Yuvaraj Govindarajulu
Head of Research and Innovation, AIShield (Powered by Bosch)
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Yuvaraj Govindarajulu is a technical leader with over a decade of experience in AI, Cybersecurity and Embedded Systems R&D. He is the AVP - Product Engineering & Head of Research at Protectt.ai. He is the co-lead of the OWASP AI Bill of Materials Project and the Co-Author, Workstream lead (Harmonization) at the OWASP AI Exchange. With over 22+ International patents filed, his key areas of focus include AI Red Teaming, GenAI Guardrails, Ransomware Attacks on AI Systems and AI supply chain Security.
Yuvaraj is a co-author and a key contributor to the AI Security Testing section, GenAI Red Teaming Guide, Agentic AI Red Teaming Guide. Previously, Yuvaraj was an active member of standard bodies shaping global AI security, including ETSI and ISO. His previous talks and publications include presentations at prominent conferences such as OWASP AppSec EU, BSI IT Security congress, NeurIPS, DEFCON and IEEE SecDev. Yuvaraj also served as the technical lead for the EU Horizon Project "COBALT", with focus on continuous AI certification. With a proven track record of innovation, he has developed novel solutions that have translated into products and impactful industry contributions.
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Building Secure Agentic AI Systems Through Embedded Testability
To improve the testability of Agentic AI Systems, we propose that agentic AI systems be built with internal instrumentation – hooks at key components (input and output prompts, tool/service/API calls, memory, etc.) that are active during development and testing, and can be toggled or closed in production. These built-in test interfaces enable both rigorous pre-deployment testing (e.g. unit tests for agent decision steps, adversarial red-teaming, robustness evaluations) and ongoing post-deployment monitoring (capturing behavioral traces for auditing and anomaly detection). By treating the AI agent not as an opaque structure but as a composition of testable sub-components, developers can pinpoint failure modes and ensure each part meets reliability and safety criteria. This approach supports behavioral traceability (recording the agent’s step-by-step reasoning), decision auditability (retaining logs of decisions and actions for later review), tool/function call transparency (monitoring external API calls or real-world actions), and other critical testing areas like robustness and safety via red teaming.
Emerging Frontiers: Ransomware Attacks in AI Systems
This session will delve into the convergence of ransomware and Artificial Intelligence/Machine Learning (AI/ML) systems, providing attendees with a comprehensive understanding of the evolving ransomware landscape in AI environments. The presentation will cover:
The progression of ransomware from traditional attacks to AI-driven variants.
Vulnerabilities in AI/ML systems, such as supply chains, models, and training pipelines, that adversaries can exploit for ransomware attacks.
Real-world examples of potential ransomware exploits in predictive AI (e.g., OWASP ML06: 2023 ML Supply Chain Attacks) and generative AI (e.g., OWASP LLM06: Excessive Agency).
Practical strategies and AI-driven solutions to detect, protect against, and mitigate ransomware threats.
Attendees will gain actionable insights into adapting traditional ransomware defenses to safeguard modern AI infrastructures and explore open challenges in standardizing defenses for AI/ML systems. The session will also provide references to OWASP frameworks and insights from the OWASP AI Exchange.
OWASP AppSec Days Banglore 2025 Sessionize Event
OWASP Global AppSec EU 2025 - CFP Sessionize Event
Yuvaraj Govindarajulu
Head of Research and Innovation, AIShield (Powered by Bosch)
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