Future of Threat Intelligence

Deepfakes have moved well past the uncanny valley and into active threat operations, and Tom Cross, Head of Threat Research at GetReal, has the client-side case studies to back it up. Tom explains how North Korean IT worker infiltration campaigns have transformed HR and video conferencing from administrative functions into active attack surface, albeit one that most security teams aren't monitoring, logging, or ingesting into their SIEM.Drawing on a long-running collaboration with a former West Point professor and intelligence officer, Tom also applies the military framework of tactical, operational, and strategic intelligence to cybersecurity, arguing that most CTI programs are really just lists of burned indicators. The actual value of IOCs, he contends, is retrospective: discovering you were communicating with a known-bad actor means you may still be compromised. He makes the case for connecting adversary intent models, red team findings, and vulnerability data into a unified predictive picture. YT Thumbnail title: Your Zoom Call Is an Attack SurfaceTopics discussed:How North Korean IT worker infiltration has converted HR processes and video conferencing into an active, unmonitored attack surfaceVoice-cloned peer impersonation via messaging apps, followed by deepfaked video calls and malware deliveryWhy deepfake audio attacks on IT help desk credential reset processes are among the most likely near-term vectorsBiometric indicators of compromise and the significant false-positive risks that distinguish them from traditional IP or domain IOCsHow the military intelligence framework of tactical, operational, and strategic analysis applies to CTI programsThe strategic importance of retrospective IOC analysis versus forward-looking ingestionWhy DPRK's financial motivation model expands their target set far beyond what traditional nation-state threat modeling would predictKey Takeaways: Ingest video conferencing logs into your SIEM.Audit your remote credential reset process for social engineering resistance.Map red team findings and vulnerability data to specific adversary profiles rather than treating them as a generic remediation backlog.Implement retrospective IOC analysis alongside forward-looking blocking.Treat DPRK's financial motivation as an equalizer when assessing APT exposure.Build threat intelligence at the strategic layer by modeling adversary intent and objectives, not just cataloging observed TTPs.Apply extra care to biometric IOC sharing.Monitor employee working-hour patterns against claimed time zones as a behavioral indicator of potential employment fraud.Extend IOC taxonomy to include multimedia and biometric formats.Listen to more episodes: Apple Spotify YouTubeWebsite

Vincent Passaro, Engineering Manager at Stripe Security, didn't get there through a slide deck or a company mandate. He got there through a shower thought that followed a conversation with a friend, and it broke how he'd been thinking about building, leading, and even measuring his own team.The reframe was simple and did not start with "we're all going to be software developers. Rather, "we're going to be product owners." That single pivot changed everything downstream, including how he approached prototyping, how he set success criteria for agents, and how he coached his team out of chasing bugs and into defining outcomes.In this episode, Will and Vince trace both of their "pin drop" moments: the specific conversations that shifted their mental models, then try to articulate what that shift actually means for CTI analysts and security engineers working real problems today.They talk about what it felt like to stop asking "how do I wire this" and start asking "what does success look like," and how fast things moved once that happened. They're honest about what breaks, like the siloed tools that don't talk to each other, the governance vacuum that opens when every analyst is shipping products, and the dopamine trap of adding features instead of finishing work. And they're equally direct about what becomes possible when outcome velocity: not headcount or tooling budget, and what becomes the competitive edge.This isn't a conversation about AI hype. It's about what happens when two practitioners who've spent years operating the plumbing realize the plumbing has been commoditized and what that means for where human judgment actually matters now.If you've been waiting for the right moment to pay attention, this is probably the episode where you stop waiting.Topics Discussed"Product owner" vs. "developer" mindset and why it changes how analysts build toolingDefining outcome criteria upfront as the core discipline for AI-assisted developmentHow AI collapses experimentation costs and eliminates dev team dependencyAnalyst-owned toolkits and outcome velocity as a competitive edge for small teamsThe governance risk: product silos, duplicated tooling, and inconsistent standardsFT3 as an open-source framework built to lower the community contribution barrierWhy CISO/board resistance to AI on security grounds will backfireThreat actors are scaling the same way — analyst adaptation is the necessary responseKey Takeaways: The unlock isn't learning to code: it's learning to think backwards from the outcome. Define what success looks like, set the criteria the agent has to meet before it moves on, and stop micromanaging the implementation. That's the product owner shift.Slow down before you build. Spend more time in planning than in execution using deep research across multiple models, comparing outputs, stress-testing the concept before a single line gets written.Drop the subscription and treat the model like a teacher, not a tool. Start with a problem you already understand. Ask it to walk you from zero to fluent. It will tell you to stop thinking like a developer and start thinking like a product owner. If you have a backlog of problems you gave up on because they weren't staffable, go find them. The feasibility question that used to take months to answer now takes an afternoon. Start there.Before your next team planning cycle, map what everyone is building. The duplicate tools are already being written in parallel by people who don't know about each other. Get ahead of it now, because it only compounds.If you're involved in open-source threat intel frameworks, the contribution problem was never motivation, it was friction. The tooling gap is closable. Build the on-ramp and the community will use it.Listen to more episodes: Apple Spotify YouTubeWebsite

What happens when a DPRK IT worker operation lands inside one of your clients, and the three-letter agency you call says they can't show up? Duaine Labno, Director of Special Investigations & Threat Intelligence at TIG Risk Services, walks through exactly that case: his team built a ruse to recover the compromised laptop, staged a physical handoff at corporate HQ, filmed the courier, ran his plates, and traced him to multiple properties. This produced the kind of ground-level intelligence the FBI told him they'd never seen before in a US-based DPRK case. Duaine explains why digital and physical investigations have to run in parallel from day one, not handed off sequentially, and what that looks like operationally when federal resources don't materialize. He also breaks down how post-COVID remote hiring processes that are speed-optimized gave adversaries a repeatable entry point, and why an untrained recruiter doing a soft document check is now a meaningful attack surface for corporate networks.YT Thumbnail title: Remote Hiring Broke Your Security PerimeterTopics discussed:How post-COVID remote hiring processes relaxed identity verification standards and created repeatable enterprise network entry points Running parallel digital and physical investigations simultaneously when tracking identity fraud and insider threatsUsing open-source intelligence and proprietary threat monitoring software to scan millions of data points for suspect behavioral patternsExecuting a live DPRK IT worker case using physical surveillance, a document ruse, and plate runs to identify a U.S.-based operatorWhy untrained recruiters conducting soft document checks have become a meaningful attack surface in corporate hiring pipelinesHow adversaries are weaponizing AI for voice alteration, deepfakes, and document manipulation to bypass hiring and KYC verification processesThe case for vetted, secure cross-industry intelligence sharing platforms to close gaps that individual organizational silos leave openWhere cyber threat intelligence trails end and physical investigation must pick up to produce actionable, court-ready evidenceKey Takeaways: Treat remote hiring pipelines as an active attack surface by pulling security, legal, and HR into the process.Train recruiters to recognize fraudulent identity documents as a first line of defense against adversarial infiltration of corporate networks.Run digital and physical investigations in parallel from the start rather than waiting for cyber analysis to conclude.Build contingency plans for federal non-response into any investigation involving foreign threat actors.Deploy threat monitoring software capable of scanning open-source data at scale to surface behavioral patterns and connections.Establish vetted, secure intelligence sharing relationships with peer organizations and law enforcement to close the visibility gaps.Pressure-test AI-assisted hiring tools against deepfake and voice alteration scenarios before deploying them.Listen to more episodes: Apple Spotify YouTubeWebsite

When Matt McKnew, Senior Manager of Incident Response at Thermo Fisher,  tracked down the Nimda worm in 2001 by analyzing packet captures to identify NetBIOS saturation patterns, threat actors weren't trying to get paid; they were causing disruption. Today, he's defending against ransomware groups that operate like businesses, complete with service models and affiliate networks. Matt explains why Clop's acquisition of six zero-days puts them in APT territory regardless of financial motivation, how attackers now hide in the noise of criminal operations making nation-state activity harder to detect, and why the North Korean IT worker scam succeeds by exploiting weak hiring processes rather than technical vulnerabilities. Topics discussed:Responding to the Nimda worm using packet capture analysis to identify NetBIOS saturation patterns across satellite ISP infrastructureBuilding trusted peer networks for crowdsourcing threat intelligence during active incidents rather than relying solely on formal feedsAnalyzing Clop ransomware's acquisition of six zero-days as evidence of APT-level sophistication despite purely financial motivationImplementing structured incident response documentation and processes to enable faster recovery and more nimble responseEvaluating nation-state threat actors by understanding their 5-year strategic plans and objectives rather than mapping everything to MITRE ATT&CKDeploying agentic AI to standardize analyst work products and maintain consistent intelligence delivery across global security teamsExamining North Korean IT worker infiltration campaigns that exploit weak HR and recruitment processesDifferentiating financially-motivated ransomware operations from nation-state APT campaigns while recognizing blurred lines in TTPsKey Takeaways: Document incident response procedures upfront with standardized policies to reduce response time during active security incidents.Build trusted peer networks across industry for crowdsourcing threat intelligence when formal feeds lack critical real-time information.Evaluate ransomware groups for APT-level capabilities when they acquire multiple zero-days regardless of their financial motivations.Research adversary 5-year strategic plans and national objectives to understand nation state threat actor targeting.Deploy agentic AI systems to standardize analyst work products and maintain consistent intelligence delivery formatting.Strengthen HR and recruitment processes with technical screening questions to defend against North Korean IT worker infiltration.Maintain curiosity and interrogate suspicious indicators until they make complete sense rather than accepting surface-level explanations.Recognize that attackers leverage the same automation and AI capabilities defenders use, requiring equivalent adoption to maintain defensive parity.Listen to more episodes: Apple Spotify YouTubeWebsite

Running CTI at a cyber insurance carrier and across more than tens of thousands of companies forces a triage discipline most programs never need to build. Alex Bovicelli, Senior Director of Threat Intelligence at Tokio Marine HCC, describes how his team scaled by narrowing focus to one thing: the initial access vectors threat actors are actually using right now: not CVSS scores, not spray-and-pray alerts, but underground forum activity, access broker behavior, and credential exposure from info stealer logs that most SMBs have zero visibility into. When a detection fires, his team doesn't just notify, they walk the customer through remediation and confirm the issue is closed, because for a company relying on an MSP with no internal security staff, an alert without support is just noise.The more pointed conversation is about what's not making headlines: thousands of SMBs are getting hit by ransomware every year, and groups like Akira have built a business model specifically around it; high volume, low ransom, staying below the threshold that triggers serious law enforcement attention. Alex explains how those attacks succeed not through sophisticated tradecraft but through SSL VPN brute forcing tools left running unattended, returning thousands of valid credentials against organizations that have no account lockout policies, no MFA on remote access, and no way to know their credentials are already in a log collector somewhere. Topics discussed:Building intelligence-led CTI programs at scale by anchoring detection on initial access vectors, access broker activity, and credential exposureUsing underground forum proximity and info stealer log correlation to identify compromised credentials across thousands of organizationsOperationalizing pre-claim threat intelligence within cyber insurance to eradicate initial access before events generate claimsClosing the alert-to-remediation loop for SMBs by delivering detection, support, and mitigation confirmation as a single workflowHow Akira and similar ransomware groups deliberately target SMBs with high-volume, sub-threshold attacks Rethinking CVSS-based patching prioritization by incorporating criminal exploitability and at-scale attack frequency into triageSeparating AI as an intelligence producer from AI as a report summarizer, where automation could realistically drive patching priorityWhy most external threat feeds leave CTI teams in a retroactive posture, and how incident response data from insurance claims changes thatKey Takeaways: Anchor your CTI program on initial access vectors rather than trying to cover every vulnerability class across your environment.Monitor access broker activity and underground forums to understand which threat actors are actively buying and selling against your industry or infrastructure.Integrate info stealer log analysis into your detection pipeline to identify compromised credentials before threat actors use them for lateral movement or ransomware deployment.Shift your patching prioritization model away from CVSS scores and toward criminal exploitability.Design alerts for smaller IT teams to be remediation-ready on receipt because an alert without a clear next step will not get acted on.Close the loop on every detection by confirming mitigation was completed, not just that the alert was acknowledged.Enforce account lockout policies and MFA on all SSL VPN and remote access entry points as a baseline control.Assess AI tooling for your CTI program on whether it can produce intelligence rather than just consume it through report summarization.Use incident response data from post-claim analysis to validate your pre-claim detection signals.Listen to more episodes: Apple Spotify YouTubeWebsite

Daniel Woods, Principal Security Researcher, and his team at Coalition analyzed forensic reports across their 100,000-policyholder base and found 50% of ransomware incidents begin with VPN or firewall exploits. But here's the twist: 40-60% of those aren't vulnerability exploits at all, they're stolen credentials bypassing perimeter devices entirely. Organizations running Cisco ASA devices show 5x higher claim rates than peers, with similar patterns across Fortinet, SonicWall, and Citrix SSL VPNs. When threat actors do exploit vulnerabilities, they're scanning and deploying shells within 24-48 hours of public disclosure, making your 72-hour patch SLAs dangerously obsolete.Daniel also surfaces the gap between security control theory and organizational reality. Microsoft claims 99.9% MFA effectiveness for individual Azure accounts, but insurance claims data shows no measurable risk reduction at the organizational level because that one service account without MFA, that legacy API integration nobody knew was enabled, or that exec who refused to enroll gives attackers everything they need. Organizations deploying threat-based training focused on social engineering tactics beyond phishing see measurably lower claim rates, suggesting we've been training for the wrong threat surface.Topics discussed:Analyzing cyber insurance claims data from 100,000 policyholders to identify which security controls actually reduce incident ratesUnderstanding why perimeter security devices like Cisco ASA, Fortinet, and SonicWall VPNs show 5x higher claim rates in insurance dataExamining the 40-60% of edge device breaches caused by stolen credentials rather than vulnerability exploitsClosing the gap between Microsoft's 99.9% individual MFA effectiveness claims and zero measurable organizational risk reductionRevealing security awareness training effectiveness through a study showing 2% phishing failure reduction versus threat-based training Comparing email security platforms where Google Workspace shows lower claims rates than Office365 due to included-by-default security featuresImplementing a zero-day alert service that notifies policyholders within hours when vulnerable perimeter devices need immediate patchingRethinking security awareness training as role-specific, finite courses targeting job risks rather than repetitive generic phishing exercisesKey Takeaways: Audit your external perimeter for exposed Cisco ASA, Fortinet, SonicWall, and Citrix SSL VPN devices.Implement hardware-based MFA enforcement across all services including legacy APIs and service accounts to close credential theft gaps.Reduce patch SLAs from 72 hours to under 24 hours since threat actors scan and deploy shells within 24-48 hours of vulnerability disclosure.Migrate email infrastructure to cloud-hosted platforms like Google Workspace that include security features by default.Replace repetitive generic phishing training with role-specific threat-based courses focused on social engineering tactics.Scan your policyholder or customer base for vulnerable perimeter devices using external scanning services to notify before exploits occur.Build identity management architecture around centralized services with hardware token enforcement.Evaluate security control effectiveness using multiple data sources rather than vendor claims alone.Listen to more episodes: Apple Spotify YouTubeWebsite

Stripe's 3-person intel team created FT3 (fraud tools, tactics & techniques), a framework modeled after MITRE ATT&CK but purpose-built for financial fraud, to eliminate the communication breakdown where "fraud" required constant reverse engineering. The structured taxonomy now powers both analyst workflows and automated fraud systems operating at transaction-millisecond speeds, with technique-based tagging that gives fraud engines the context to make informed decisions without human interpretation of vague "fraudulent" alerts.Vincent Passaro, Engineering Manager at Stripe Security, walks through their shift from reactive blocking to building infrastructure targeting packages for law enforcement prosecution. By mapping card testing, account takeovers, and money movement techniques across the full attack chain, the team now produces actionable intelligence packages. The framework drives LLM-powered classification of legacy incident reports, threat-informed red team testing by automatically mapping techniques to API capabilities, and standardized intelligence sharing with financial institutions. YT Thumbnail title: Technique Tagging at ScaleTopics discussed:Creating FT3 framework modeled after MITRE ATT&CK to establish standardized fraud technique taxonomyTransitioning from AWS tier-3 incident response to financial fraud intelligence while applying cloud security methodologiesBuilding infrastructure targeting packages that map adversary infrastructure roles for law enforcement prosecutionScaling small teams through technique-based tagging that enables fraud systems to make decisions at millisecond transaction speedsLeveraging LLMs for automated classification of historical incident reports and mapping fraud techniques to API endpoint capabilitiesIntegrating threat intelligence with red team and fraud operations to create threat-informed testing roadmaps prioritized by business impactKey Takeaways: Build fraud-specific taxonomies to eliminate communication gaps where "fraud" requires constant reverse engineering.Map fraud techniques across the full attack timeline for complete adversary behavior visibility.Create infrastructure targeting packages that identify adversary server roles and network diagrams for prosecution-ready intelligence sharing.Leverage LLMs with fraud technique context to automatically classify historical incident reports and identify new techniques.Use API documentation and fraud frameworks together with LLMs to generate threat-informed red team testing roadmaps.Prioritize threat actor tracking based on business impact and platform prevalence rather than defaulting to nation-state actors or compliance checklists.Integrate threat intelligence, red team, and fraud operations under unified leadership to enable rapid validation of observed techniques.Design fraud frameworks with extensive contextual documentation to enable adoption by non-security teams and facilitate machine-readable intelligence sharing across organizations.Listen to more episodes: Apple Spotify YouTubeWebsite

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.