Webinar Description
Key Takeaways
- Training session demonstrating AI integration with DefectDojo Pro for accelerated vulnerability management maturity
- Covers Model Context Protocol server implementation, automated reporting, and AI-powered remediation workflows
- Designed for CISOs, security engineers, AppSec leaders, and DevSecOps practitioners
- Explores integration with major LLMs including Claude, ChatGPT, and Gemini
- Addresses STRIDE threat modelling and compliance reporting automation
Introduction
AI Use Cases with DefectDojo Pro: Maturing Vulnerability Management Overnight is a virtual training session examining how artificial intelligence can compress traditional vulnerability management programme timelines. The webinar targets security professionals seeking to understand practical applications of AI agents within established security tooling. As organisations face mounting pressure to remediate vulnerabilities faster while maintaining compliance, the intersection of large language models and security operations has become increasingly relevant to application security teams.
About This Event
This webinar-format training session is led by a Principal Solutions Architect from DefectDojo. The programme focuses on demonstrating how AI-driven automation can reduce the time required to mature vulnerability management capabilities from months to days. Rather than theoretical discussion, the session emphasises practical demonstrations and implementation guidance for security teams considering AI integration within their existing workflows.
AI Integration Approaches for Vulnerability Management
The training examines three distinct integration pathways for incorporating AI capabilities into vulnerability management operations. The first involves the Model Context Protocol (MCP) server, which provides structured and secure access for large language models to interact with security data. This approach addresses a fundamental challenge in AI-security integration: enabling LLMs such as Claude, ChatGPT, and Gemini to access sensitive vulnerability information without compromising data governance requirements.
The second integration pathway focuses on using AI agents to generate custom reports and dashboards. Security teams frequently struggle with translating raw vulnerability data into formats suitable for different stakeholders, from technical remediation guidance for engineering teams to executive-level risk summaries for leadership. AI-assisted report generation can automate much of this translation work while maintaining consistency across outputs.
The third area covers DefectDojo Sensei, an AI-powered capability for auto-remediation and threat modelling. This includes generating human-approved pull requests that address identified vulnerabilities, integrating with version control platforms including GitHub, GitLab, Bitbucket, and Azure DevOps. The threat modelling component incorporates STRIDE methodology, a framework that categorises threats across spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege.
Operational Challenges Addressed
Vulnerability management programmes traditionally mature through incremental process improvements over extended periods. Manual triage, inconsistent prioritisation, and bottlenecked remediation workflows create backlogs that compound over time. The training addresses how AI automation can accelerate several historically labour-intensive activities: risk prioritisation across large vulnerability inventories, compliance reporting against regulatory frameworks, and the generation of actionable remediation guidance.
Security teams also face challenges in making vulnerability data accessible to stakeholders who lack deep technical expertise. Executive dashboards and compliance reports require different presentations of the same underlying data, and maintaining these outputs manually consumes analyst time that could otherwise support remediation efforts.
Who Should Attend
The session is designed for security professionals responsible for vulnerability management operations and strategy. This includes CISOs evaluating AI adoption within their security programmes, security engineers implementing and maintaining vulnerability management tooling, and AppSec leaders overseeing application security across development portfolios. Penetration testers, managed security service providers, and DevSecOps practitioners working to integrate security into continuous delivery pipelines will also find relevant material in the training content.
Organisations at various stages of vulnerability management maturity may benefit, whether establishing foundational processes or seeking to optimise existing programmes through automation.