bypassing standard guardrails. This is followed by a demonstration of intent-based detection and neutralization using Prophaze’s firewall technology, illustrating the difference between syntax-based and intent-based approaches to filtering inputs and outputs.
Who Should Attend
This webinar is designed for security professionals responsible for protecting applications that incorporate large language models, as well as development teams shipping these applications into production. Enterprise architects evaluating real-time input and output filtering for production deployments will find the deployment framework discussion relevant.