Future of Threat Intelligence

Fortinet processes telemetry from 50% of the next-generation firewall market, giving Aamir Lakhani, Global Director of Threat Intelligence & Adversarial AI Research, and his team visibility into a looming shift: threat actors moving from exploiting a small subset of proven CVEs to weaponizing the entire vulnerability landscape through AI automation. While defenders currently concentrate resources on commonly exploited vulnerabilities, Aamir warns AI will soon enable attacks across everything "just as efficiently and as fast," requiring security teams to rethink patch management strategies when they can no longer rely on focused defense. Aamir also touches on how The World Economic Forum's Cybercrime Atlas program operates through weekly sessions with 20-40 researchers who deliberately build intelligence packages using only open-source methods. This avoids proprietary data so law enforcement can recreate findings and successfully prosecute cases. He shares how his leadership approach rejects the traditional climb: stay at the bottom of the ladder and push your team up, because their public accomplishments improve both team performance and your career trajectory more than personal competition ever could.Topics discussed:A 50% next-generation firewall market share providing visibility into state-sponsored attacks and ransomware-as-a-service operations dailyAI-driven threat evolution from narrow CVE exploitation to automated attacks across vulnerability landscapes requiring new patch strategiesThreat actor professionalization, including recruitment events, training programs, and internal conferences for cybercrime operationsAdversarial AI capabilities using local LLM training with tools like Ollama to bypass jailbroken model dependencies like WormGPTNetwork-centric threat hunting using metadata and netflow analysis over full packet capture due to bandwidth and analysis constraintsWorld Economic Forum Cybercrime Atlas program methodology using open-source intel to build prosecutable law enforcement intel packagesPrioritizing team advancement over personal climbing by publicizing subordinate accomplishments to improve retention and performanceAI alert fatigue emerging from comprehensive attack cycle tracking where 10% incorrect information invalidates 90% accurate findingsKey Takeaways: Prepare for AI-enabled threat actors to exploit the entire CVE landscape simultaneously.Prioritize metadata and netflow analysis over full packet capture for threat hunting due to better manageability and analysis efficiency.Deploy open-source tools to baseline network behavior and marry telemetry data with threat intel platforms for pattern recognition.Identify your organization's critical pain points that would force ransom payment rather than focusing solely on perimeter defense tech.Join collaborative threat research initiatives like World Economic Forum's Cybercrime Atlas.Build intelligence packages using open-source methods to ensure findings can be recreated and prosecuted.Conduct CTF-based interviews focused on problem-solving approach and persistence rather than expecting candidates to know all answers.Spotlight team by publicizing accomplishments and research contributions to improve retention, morale, and your own career advancement.Mandate regular video check-ins to monitor team mental health and prevent burnout in high-stress roles.Listen to more episodes: Apple Spotify YouTubeWebsite

PayPal's fraud team catches credential stuffing before money moves by watching business intelligence signals that most organizations overlook: explosive traffic growth to legacy endpoints, mismatched phone numbers against account creation locales, and anomalies hidden in raw uncleaned data. Blake Butler, Senior Manager & Head of Fraud Threat Intelligence, applies infrastructure analysis techniques from offensive security to fraud investigations. This fills the gap most organizations face: anti-fraud teams understand scam mechanics but lack technical depth, whereas infosec practitioners know infrastructure but not how criminals monetize accounts at scale.Blake breaks down how phishing kits now bypass MFA through real-time automation. His detection philosophy: counting and explosive growth patterns beat machine learning for uncovering fraud. Data scientists clean away the signal. Topics discussed:Applying offensive security infrastructure analysis methods to fraud threat intelligence investigationsDetecting credential stuffing and account takeover campaigns through anomalies in account creation regions, phone number locales, and explosive traffic growthUnderstanding how modern phishing kits automate real-time OTP theft by integrating directly into legitimate platform APIs during password resetsTracking massive fraud operations emerging from China and South America through business intelligence signalsIdentifying fraud indicators in uncleaned data: extra spaces, unrenderable characters, and AI-generated webshop metadata artifactsBuilding security communities to enable monthly collaboration with local practitioners on emerging threats and tool developmentBridging the critical talent gap between anti-fraud teams lacking technical infrastructure skills and infosec practitioners without fraud monetization expertiseEvaluating phishing-as-a-service platforms and encrypted communication tools that lower barriers to entry for criminal actorsKey Takeaways: Monitor explosive traffic growth patterns to legacy endpoints and unusual account creation regions to detect credential stuffing.Analyze raw uncleaned data for fraud signals including extra spaces, unrenderable characters, and metadata artifacts.Apply infrastructure analysis techniques to fraud investigations to identify phishing domains and criminal tooling.Track mismatches between phone number locales and account creation regions as indicators of automated account generation.Investigate anomalies in business intelligence metrics through simple counting before deploying MLMs to uncover emerging fraud trends.Build fraud threat intelligence teams that combine offensive security backgrounds with fraud monetization expertise to fill the critical industry talent gap.Attend security community meetups to collaborate with local practitioners on emerging threats between annual conferences.Implement MFA while recognizing that advanced phishing kits now automate real-time OTP theft through direct platform API integration.Hire candidates with infosec infrastructure knowledge who understand how criminal actors use tooling to automate credential stuffing and account monetization operations.Listen to more episodes: Apple Spotify YouTubeWebsite

Tidal Cyber's Director of Cyber Threat Intelligence Scott Small reveals how his knowledge base now tracks almost 25,000 procedure-level instances across nearly 800 MITRE ATT&CK techniques and sub-techniques, capturing the command-level detail that exposes the false promise of "100% coverage" when working at technique abstraction alone. He argues that the pre-attack reconnaissance phase remains the most essential yet most ignored portion of the framework, including the recently formalized technique for purchasing and selling victim data on stealer marketplaces. Scott's AI workflow treats LLMs strictly as structured data processors that reference MITRE's written technique examples to parse unstructured threat reports, refusing to use them as intelligence sources themselves. He's seeing threat intelligence and detection engineering roles merge as individuals develop hybrid skill sets. His methodology for mapping TTPs to vulnerabilities gives security teams a data-driven rationale to deprioritize patches when strong post-exploitation defenses already cover the attack vector.Topics discussed:Tracking almost 25,000 procedure-level instances across 800 MITRE ATT&CK techniques to expose the false promise of technique-level coverage aloneDefending pre-attack reconnaissance phases including the technique for purchasing victim data on stealer marketplacesClassifying scanning activity by threat type to prioritize C2 infrastructure linked to APTs over fraud-related domainsBlending threat intelligence and detection engineering roles as analysts gain EDR skills Using AI as structured data processors that reference MITRE's written technique examples to parse unstructured threat reports without generating intelligenceMapping TTPs to vulnerabilities to create data-driven rationale for deprioritizing patches when post-exploitation defenses cover the vectorVisualizing attack narratives through the MITRE ATT&CK matrix to tell leadership about defense gaps and justify resource allocation decisionsKey Takeaways: Track adversary procedures at the command and protocol level to identify real defense gaps.Monitor stealer marketplace activity and automated dealer platforms for credential exposures tied to your domain, then reset credentials.Prioritize threat intel alerts by focusing first on APT-linked activity over fraud campaigns.Develop hybrid skill sets where CTI analysts understand EDR logging capabilities and threat hunters consistently consult adversary behavior reporting for hunt hypotheses.Implement AI workflows that use LLMs to extract structured technique data from unstructured threat reports, not as intelligence output itself.Map TTPs to specific vulnerabilities to build data-driven cases for deprioritizing patches when post-exploit defenses provide coverage.Create visual attack narratives using the MITRE ATT&CK matrix to communicate defense gaps and resource needs.

When Casey Beaumont's entire CTI team departed just before new analysts started, she found herself running threat intelligence solo for months while directing incident response, threat hunting, and red team operations. That trial by fire taught her exactly what separates tactical intelligence from strategic value, and why the best analysts invest significant personal time building trust networks that enterprise tools cannot replicate. Casey's teams at Marsh McLennan, where she’s the Director of Advanced Cyber Practices, received warnings about Scattered Spider infrastructure 20 minutes after domains registered, before threat actors sent a single SMS phishing message to employee cell phones. That early intelligence enabled blocking domains internally and preparing communications before the first report came in. These private intel networks, built through years of trust and after-hours engagement, consistently deliver the warnings that matter most for large enterprises facing sophisticated, targeted attacks.   Beyond tactical response, Casey explains how her CTI program produces strategic intelligence that drives architectural decisions. She also shares her framework for vendor breach assessments that cuts through legal wordplay, why attribution matters far less than response speed during active incidents, and how to scope CTI mission appropriately to prevent analyst burnout in organizations with massive attack surfaces.   Topics discussed: Managing unified teams of CTI, threat hunting, red team, and incident response to eliminate resource allocation friction during active incidents and supply chain events. Building private intelligence networks that deliver infrastructure warnings within 20 minutes of threat actor activity. Transitioning from tactical incident response to strategic CTI leadership and learning analyst tradecraft through necessity when running solo. Conducting vendor breach assessments using four critical questions about control gaps, persistence, data exposure, and remediation plans. Evaluating intelligence relevance at large enterprises with complex environments where shadow IT, acquisitions, and distributed technology create unclear exposure. Why vendor breaches should not automatically disqualify partnerships and how strong vendor relationships enable influence over authentication improvements and security controls. Producing strategic CTI that drives architectural investment decisions by documenting systemic risks across technology ecosystems rather than isolated incidents. Understanding CTI stakeholder needs through deliberate interviewing to prevent analysts from producing reports that leadership ignores. Sharing unattributed intelligence with law enforcement that enabled warnings to seven or eight fully breached companies with no awareness of compromise. Why leadership overemphasizes attribution during active incidents when tactical response and containment should take priority. How great CTI analysts invest significant personal time building professional brands, attending conferences, and earning trust in private intelligence communities. Key Takeaways:  Consolidate CTI, threat hunting, red team, and incident response under unified leadership to eliminate resource allocation friction during active supply chain incidents and targeted attacks. Conduct vendor breach assessments using four critical questions: what control gaps enabled the breach, does the actor maintain persistence, what client data was exposed, and what remediation plans address root causes. Identify vendor evasiveness during breach discussions by listening for careful language around product names that insinuate limited scope while obscuring broader organizational compromise. Produce strategic CTI reports that document systemic risks across technology ecosystems rather than isolated incidents to give executives justification for architectural investment decisions. Interview CTI stakeholders systematically to understand what intelligence formats and content they need before analysts waste time producing reports that leadership ignores. Scope CTI team mission to specific focus areas like tactical threats and supply chain rather than attempting comprehensive coverage of vulnerabilities, geopolitics, and fraud with limited staff. Share unattributed threat intelligence with law enforcement partners when legal and privacy teams approve to enable warnings for other breached organizations unaware of compromise. Deprioritize threat actor attribution during active incident response unless conclusive evidence enables tactical pivots, focusing instead on containment and remediation before forensic analysis. Listen to more episodes:  Apple  Spotify  YouTube Website

Michael Moore, CISO for the Secretary of State of Arizona's office, explains how he acts as a virtual CISO for all 15 counties by conducting physical security assessments at election facilities and providing real-time guidance during critical events. His approach treats surprise attacks as learning opportunities that should only work once, immediately sharing adversary infrastructure and TTPs across the entire election community to burn their capabilities. Michael emphasizes that misinformation, disinformation, and malinformation represent converging threat vectors that manifest as both cyber attacks and physical violence, requiring defenders to think beyond traditional security boundaries. Ryan Murray, CISO for the State of Arizona, shares his Cybersecurity Trinity for AI framework: defend from AI-enabled attacks, defend with AI-augmented tools, and defend the AI systems organizations deploy. He explains how Arizona replicated MS-ISAC functionality through AZ ISAC, enabling 1,000+ government personnel across 200+ entities to share intelligence in real time without requiring mature security programs. Ryan stresses that organizations already generate valuable threat intelligence internally through phishing reports and security alerts, and the real challenge is communication and relationship-building rather than expensive commercial feeds. Topics discussed: How physical security gaps at government facilities create tactical vulnerabilities that scale across entire states. Building sector champion models where election security and critical infrastructure specialists act as virtual CISOs for under-resourced local governments. Why misinformation, disinformation, and malinformation represent converging cyber, physical, and reputational threat vectors that radicalize populations into kinetic attacks. Implementing real-time threat intelligence sharing protocols that enable 1,000+ defenders to communicate via platforms like Slack during active incidents. The evolution from receiving threat intelligence to generating intelligence internally by analyzing phishing campaigns, user reports, and infrastructure scanning patterns. Applying the "surprise attack only works once" principle by burning adversary infrastructure and TTPs immediately through broad intelligence sharing. Why the distinction between "intelligence" in national security contexts versus cyber threat intelligence creates executive buy-in challenges. How to prove negative outcomes and communicate near-miss stories where intelligence prevented catastrophic breaches. The collapsing patch window problem where automated vulnerability discovery and exploitation eliminates traditional seven-day remediation timelines. Implementing the Cybersecurity Trinity for AI: defending from AI-enabled attacks, defending with AI-enhanced tools, and defending AI systems from prompt injection and data leakage. Why secure-by-design pledges fail when financially motivated vendors push defensive responsibility to the least capable organizations. Building tabletop exercise programs that prepare election officials for denial-of-service attacks disguised as physical threats. How generative AI enables Script Kitty 2.0, where non-technical adversaries automate reconnaissance, exploitation, and data exfiltration through natural language prompts. The challenge of deepfakes and synthetic media targeting sub-national officials who lack the visibility and resources for sophisticated reputation defense. Key Takeaways:  Build sector champion programs where specialists act as virtual CISOs for under-resourced entities. Implement real-time communication platforms like Slack that enable defenders to share threat indicators during active incidents. Generate internal threat intelligence by systematically analyzing phishing campaigns, tracking top recipients, subject lines, and infrastructure patterns. Apply the principle that surprise attacks should only work once by immediately burning adversary infrastructure and TTPs through broad community sharing. Use tabletop exercises to prepare personnel for converged threats like bomb hoaxes that function as denial-of-service attacks on critical operations. Frame AI strategy using the Cybersecurity Trinity: defend from AI-enabled attacks, defend with AI tools, and defend AI systems from exploitation. Recognize that patch windows have collapsed to zero for critical edge-facing vulnerabilities due to automated discovery and weaponization. Focus communications on near-miss stories that demonstrate how intelligence prevented catastrophic outcomes before executive awareness. Listen to more episodes:  Apple  Spotify  YouTube Website

Unlike CISOs who work with consistent vulnerabilities across cloud environments, CFOs face company-specific financial processes that change constantly, making automation historically complex to solve before the AI era. Ahikam Kaufman, CEO & CFO of Safebooks AI, explains why machine learning is the only viable solution to detect sophisticated embezzlement schemes that regulatory compliance demands every public company address — with no materiality threshold.  His background building fraud prevention systems at Intuit and Check has taught him how graph technology can link seemingly unrelated financial transactions to expose coordinated internal fraud attempts that would be impossible for humans to catch at scale. The challenge is compounded by the fact that most finance staff are accountants, not technologists, requiring AI tools that bridge data complexity without demanding high technical skill levels. Topics discussed: Sarbanes-Oxley requires fraud protection programs with no materiality thresholds, yet most organizations lack systematic detection across payroll, vendor, and expense systems. Financial fraud detection requires unique AI models for each company using historical data, unlike consistent threats across organizations. Advanced fraud schemes link multiple transaction types requiring graph technology to connect disparate activities that individual monitoring would miss. Fraudsters use AI for parallel attacks, fake invoices, vendor manipulation, and executive impersonation, requiring automated defense systems for real-time processing. Achieving 99.9% accuracy through structured enterprise data and rule-based controls where financial precision is non-negotiable. Financial AI platforms integrate with existing systems without replacements or workflow changes, providing immediate automation value. Key Takeaways:  Implement AI-powered fraud detection systems that monitor vendor account changes, payroll additions, and journal entry anomalies. Build company-specific AI models using 1-2 years of historical financial data to learn unique business processes, data structures, and transaction patterns. Deploy graph technology to link related financial transactions across different systems to identify coordinated fraud attempts. Establish partnerships between CFOs and CISOs to combine external cybersecurity threat detection with internal financial fraud monitoring. Focus on AI platforms that integrate with existing financial technology stacks without requiring system replacements. Create rule-based governance frameworks for financial AI systems to eliminate hallucinations and maintain accuracy levels. Monitor AI-amplified fraud techniques, such as sophisticated fake invoices, manipulated vendor banking information, and executive impersonation. Develop automated systems that can demonstrate reasonable effort for fraud prevention to satisfy regulatory requirements and insurance protections. Listen to more episodes:  Apple  Spotify  YouTube Website

Cyber insurance has transformed from a liability-focused niche product into a comprehensive business continuity tool, but widespread misconceptions continue to prevent organizations from maximizing its strategic value. Sjaak Schouteren, Cyber Growth Leader - Europe at Marsh, offers David how they combine risk quantification with business-focused communication strategies that give security leaders the tools to speak board language about cyber threats. Rather than the complex audit processes, modern cyber insurance acquisition can be remarkably streamlined. Sjaak's experience managing real-world incident response highlights how proper coverage creates strategic advantages beyond simple risk transfer, including immediate access to specialized negotiation teams and forensics experts who can extend decision timeframes during crisis situations. Topics discussed: How the 2020-2022 ransomware surge taught insurers that mid-cap companies were primary targets requiring comprehensive coverage. The three-pillar structure of modern cyber insurance covering first-party losses, third-party liability, and immediate incident response services without deductibles for initial crisis management. Why risk quantification through scenario analysis and financial impact modeling provides CISOs with the business language needed to communicate effectively with boards and C-suite executives. How risk engineers from security backgrounds have eliminated technical translation barriers between IT teams and underwriters. The strategic advantage of immediate incident response coverage that provides access to specialized forensics, legal, and negotiation teams within 48-72 hours of an incident. Why organizations with cyber insurance actually pay ransomware demands less frequently due to professional negotiation teams and comprehensive recovery support. The evolution from narrow data breach coverage to comprehensive business protection across all organization sizes. The distinction between risk mitigation through security controls and risk transfer through insurance as complementary rather than competing strategies. Key Takeaways:  Conduct cross-functional scenario planning to identify business-critical cyber risks before evaluating insurance coverage options. Map potential cyber incidents on a risk heat map measuring probability and impact to distinguish between minor inconveniences and threats that could damage business operations. Quantify average and maximum financial losses for each business-critical scenario to make data-driven decisions about risk. Leverage specialized risk engineers from security backgrounds during the underwriting process to eliminate technical translation barriers. Engage professional ransomware negotiators rather than attempting internal negotiations. Position cyber insurance as business enablement rather than just risk transfer by demonstrating how coverage strengthens overall cyber resilience. Listen to more episodes:  Apple  Spotify  YouTube Website

What happens when someone who's been building AI systems for 33 years confronts the security chaos of today's AI boom? Rob van der Veer, Chief AI Officer at Software Improvement Group (SIG), spotlights how organizations are making critical mistakes by starting small with AI security — exactly the opposite of what they should do. From his early work with law enforcement AI systems to becoming a key architect of ISO 5338 and the OWASP AI Security project, Rob exposes the gap between how AI teams operate and what production systems actually need. His insights on trigger data poisoning attacks and why AI security incidents are harder to detect than traditional breaches offer a sobering reality check for any organization rushing into AI adoption. The counterintuitive solution? Building comprehensive AI threat assessment frameworks that map the full attack surface before focused implementation. While most organizations instinctively try to minimize complexity by starting small, Rob argues this approach creates dangerous blind spots that leave critical vulnerabilities unaddressed until it's too late. Topics discussed: Building comprehensive AI threat assessment frameworks that map the full attack surface before focused implementation, avoiding the dangerous "start small" security approach. Implementing trigger data poisoning attack detection systems that identify backdoor behaviors embedded in training data. Addressing the AI team engineering gap through software development lifecycle integration, requiring architecture documentation and automated testing before production deployment. Adopting ISO 5338 AI lifecycle framework as an extension of existing software processes rather than creating isolated AI development workflows. Establishing supply chain security controls for third-party AI models and datasets, including provenance verification and integrity validation of external components. Configuring cloud AI service hardening through security-first provider evaluation, proper licensing selection, and rate limiting implementation for attack prevention. Creating AI governance structures that enable innovation through clear boundaries rather than restrictive bureaucracy. Developing organizational AI literacy programs tailored to specific business contexts, regulatory requirements, and risk profiles for comprehensive readiness assessment. Managing AI development environment security with production-grade controls due to real training data exposure, unlike traditional synthetic development data. Building "I don't know" culture in AI expertise to combat dangerous false confidence and encourage systematic knowledge-seeking over fabricated answers.   Key Takeaways:    Don't start small with AI security scope — map the full threat landscape for your specific context, then focus implementation efforts strategically. Use systematic threat modeling to identify AI-specific attack vectors like input manipulation, model theft, and training data reconstruction. Create processes to verify provenance and integrity of third-party models and datasets. Require architecture documentation, automated testing, and code review processes before AI systems move from research to production environments. Treat AI development environments as critical assets since they contain real training data. Review provider terms carefully, implement proper hardening configurations, and use appropriate licensing to mitigate data exposure risks. Create clear boundaries and guardrails that actually increase team freedom to experiment rather than creating restrictive bureaucracy. Implement ongoing validation that goes beyond standard test sets to detect potential backdoor behaviors embedded in training data. Listen to more episodes:  Apple  Spotify  YouTube Website

Karim Hijazi’s approach to threat hunting challenges conventional wisdom about endpoint security by proving that some of the most critical intelligence exists outside organizational networks. As Founder & CEO of Vigilocity, his 30-year journey from the legendary Mariposa botnet investigation to building external monitoring capabilities demonstrates why DNS analysis remains foundational to modern threat detection, even as AI transforms both offensive and defensive capabilities. In his chat with David, Karim explores how threat actors continue to rely on command and control infrastructure as their operational lifeline. His insights into supply chain threats, "low and slow" reconnaissance campaigns, and the evolution of domain generation algorithms provide security leaders with a unique perspective on proactive defense strategies that complement traditional security controls. Topics discussed: External DNS monitoring approaches that identify threat actor infrastructure before weaponization. How AI has fundamentally disrupted domain generation algorithm prediction, creating new blind spots for traditional threat intelligence. Supply chain threat intelligence methodologies that identify compromised partners and assess contagion risks. The evolution of command and control infrastructure from cleartext to encrypted communications and back. "Low and slow" reconnaissance patterns that precede ransomware attacks, operating with months-long dormancy periods. Strategies for communicating threat intelligence value to business stakeholders without creating defensive reactions from security teams. The limitations of current AI applications in security, particularly around nuanced threat analysis requiring human experience and pattern recognition. Board-level cybersecurity education requirements for organizations to survive sophisticated attacks in the next 5 years. Innovation challenges in cybersecurity where rebranding existing solutions prevents breakthrough defensive capabilities. Non-invasive threat hunting philosophies that deliver forensic-level detail without deploying endpoint agents. Key Takeaways:  Monitor external DNS communications to identify command and control infrastructure before threat actors weaponize domains against your organization. Assess supply chain partners through external threat intelligence lenses to identify compromised third parties that represent contagion risks. Develop detection capabilities for "low and slow" reconnaissance campaigns that operate with extended dormancy periods between communications. Implement AI as a noise reduction tool rather than a primary decision maker, maintaining human oversight for nuanced threat analysis. Establish board-level cybersecurity expertise to ensure adequate understanding and support for advanced threat hunting investments. Focus security innovation efforts on breakthrough capabilities rather than rebranding existing solutions with new acronyms. Correlate external threat intelligence with internal security data to validate threats and reduce false positive rates. Build threat hunting capabilities that can operate at machine speeds to handle increasing volumes of AI-generated attacks. Create communication strategies that present external threat intelligence as validation tools rather than indictments of existing security programs. Maintain expertise in DNS analysis and network fundamentals as core competencies, regardless of technological advances. Listen to more episodes:  Apple  Spotify  YouTube Website

Psychology beats punishment when building human firewalls. Craig Taylor, CEO & Co-founder of CyberHoot, brings 30 years of cybersecurity experience and a psychology background to challenge the industry's fear-based training approach. His methodology replaces "gotcha" phishing simulations with positive reinforcement systems that teach users to identify threats through skill-building rather than intimidation. Craig also touches on how cybersecurity is only 25 years old compared to other fields, like medicine's centuries of development, leading to significant industry mistakes. NIST's 2003 password requirements, for example, were completely wrong and took 14 years to officially retract. Craig's multidisciplinary approach combines psychology with security practice, recognizing that the industry's single-focus mindset contributed to these fundamental errors that organizations are still correcting today. Topics discussed: Replacing fear-based phishing training with positive reinforcement systems that teach threat identification through skill-building. Implementing seven-point email evaluation frameworks covering sender domain verification, emotional manipulation detection, and alternative communication verification protocols. Developing 3- to 5-minute gamified training modules that reward correct threat identification across specific categories. Correcting cybersecurity industry misconceptions through multidisciplinary approaches. Evaluating emerging security technologies like passkeys through industry backing analysis. Building human firewall capabilities through psychological understanding of manipulation tactics. Implementing pause-and-verify protocols to confirm unusual requests that pass technical email verification checks. Key Takeaways:  Replace punishment-based phishing simulations with positive reinforcement training that rewards users for correctly identifying threat indicators. Implement gamified security training modules instead of lengthy video sessions to maintain user engagement. Establish pause-and-verify protocols requiring alternative communication channels to confirm unusual requests that pass technical email verification checks. Evaluate emerging security technologies by examining industry backing and major sponsor adoption before incorporating them into training programs. Calibrate reward systems to provide minimal incentives (like monthly lunch gift cards) that drive engagement without creating external dependency. Train users to identify the seven key phishing indicators: sender domain accuracy, suspicious subject lines, inappropriate greetings, poor grammar, external links, questionable attachments, and emotional urgency tactics. Build internal locus of control in security training by focusing on skill mastery rather than fear-based compliance, ensuring users understand why security practices protect them personally. Deploy fully automated security training systems that eliminate administrative overhead while maintaining month-to-month flexibility and offering discounts to educational and nonprofit organizations. Listen to more episodes:  Apple  Spotify  YouTube Website

What happens when you apply economic principles like opportunity cost and comparative advantage to cybersecurity decision-making? Fernando Montenegro, VP & Practice Lead of Cybersecurity at The Futurum Group, demonstrates how viewing security through an economics lens reveals critical blind spots most practitioners miss. His approach transforms how organizations evaluate cloud migrations, measure program success, and allocate security resources. Fernando also explains why cybersecurity has evolved from a technical discipline into a socioeconomic challenge affecting society at large. His three-part framework for AI implementation — understanding the technology, mapping business needs, and assessing threat environments — offers security leaders a structured approach to cutting through hype and making strategic decisions.  Topics discussed: How security economics and opportunity cost analysis reshape cloud migration decisions and resource allocation strategies The National Academies' 2025 "Cyber Hard Problems" report and its implications for cybersecurity's expanding societal impact A three-part framework for AI implementation: technology comprehension, business alignment, and threat environment assessment Why understanding organizational business operations eliminates the biggest blind spot in threat intelligence programs Multi-layered professional networking strategies for separating signal from noise in threat intelligence analysis How cloud environments fundamentally change threat intelligence workflows from IP-based to identity and architecture-focused approaches Key Takeaways:  Apply economic opportunity cost analysis to security decisions by evaluating what you give up versus what you gain from each security investment. Map your organization's business operations across marketing, sales, and product development to provide crucial context for technical threat intelligence. Assess AI implementations through a three-part framework: technology limitations, business use cases, and specific threat considerations. Measure security program success by evaluating alignment with organizational goals and influence on non-security business decisions. Run intentional OODA loops on your security program to maintain strategic direction and continuous improvement. Listen to more episodes:  Apple  Spotify  YouTube Website

What does it take to transform a traditional event-driven SOC into an intelligence-driven operation that actually moves the needle? At T. Rowe Price, it meant abandoning the "spray and pray" approach to threat detection and building a systematic framework that prioritizes threats based on actual business risk rather than industry hype. PJ Asghari, Team Lead for Cyber Threat Intelligence Team, walked David through their evolution from a one-person intel operation to a program that directly influences detection engineering, fraud prevention, and executive decision-making. His approach centers on the "what, so what, now what" framework for intelligence reporting — a simple but powerful structure that bridges the gap between technical analysis and business action. Topics discussed: Moving beyond event-based monitoring to prioritize threats based on sector-specific risk profiles and threat actor targeting patterns rather than generic threat feeds. Focusing on financially-motivated actors, initial access brokers, and PII theft rather than nation-state activities that rarely target mid-tier financial firms directly. Addressing the cross-functional challenge that spans HR, talent acquisition, insider threat, and CTI teams. Using mise en place principles from culinary backgrounds to establish clear PIRs that align team focus with organizational needs. Creating trackable deliverables through ticket systems, RFI responses, and cross-team support that translates intelligence work into measurable business impact. Maintaining critical thinking and media literacy skills while leveraging automation for administrative tasks and threat feed processing. Key Takeaways:  Implement the "what, so what, now what" reporting structure to ensure intelligence reaches appropriate audiences with clear business implications and recommended actions. Build cross-functional relationships with fraud, insider threat, and vulnerability management teams to create measurable value through ticket creation and support requests rather than standalone reporting. Establish sector-specific threat prioritization by mapping threat actors to your actual business model rather than following generic industry threat landscapes. Create trackable metrics through service delivery, including RFI responses, expedited patching recommendations, and credential compromise notifications to demonstrate concrete value. Focus hiring on inquisitive mindset and communication skills over certifications, using interviews to assess critical thinking and ability to dig deeper into investigations. Map threat actor TTPs to MITRE framework to identify defense stack gaps and provide actionable detection engineering guidance rather than just IOC sharing. Invest in dark web monitoring and external attack surface management for financial services to catch credential compromises and brand abuse before they impact customers. Establish regular threat actor recalibration cycles to ensure prioritization remains aligned with current threat landscape rather than outdated assumptions. Listen to more episodes:  Apple  Spotify  YouTube Website

Most security leaders position themselves as guardians against risk, but Aimee Cardwell, CISO in Residence at Transcend and Board Member at WEX, built her reputation on a different approach: balancing risk to accelerate business growth. Her unconventional path from Fortune 5 CIO to CISO of a 1,200-person security team at UnitedHealth Group showcases how technical leaders can become true business partners rather than obstacles. Managing two company acquisitions every month, Aimee tells David how she developed a shifted-left security integration process that actually accelerated deal timelines while improving security outcomes. Her framework for risk appetite conversations moves executives beyond fear, uncertainty and doubt into productive discussions about cyber resilience, changing how organizations think about security investment and business enablement.   Topics discussed: How healthcare data regulations create complex compliance frameworks where companies must selectively forget customer information based on overlapping regulatory requirements. The transferable advantages CIOs bring to CISO roles, particularly in software development lifecycle security and communicating complex technical concepts to non-technical stakeholders. Shifting security strategy from risk prevention to intelligent risk balancing, enabling business growth while maintaining appropriate protection levels. Managing large-scale acquisition security integration through pre-closing requirements that accelerate post-acquisition security improvements. Establishing organizational risk appetite through worst-case scenario planning that moves leadership past emotional responses into rational decision-making frameworks. Developing cyber resilience strategies that assume incident occurrence and focus on recovery speed and impact minimization rather than just prevention. Scaling security controls based on business growth milestones, avoiding upfront overinvestment while ensuring appropriate protection as companies expand. Building consensus-driven risk acceptance frameworks while managing competing perspectives from multiple C-level executives and board members. Key Takeaways:  Implement pre-closing security requirements for acquisitions, shifting security integration 45 days before deal completion to accelerate post-acquisition timelines. Frame risk conversations around worst-case scenario analysis, using real examples and stock performance data to move executives past emotional responses and build resiliency. Develop tiered security controls that scale with business growth, implementing basic protections early and adding complexity as revenue and user bases expand. Position regulatory compliance as a competitive advantage and trust-building mechanism rather than a business constraint. Create "how do we get to yes" frameworks that start with business objectives and work backward to appropriate risk mitigation strategies. Use customer trust metrics and retention data to demonstrate security's direct contribution to business growth and competitive positioning. Leverage software development lifecycle experience to integrate security into engineering processes rather than treating it as an external validation step. Listen to more episodes:  Apple  Spotify  YouTube Website

The economics of ransomware reveal a sophisticated criminal enterprise that most security leaders dramatically underestimate. Steve Baer, Field CISO at Digital Asset Redemption, operates at the intersection of cybercrime and legitimate business, where his team's human intelligence gathering in Dark Web communities provides early warning systems that traditional security infrastructure cannot match. His insights into criminal business models, negotiation psychology, and the financial flows funding modern cybercrime offer a perspective rarely available to security practitioners. Steve walks David through Digital Asset Redemption's evolution from facilitating compliant cryptocurrency payments to building comprehensive threat intelligence capabilities using native speakers who maintain long-term relationships with criminal actors. His team's approach has enabled them to identify targeting intelligence before attacks occur and, in one notable case, leverage personal information about an attacker to secure free decryption keys for a nonprofit organization. Topics discussed: The ransomware-as-a-service ecosystem where criminal affiliates can launch operations for $40-200 monthly subscriptions and achieve 10% success rates, generating millions in revenue. How Dark Web markets extend beyond stolen credentials to include zero-day vulnerabilities starting at $100,000, access broker services targeting specific organizations, and complete compromise kits for enterprise security tools. The organizational structures of criminal enterprises that mirror RICO-era mafia operations through loose affiliations rather than hierarchical control, making traditional law enforcement approaches ineffective. Negotiation psychology and tactics used in ransom discussions, including the business incentives that motivate threat actors to provide working decryption keys and maintain operational reputation. Financial models underlying cybercrime operations, including revenue sharing with affiliate programs, bonus structures for successful targeting, and the necessity of cryptocurrency laundering services. Market indicators for measuring criminal enterprise growth, including quarterly analysis of unique threat actor groups, highest ransom demands, and seasonal patterns in retail-focused attacks. Human intelligence gathering techniques using multiple personas and native language speakers to build long-term relationships within criminal communities for early warning capabilities. The economic realities that enable small criminal teams to generate substantial revenue while operating from countries where attacking American institutions is legally encouraged rather than prosecuted. Why technical compliance frameworks provide insufficient protection against adversaries who can purchase complete compromise capabilities for mainstream security technologies. Key Takeaways:  Implement human intelligence capabilities to complement technical security controls, recognizing that criminal innovation often outpaces defensive technology deployment. Understand the true economics of ransomware operations, where criminal affiliates can achieve substantial returns with minimal upfront investment through established service models. Prepare comprehensive incident response plans that include professional negotiation capabilities, legal frameworks for attorney-client privilege, and understanding of criminal psychology. Monitor Dark Web markets not just for credential exposure but for targeting intelligence, access broker activity, and the availability of compromise kits specific to your security stack. Establish relationships with specialized incident response firms before needing them, understanding that ransom negotiations require specific expertise and cannot be effectively handled internally. Focus security education on understanding adversarial capabilities and business models rather than solely on compliance requirements or singular technology solutions. Listen to more episodes:  Apple  Spotify  YouTube Website

Most security leaders are fighting yesterday's ransomware war while today's attackers have moved to data exfiltration and reputation destruction. Manisha Agarwal-Shah, Deputy CISO at McAfee, brings 18 years of cybersecurity experience from consulting through AWS to explore why traditional ransomware defenses miss the mark against modern threat actors. Her framework for building security teams prioritizes functional coverage over deep expertise, ensuring organizations can respond to crises even when leadership transitions occur. Manisha tells David how privacy regulations like GDPR actually strengthen security postures rather than create compliance burdens. She also shares practical strategies for communicating technical threats to C-suite executives and explains why deputy CISO roles serve organizational continuity rather than ego management. Her insights into ransomware evolution trace the path from early scareware through encryption-based attacks to today's supply chain infiltration and data theft operations.   Topics discussed: The evolution of ransomware from opportunistic scareware to sophisticated supply chain attacks targeting high-value organizations through trusted vendor relationships. Building security team structures that prioritize functional coverage across cyber operations, GRC, and product security rather than pursuing deep expertise in every domain. The strategic role of deputy CISO positions for organizational continuity and crisis leadership when primary security executives are unavailable or in transition. How privacy regulations like GDPR, HIPAA, and PCI DSS create security baselines that complement rather than conflict with proactive defense strategies. Communicating technical ransomware risks to non-technical executives through business impact frameworks and regular steering committee discussions. AI-driven behavioral anomaly detection capabilities for identifying unusual file encryption patterns and suspicious process activities before damage occurs. Comprehensive ransomware response planning including executive battle cards, offline playbook storage, and tested communication channels for network-down scenarios. The shift from encryption-based ransomware to data exfiltration and reputation damage attacks that bypass traditional backup and recovery strategies. Cloud security posture management implementations for organizations operating in hybrid on-premises and cloud environments. Data retention and minimization strategies that reduce blast radius during security incidents while maintaining regulatory compliance requirements.   Key Takeaways:  Document a comprehensive ransomware response plan that includes executive battle cards for each C-suite role and store it in offline, restricted locations accessible when networks are compromised. Test your ransomware playbook regularly with all key decision makers in simulated scenarios to ensure everyone understands their roles and responsibilities during actual incidents. Build security teams with functional coverage across cyber operations, GRC, and product security rather than pursuing deep expertise in every domain when resources are limited. Establish deputy CISO roles for organizational continuity and crisis leadership, ensuring someone can engage executives and coordinate incident response when primary leadership is unavailable. Communicate technical ransomware threats to non-technical executives through business impact frameworks that translate technical risks into financial and reputational consequences. Implement AI-driven behavioral anomaly detection systems that can identify unusual file encryption patterns and suspicious process activities before ransomware damage occurs. Deploy immutable backup solutions as one layer of defense, but recognize they won't protect against data exfiltration and reputation-based ransomware attacks. Leverage privacy regulations like GDPR, HIPAA, and PCI DSS as security baselines that provide data minimization, retention limits, and protection requirements. Create pre-established relationships with cyber insurance brokers, forensics providers, breach response teams, and public relations firms before ransomware incidents occur. Focus on cloud security posture management tools to identify misconfigurations and external exposures in hybrid cloud environments targeted by threat actors. Listen to more episodes:  Apple  Spotify  YouTube Website

Team Cymru's threat researchers have spent years developing an almost psychological understanding of cybercriminals, tracking their behavioral patterns alongside technical infrastructure to predict where attacks will emerge before they happen. Josh and Abigail share with David how their multi-year tracking of Russian cybercrime groups enabled critical contributions to Operation Endgame. Their work demonstrates how sustained intelligence gathering creates opportunities for law enforcement victories that reactive security cannot achieve. Drawing from Josh's eight years at Team Cymru and background in law enforcement national security investigations, and Abigail's specialization in Russian cybercrime tracking, they reveal how NetFlow telemetry provides unprecedented visibility into criminal operations. Their approach goes far beyond traditional indicator-based threat intelligence, focusing instead on understanding the human patterns that drive criminal infrastructure deployment and management. Topics discussed: The evolution of Team Cymru's threat research mission from ad hoc investigations to formalized self-tasking teams. How NetFlow telemetry enables upstream infrastructure mapping that reveals criminal backend systems invisible to traditional security tools. The behavioral analysis techniques that distinguish between different criminal operators based on work schedules, personal browsing habits, and infrastructure access patterns. Why collaboration between private sector researchers and law enforcement requires transparency and trust-building rather than hoarding intelligence behind restrictive sharing classifications. How Operation Endgame demonstrated the effectiveness of combining multiple organizational perspectives on the same threats, with each contributor providing unique visibility into different attack components. The measurement challenges in threat research success when outcomes depend on external decision-makers and sensitive operations may not publicly acknowledge private sector contributions. Why financially motivated threat actors are shifting from mass spray-and-pray campaigns to more targeted, higher-payout operations. How click-fix attacks exploit human psychology by convincing victims to execute malicious commands themselves. The dual-edged impact of AI on cybercrime, lowering barriers to entry for malicious actors while simultaneously enabling more sophisticated social engineering and automation capabilities. Why security awareness training must evolve beyond identifying typos and obvious phishing indicators to address AI-generated content and sophisticated impersonation techniques. Key Takeaways:  Build long-term tracking capabilities that focus on understanding threat actor behavior patterns rather than chasing individual indicators or campaigns. Implement NetFlow telemetry analysis to identify upstream infrastructure connections that reveal criminal backend systems before they're deployed operationally. Develop collaborative relationships with law enforcement and private sector partners based on transparency and shared mission objectives. Create threat research teams with self-tasking authority to focus on societally important threats rather than customer-driven priorities that may miss critical criminal activity. Establish behavioral profiling techniques that distinguish between different criminal operators based on work patterns, personal interests, and infrastructure access methods. Invest in sustained intelligence gathering capabilities that track threat actors across multiple campaigns and infrastructure changes over extended periods. Prepare for the increasing sophistication of click-fix attacks by educating users about command execution risks and implementing controls that detect suspicious copy-paste activities. Develop AI-aware security awareness training that addresses deepfake voice calls, sophisticated impersonation techniques, and realistic-looking malicious websites. Build measurement frameworks for threat research success that account for external decision-making timelines and sensitive operation requirements. Listen to more episodes:  Apple  Spotify  YouTube Website

Jonathan Jaffe, CISO at Lemonade, has built what he predicts will be "the perfect AI system" using agent orchestration to automate vulnerability management at machine speed, eliminating the developer burden of false positive security alerts. His unconventional approach to security combines lessons learned from practicing law against major tech companies with a systematic strategy for partnering with security startups to access cutting-edge technology years before competitors. Jonathan tells David a story that showcases how even well-intentioned people will exploit systems if they believe they won't get caught or cause harm, which has shaped his approach to insider threat detection and the importance of maintaining skeptical oversight of automated security controls. His team leverages AI agents that automatically analyze GitHub Dependabot vulnerabilities, determine actual exploitability by examining entire code repositories, and either dismiss false positives or generate proof-of-concept explanations for developers. Topics discussed: The evolution from traditional security approaches to AI-powered agent orchestration that operates at machine speed to eliminate false positive vulnerability alerts. Strategic partnerships with security startups as design partners, trading feedback and data for free access to cutting-edge technology while helping shape market-ready products. Policy-based security enforcement for cloud-native environments that prevents the need to manage individual pods, containers, or microservices through automated compliance checks. How legal experience prosecuting tech companies provides unique insights into adversarial thinking and the psychology behind insider threats and system exploitation. Implementation of AI vulnerability management systems that automatically ingest CVEs, analyze code repositories for exploitable methods, and generate proof-of-concept explanations for developers. Risk management strategies for adopting startup technology by starting small in non-impactful areas and gradually building trust through demonstrated value and reliability. Transforming security operations from reactive vulnerability patching to proactive automated threat prevention through intelligent agent-based systems. Key Takeaways:  Implement policy-based security enforcement for cloud environments to automate compliance across all deployments rather than managing individual pods or containers manually. Partner with security startups as design partners by trading feedback data for free access to cutting-edge technology while helping them develop market-ready products. Build AI agent orchestration platforms that automatically ingest GitHub Dependabot CVEs, analyze code repositories for exploitable methods, and dismiss false positive vulnerability alerts. Begin startup technology adoption in low-risk or non-impactful areas to build trust and demonstrate value before expanding to critical security functions. Establish relationships with venture capital communities to gain early access to portfolio companies and emerging security technologies before mainstream adoption. Apply healthy skepticism to security controls by recognizing that even well-intentioned employees may exploit systems if they believe they won't cause harm or get caught. Focus AI development efforts on automating time-intensive security tasks that typically require many days of manual developer work into machine-speed operations. Evaluate business risk first before pursuing legal or compliance actions by calculating whether the effort investment justifies potential outcomes and settlements. Listen to more episodes:  Apple  Spotify  YouTube Website

The security industry's obsession with cutting-edge threats often overshadows a more pressing reality: the vast majority of organizations are still mastering basic AI implementation. Vivek Menon, CISO & Head of Data at Digital Turbine, brings his insights from the RSA expo floor to share why the agentic AI security rush may be premature, while highlighting the genuine opportunities AI presents for resource-constrained security teams. Vivek shares with David how smaller organizations can leverage AI automation to achieve enterprise-level security capabilities without corresponding budget increases. His balanced approach to AI security threats demonstrates why defenders maintain strategic advantages over attackers, despite the expanded attack surface that dominates industry discussions.   Topics discussed: Why the agentic AI security market represents a classic "horse before the cart" scenario, with vendors solving problems for the 1% of enterprises building agents while 99% are still evaluating basic AI adoption. How the rush toward AI agents is forcing long-overdue conversations about non-human identity management, which lacks pace and scale in implementation. The strategic advantage defenders maintain in AI-powered security conflicts, leveraging time-based preparation capabilities while attackers face immediate success requirements with limited development windows. The dual nature of AI security impact, balancing genuine attack surface expansion against significantly enhanced defensive capabilities. Distinguishing between legitimate security innovation and buzzword-driven marketing, focusing on practical implementation readiness over theoretical capability demonstrations. How programmatic advertising technology companies navigate unique security challenges while maintaining operational efficiency in highly automated, data-driven business environments.   Key Takeaways:  Evaluate vendor AI solutions by asking what percentage of your industry actually uses the underlying technology before investing in security tools for emerging threats. Prioritize non-human identity management initiatives now, as the shift toward AI agents will expose existing gaps in identity governance at scale. Leverage AI automation to achieve enterprise-level security capabilities without proportional budget increases, especially for resource-constrained organizations. Adopt AI as a defensive accelerator rather than viewing it primarily as an attack surface expansion problem. Invest time in comprehensive threat protection strategies, capitalizing on defenders' advantage over attackers who must succeed immediately. Assess your organization's AI maturity before implementing agentic AI security solutions, ensuring you're solving actual rather than theoretical problems. Focus security budgets on mainstream technology threats affecting 99% of enterprises rather than cutting-edge solutions for the 1%. Listen to more episodes: Apple  Spotify  YouTube Website

Most organizations approach ransomware as a technical problem, but Steve Baer, Field CISO at Digital Asset Redemption, has built his career understanding it as fundamentally human. His team's approach highlights why traditional cybersecurity tools fall short against motivated human adversaries and how proactive intelligence gathering can prevent incidents before they occur. Steve's insights from the ransomware negotiation business challenge conventional wisdom about cyber extortion. Professional negotiators consistently achieve 73-75% reductions in ransom demands through skilled human interaction, while many victims discover their "stolen" data is actually worthless historical information that adversaries misrepresent as current breaches. Digital Asset Redemption's unique position allows them to purchase stolen organizational data on dark markets before public disclosure, effectively preventing incidents rather than merely responding to them. Topics discussed: Building human intelligence networks with speakers of different languages who maintain authentic personas and relationships within dark web adversarial communities. Professional ransomware negotiation techniques that achieve consistent 73-75% reductions in extortion demands through skilled human interaction rather than automated responses. The reality that less than half of ransomware victims require payment, as many attacks involve worthless historical data misrepresented as current breaches. Proactive data acquisition strategies that purchase stolen organizational information on dark markets before public disclosure to prevent incident escalation. Why AI serves as a useful tool for maintaining context and personas but cannot replace human intelligence when countering human adversaries. Key Takeaways:  Investigate data value before paying ransoms — many attacks involve worthless historical information that adversaries misrepresent as current breaches. Engage professional negotiators rather than attempting DIY ransomware negotiations, as specialized expertise consistently achieves 73-75% reductions in demands. Build relationships within the cybersecurity community since the industry remains small and professionals freely share valuable threat intelligence. Deploy human intelligence networks with diverse language capabilities to gather authentic threat intelligence from adversarial communities. Assess AI implementation as a useful tool for maintaining context and personas while recognizing human adversaries require human intelligence to counter. Listen to more episodes:  Apple  Spotify  YouTube Website

The cybersecurity industry has talked extensively about burnout, but Mark Alba, Managing Director of Cybermindz, is taking an unprecedented scientific approach to both measuring and treating it. In this special RSA episode, Mark tells David how his team applies military-grade psychological protocols originally developed for PTSD treatment to address the mental health crisis in security operations centers. Rather than relying on anecdotal evidence of team fatigue, they deploy clinical psychologists to measure resilience through validated psychological assessments and deliver interventions that can literally change how analysts' brains process stress. Mark walks through their use of the iRest Protocol, a 20-year-old treatment methodology from Walter Reed Hospital that shifts brain activity from amygdala-based fight-or-flight responses to prefrontal cortex logical thinking. Their team of five PhDs works directly within enterprise SOCs to establish baseline psychological metrics and track improvement over time, giving security leaders unprecedented visibility into their team's actual capacity to handle high-stress incident response. Topics discussed: Clinical measurement of cybersecurity burnout through validated psychological assessments including the MASLAC sleep index and psychological capital evaluations. Implementation of the iRest Protocol, a military-developed meditative technique used at Walter Reed Hospital for PTSD treatment. Real-time resilience scoring through the Cybermindz Resilience Index that combines sleep quality, psychological capital, burnout indicators, and stress response metrics. Research methodology to establish causation versus correlation between psychological state and SOC performance metrics like mean time to respond and incident response rates. Neuroscience of cybersecurity roles, including how threat intelligence analysts perform optimally at alpha brain wave levels while incident responders need beta wave states. Strategic staff rotation based on psychological state rather than just skillset, moving analysts between different cognitive roles to optimize both performance and mental health. Key Takeaways:  Implement clinical burnout measurement using validated tools like the MASLAC sleep index and psychological capital assessments rather than relying on subjective burnout indicators in your SOC operations. Deploy psychometric testing within security operations centers to establish baseline resilience metrics before incidents occur, enabling proactive team management strategies. Establish brainwave optimization protocols by moving threat intelligence analysts to alpha wave states for creative pattern recognition and incident responders to beta wave states for rapid decision-making. Correlate psychological metrics with traditional SOC performance indicators like mean time to respond and incident response rates to identify causation patterns. Rotate staff assignments based on real-time psychological capacity assessments rather than just technical skills, optimizing both performance and mental health outcomes. Measure psychological capital within your security team to understand cognitive capacity for handling high-stress cyber incidents and threat analysis workloads. Establish post-incident psychological protocols using clinical psychology techniques to prevent long-term burnout and retention issues following major security breaches. Create predictive analytics models that combine resilience scoring with operational metrics to forecast SOC team performance and proactively address capacity issues. Listen to more episodes:  Apple  Spotify  YouTube Website