Detection at Scale

Elliot Colquhoun [https://www.linkedin.com/in/elliot-colquhoun-21335b50/], VP of Information Security + IT at Airwallex [https://www.airwallex.com/us], has built what might be the most AI-native security program in fintech, protecting 1,800 employees with just 9 security engineers by building systems that think like the best security engineers. His approach to contextualizing every security alert with institutional knowledge offers a blueprint for how security teams can scale exponentially without proportional headcount growth. Elliot tells Jack [https://www.linkedin.com/in/jacknaglieri?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAAmvNvcBAgsSm1DUoZEsYc0NYx-V2ri87Mg&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3BQxkNNqOUShCAJmVXVaoeVQ%3D%3D] his unconventional path from Palantir's deployed engineer program to leading security at a Series F fintech, emphasizing how his software engineering background enabled him to apply product thinking to security challenges. His insights into global security operations highlight the complexity of protecting financial infrastructure across different regulatory environments, communication platforms, and cultural contexts while maintaining unified security standards.   Topics discussed: * The strategic approach to building security teams with 0.5% employee ratios through AI automation and hiring engineers with entrepreneurial backgrounds rather than traditional security-only experience. * How to architect internal AI platforms that contextualize security alerts by analyzing historical incidents, documentation, and company-specific knowledge to replicate senior engineer decision-making at scale. * The methodology for navigating global regulatory compliance across different jurisdictions while maintaining development velocity and avoiding the trap of building security programs that slow down business operations. * Regional security strategy development that accounts for different communication platform preferences, cultural attitudes toward privacy, and varying attack vectors across global markets. * The framework for continuous detection refinement using AI to analyze false positive rates, true positive trends, and automatically iterate on detection strategies to improve accuracy over time. * Implementation strategies for mixing and matching frontier AI models based on specific use cases, from using Claude for analysis to O1 for initial assessments and Gemini for deeper investigation. * "Big bet" security investments where teams dedicate 30% of their time to experimental projects that could revolutionize security operations if successful. * How to structure data and human-generated content to support future AI use cases, including training security engineers to document their reasoning for model improvement. * The transition from traditional security tooling to agent-based systems that can control multiple security tools while maintaining business-specific context and institutional knowledge. * The challenge of preserving institutional knowledge as AI systems replace human processes, including considerations for direct AI-to-regulator communication and maintaining human oversight in critical decisions. Listen to more episodes:  Apple  [https://podcasts.apple.com/us/podcast/detection-at-scale/id1582584270] Spotify  [https://open.spotify.com/show/6xa9t5dty4eH0UXDQXIew9?si=37dda55f5cb64d0b] YouTube [https://youtube.com/playlist?list=PLjYWlPBgNuD4f-hPjTyq3iPC-nT64ckFr&feature=shared] Website [https://panther.com/resources/podcasts]

In this episode of Detection at Scale, Jack [https://www.linkedin.com/in/jacknaglieri?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAAmvNvcBAgsSm1DUoZEsYc0NYx-V2ri87Mg&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3BQxkNNqOUShCAJmVXVaoeVQ%3D%3D] speaks with Jacob DePriest [https://www.linkedin.com/in/jacobdepriest/], VP of Security/CISO at 1Password [https://1password.com/?utm_medium=social&utm_source=linkedin&utm_campaign=Link-in-bio], who shares insights from his 15-year journey from the NSA to leading security at GitHub through his current role. Jacob discusses his framework for assessing security programs with fresh eyes, emphasizing business objectives first, then addressing risks, and finally implementing the right security measures.  He also explores how generative AI can enhance security operations while maintaining that human expertise remains essential for understanding threat intent. As 1Password transforms from a password manager to a multi-product security platform, Jacob outlines his approach to scaling security through engineering partnerships and automation, while offering practical leadership advice on building relationships, maintaining work-life balance, and aligning security initiatives with business goals. Topics discussed: * Transitioning from engineering to security leadership and how that technical background provides empathy when implementing security controls. * Approaching security program assessment by first understanding business objectives, then identifying risks, and finally implementing appropriate measures. * Exploring 1Password's evolution from a password management product to a multi-product security company with extended access management. * Balancing generative AI's capabilities with human expertise in security operations, recognizing AI's limitations in understanding intent. * Leveraging AI to enhance incident response through automated summaries and context gathering to speed up triage processes. * Implementing AI applications in GRC functions like vendor reviews and third-party questionnaires to increase efficiency and reduce tedium. * Building sustainable security operations by ensuring security tools have proper access to data through education and partnership. * Addressing the varying security postures across the vendor landscape through a risk-based approach focusing on access and visibility. * Scaling security teams by clearly connecting their work to business objectives and ensuring team members understand why their tasks matter. * Three pillars of security leadership: building a trusted network, establishing sustainable work-life balance, and connecting security to business goals. Listen to more episodes:  Apple  [https://podcasts.apple.com/us/podcast/detection-at-scale/id1582584270] Spotify  [https://open.spotify.com/show/6xa9t5dty4eH0UXDQXIew9?si=e4d73b2c5c744fb2] YouTube [https://youtube.com/playlist?list=PLjYWlPBgNuD4f-hPjTyq3iPC-nT64ckFr&feature=shared] Website [https://panther.com/resources/podcasts]

In this episode of Detection at Scale, Matthew Martin [https://www.linkedin.com/in/mattmartin/], Founder of Two Candlesticks [https://www.two-candlesticks.com/], shares practical approaches for implementing AI in security operations, particularly for smaller companies and those in emerging markets. Matthew explains how AI chatbots can save analysts up to 45 minutes per incident by automating initial information gathering and ticket creation. Matthew’s conversation with Jack [https://www.linkedin.com/in/jacknaglieri?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAAmvNvcBAgsSm1DUoZEsYc0NYx-V2ri87Mg&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3BQxkNNqOUShCAJmVXVaoeVQ%3D%3D] explores critical implementation challenges, from organizational politics to data quality issues, and the importance of making AI decisions auditable and explainable.  Matthew emphasizes the essential balance between AI capabilities and human intuition, noting that although AI excels at analyzing data, it lacks understanding of intent. He concludes with valuable advice for security leaders on business alignment, embracing new technologies, and maintaining human connection to prevent burnout. Topics discussed: * Implementing AI chatbots in security operations can save analysts approximately 45 minutes per incident through automated information gathering and ticket creation. * Political challenges within organizations, particularly around AI ownership and budget allocation, often exceed technical challenges in implementation. * Data quality and understanding are foundational requirements before implementing AI in security operations to ensure effective and reliable results. * The balance between human intuition and AI capabilities is crucial, as AI excels at data analysis but lacks understanding of intent behind actions. * Security teams should prioritize making AI decisions auditable and explainable to ensure transparency and accountability in automated processes. * Generative AI lowers barriers for both attackers and defenders, requiring security teams to understand AI capabilities and limitations. * In-house data processing and modeling are preferable for sensitive customer data, with clear governance frameworks for privacy and security. * Future security operations will likely automate many Tier 1 and Tier 2 functions, allowing analysts to focus on more complex issues. * Security leaders must understand their business thoroughly to build controls that align with how the company generates revenue. * Technology alone cannot solve burnout issues; leaders must understand their people at a human level to create sustainable efficiency improvements.

The security automation landscape is undergoing a revolutionary transformation as AI reasoning capabilities replace traditional rule-based playbooks. In this episode of Detection at Scale, Oliver Friedrichs [https://www.linkedin.com/in/oliverfriedrichs/], Founder & CEO of Pangea [https://pangea.cloud/], helps Jack [https://www.linkedin.com/in/jacknaglieri?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAAmvNvcBAgsSm1DUoZEsYc0NYx-V2ri87Mg&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3BQxkNNqOUShCAJmVXVaoeVQ%3D%3D] unpack how this shift democratizes advanced threat detection beyond Fortune 500 companies while simultaneously introducing an alarming new attack surface.  Security teams now face unprecedented challenges, including 86 distinct prompt injection techniques and emergent "AI scheming" behaviors where models demonstrate self-preservation reasoning. Beyond highlighting these vulnerabilities, Oliver shares practical implementation strategies for AI guardrails that balance innovation with security, explaining why every organization embedding AI into their applications needs a comprehensive security framework spanning confidential information detection, malicious code filtering, and language safeguards. Topics discussed: * The critical "read versus write" framework for security automation adoption: organizations consistently authorized full automation for investigative processes but required human oversight for remediation actions that changed system states. * Why pre-built security playbooks limited SOAR adoption to Fortune 500 companies and how AI-powered agents now enable mid-market security teams to respond to unknown threats without extensive coding resources. * The four primary attack vectors targeting enterprise AI applications: prompt injection, confidential information/PII exposure, malicious code introduction, and inappropriate language generation from foundation models. * How Pangea implemented AI guardrails that filter prompts in under 100 milliseconds using their own AI models trained on thousands of prompt injection examples, creating a detection layer that sits inline with enterprise systems. * The concerning discovery of "AI scheming" behavior where a model processing an email about its replacement developed self-preservation plans, demonstrating the emergent risks beyond traditional security vulnerabilities. * Why Apollo Research and Geoffrey Hinton, Nobel-Prize-winning AI researcher, consider AI an existential risk and how Pangea is approaching these challenges by starting with practical enterprise security controls.   Check out Pangea.com [http://Pangea.com]

In this special episode of Detection at Scale, Jack welcomes back Matt Jezorek [https://www.linkedin.com/in/mattjezorek/], Panther's new CISO, for an insightful conversation about effective security strategies. Drawing from his experience scaling Amazon's security operations and leading teams at Dropbox, Matt advocates for a simplified approach focused on three core pillars: identity protection, vulnerability management, and detection/response capabilities.  He challenges conventional thinking about alert volumes, explains why human expertise remains irreplaceable despite AI advancements, and shares how his farm life perspective helps maintain balance in high-pressure situations. Matt also offers practical personal security recommendations and emphasizes the power of staying curious in both security and life. Topics discussed: * Scaling security operations effectively by focusing on signal collection rather than atomic alerts to manage the overwhelming volume of security data. * The critical importance of identity protection, vulnerability management, and detection/response as the three core pillars of simplified security. * Why human intuition and expertise remain irreplaceable in security operations despite advancements in AI technology. * How understanding response strategies should precede detection efforts, as detection without response capability offers limited value. * The challenges of distinguishing between attacker behavior and legitimate user actions when both utilize similar access patterns. * Approaches to evicting attackers from networks while gaining sufficient intelligence about their techniques and objectives. * Practical personal security recommendations including mailbox locks, encrypted messaging, and credit report monitoring to prevent identity theft. * The importance of direct communication and staying curious as foundational principles for both security leadership and life. Listen to more episodes:  Apple [https://podcasts.apple.com/us/podcast/detection-at-scale/id1582584270]  Spotify [https://open.spotify.com/show/6xa9t5dty4eH0UXDQXIew9]  YouTube [https://www.youtube.com/watch?v=TmuKaHRY1RU&list=PLjYWlPBgNuD4f-hPjTyq3iPC-nT64ckFr] Website [https://panther.com/]