Webinar Description
Key Takeaways
- Explores the distinction between deterministic rule-based scanning and agentic AI-driven code analysis
- Addresses cost-benefit considerations when deploying AI models for security testing at scale
- Presents benchmark results comparing AI model performance in vulnerability detection
- Demonstrates real-world cases where AI identified vulnerabilities missed by traditional engines
- Designed for application security professionals, DevSecOps teams and security leadership
Introduction
Beyond SAST: An Analyst’s Guide to Agentic Code Scanning and AI SAST is a virtual webinar examining how artificial intelligence is reshaping static application security testing. Presented by Cycode and Latio Tech, the session targets application security professionals and engineering leaders navigating the transition from conventional rule-based scanning to AI-augmented approaches. As organisations accelerate software delivery while facing increasingly sophisticated threats, understanding where traditional SAST falls short and how agentic scanning addresses those gaps has become a pressing concern for security teams.
About This Event
This on-demand webinar provides a technical, analyst-focused examination of AI-enabled code scanning. The session combines practical demonstrations with benchmark data, offering attendees concrete evidence rather than theoretical discussion. Cycode, a platform provider in the application security space, hosts the event alongside Latio Tech, contributing independent analysis and real-world case studies to the presentation.
Deterministic Scanning Versus Agentic AI Analysis
Traditional static application security testing relies on deterministic rule-based engines. These tools match code patterns against known vulnerability signatures, providing consistent and predictable results. However, their effectiveness depends entirely on the comprehensiveness of their rule sets, meaning novel vulnerability patterns or context-dependent security issues often evade detection.
Agentic code scanning represents a fundamentally different approach. Rather than pattern matching, these systems employ AI reasoning to analyse code behaviour, understand context and identify security implications that rigid rules cannot capture. The webinar explores this distinction in depth, helping attendees understand when each approach delivers value and where their respective limitations emerge.
Cost and Scalability Considerations
Deploying AI for security testing introduces economic questions that traditional tooling does not present. The session addresses the trade-offs between frontier AI models, which offer superior reasoning capabilities at higher computational cost, and more affordable alternatives that may sacrifice some detection accuracy. For organisations scanning large codebases frequently, these cost differences compound significantly.
The webinar provides practical guidance on determining appropriate scanning frequency and scope, helping security teams balance thoroughness against resource constraints. This cost-benefit analysis proves particularly relevant for enterprises managing extensive application portfolios where scanning every commit with the most capable models may prove economically impractical.
Detecting Complex Vulnerability Chains
One capability distinguishing agentic scanning from traditional approaches involves identifying how multiple lower-severity issues combine into critical exploit paths. A series of individually minor vulnerabilities may chain together to enable significant attacks, yet rule-based engines evaluating each finding in isolation often miss these relationships.
The session presents examples including authorisation-related CVEs where AI-driven analysis detected vulnerabilities that deterministic scanning overlooked. These demonstrations illustrate the practical security improvements agentic approaches can deliver, moving beyond theoretical capabilities to documented results.
Who Should Attend
The webinar serves application security professionals, security analysts and product security managers evaluating how AI fits within their existing programmes. CISOs and security leadership seeking to understand the strategic implications of these technologies will find relevant material, as will DevSecOps teams responsible for integrating security tooling into development workflows. The content assumes familiarity with application security fundamentals and addresses organisations with established or maturing security programmes rather than those building initial capabilities.
Practical Value for Security Teams
Beyond technology comparison, the session addresses operational challenges security teams face when adopting AI-assisted code review. Prioritising and remediating findings across complex codebases remains difficult regardless of detection method, and the webinar offers strategies for managing this workload effectively. The benchmark results shared during the presentation provide concrete data points for teams building business cases or evaluating vendor claims in this rapidly evolving market segment.