Prabh Nair

Agentic AI is changing the way applications are designed, tested, deployed, and secured.Traditional application security focuses on APIs, authentication, authorization, databases, code, sessions, and technical attack surfaces.But Agentic AI introduces a different challenge.A user may not need technical knowledge to influence the system.A simple natural language prompt can make an AI agent classify intent, call a tool, retrieve data, generate a response, trigger a workflow, or influence a business decision.In this podcast episode, Prabh speaks with Akansha about Threat Modeling for Agentic AI Systems, using a practical customer support chatbot architecture as the case study.The architecture discussed includes:Classifier agentResponder agentQA reviewer agentHuman approval processRetrieval databaseTool integrationsLogging and monitoringRefund workflowThird-party integrationsThe session explains how a customer request flows through different agents, how intent is classified, how responses are generated, how refund requests are reviewed, and why human approval is important for high-risk financial actions.Content Reference https://github.com/smartdevil09/AI-Security-Professional-Roadmap/blob/main/AI%20security%20concepts/Threat%20Modelling%20Agentic%20Architecture.pdfLinkedin Profilehttps://www.linkedin.com/in/akesharwani/In this episode, we discuss:How Agentic AI differs from traditional application securityWhy prompts and natural language interactions create new risksWhy threat modeling should happen before production deploymentWhy stakeholder engagement is criticalHow to understand the business problem before identifying threatsHow to create an asset inventory for AI systemsHow to identify business assets and AI assetsHow to prepare data flow diagrams for multi-agent systemsHow to define trust boundaries between users, agents, tools, databases, and third partiesWhy refund workflows need stronger approval controlsWhy human approval is required for critical financial transactionsWhy logging and monitoring must be carefully designedHow to avoid logging sensitive PII dataHow attackers may exploit AI agents using prompt injectionHow AI agents may be manipulated into unauthorized actionsHow traditional AppSec controls still matter in Agentic AI systemsHow third-party Agentic AI systems should be assessedWhat documentation should be requested from vendorsHow to use STRIDE, MITRE ATLAS, OWASP LLM Top 10, CVE, and CWE for threat enumerationHow to evaluate likelihood, impact, business risk, and compliance riskWhy threat modeling must be continuously updated as architecture and threats changeAkansha also explains that threat modeling Agentic AI is not a simple automated checklist activity.It requires business context, stakeholder interviews, architecture understanding, asset inventory, data flow mapping, trust boundary analysis, risk assessment, guardrail design, logging, monitoring, validation, and continuous review.#AgenticAI #AISecurity #ThreatModeling #AppSec #AIGovernance #OWASP #MITREATLAS #CyberSecurity #GRC #CoffeeWithPrabh

Healthcare cybersecurity is not only about protecting networks, servers, applications, or medical devices.

Shantanu https://www.linkedin.com/in/shantanushastrish/In this podcast episode, Prabh speaks with Shantanu about healthcare cybersecurity, connected medical devices, hospital security, medical device threat modeling, security by design, cyber resilience, and AI in healthcare.Modern hospitals are now highly interconnected technology ecosystems. Patient monitors, scanners, ultrasound devices, laboratory systems, hospital applications, cloud platforms, networks, and AI-enabled tools exchange information to support faster diagnosis and better treatment decisions.But this connectivity also increases the cybersecurity risk.In healthcare, downtime is not only a business issue.Learn how healthcare cybersecurity protects connected medical devices from threats. Understand the core security measures hospitals use today.Healthcare cybersecurity is becoming a critical priority as hospitals integrate more digital infrastructure. In this discussion, Lead Cybersecurity Engineer Shantanu and CISO Prabh Nair break down the complexities of maintaining medical device security within modern hospital networks. They examine the specific technological advancements currently shaping the industry and the inherent risks that come with them.This conversation is essential for IT professionals and healthcare administrators looking to secure connected medical devices against evolving vulnerabilities. You will gain a clear perspective on the strategies required to implement robust hospital network security, ensuring patient safety remains the top priority. By analyzing these real-world security measures, you will be better equipped to identify potential gaps in your own organizational protocols.Subscribe for weekly cybersecurity breakdowns, and comment below on which healthcare security topic you want us to cover next.

AAISM exam preparation is not only about memorizing AI terms.It is about learning how to think like an AI security manager.In this session, I explains AAISM-style practice questions using a practical, manager-focused approach. The focus is on understanding how to choose the best answer when multiple options look correct.

The session starts with an AI loan approval case study and connects it with AI governance, AI risk management, AI technologies and controls, enterprise monitoring, and continuous improvement.The key message is simple:AAISM is about governance, risk, controls, evidence, and accountability.In this session, we cover:- How to approach AAISM questions- How to think like an AI security manager- Why governance comes before AI deployment- Why business risk comes before technology- Why AI inventory is required before risk categorization- How AI risk appetite and risk tolerance differ- How to choose controls based on risk- Why data governance is the foundation of AI security- How to handle bias, fairness, transparency, and explainability questions- Why human oversight matters for high-impact AI decisions- How to evaluate vendor AI risk- Why independent assurance matters for third-party AI platforms- How to identify AI exam traps- How to eliminate close distractors- How to connect AI risks with controls, owners, and evidence- How to answer questions on prompt injection, data poisoning, model inversion, model drift, hallucination, and deepfake risk- How to approach AI incident response automation questions- How to understand supervised, unsupervised, and reinforcement learning basics for the examThe most important exam mindset:AAISM Playlisthttps://www.youtube.com/playlist?list=PL0hT6hgexlYwHFcnBpXG2zuM7inotM0z3AAISM Domain 1https://www.youtube.com/watch?v=jb6tQppDPoE&t=2369sAAISM Domain 2https://www.youtube.com/watch?v=hyfIoSQH0vAAAISM Domain 3 https://www.youtube.com/watch?v=260RFZGgwCY&t=1423sDo not choose the most technical answer immediately.Choose the answer that best reduces risk, supports governance, creates accountability, provides evidence, and protects trustworthy AI outcomes.#AAISM #AISecurity #AIGovernance #CyberSecurity #GRC #RiskManagement #AICompliance #PrabhNair

In this podcast episode, Prabh speaks with David, a cybersecurity risk governance leader, about Enterprise Risk Management, GRC, risk appetite, risk tolerance, executive reporting, AI risk, and how to build a risk management program from scratch.David shares his first experience of building a risk management program in 2004 at a major Australian bank using ISO 17799, and explains why risk professionals must understand business objectives before applying any framework.Many organizations struggle with risk management because different teams use different definitions, different scoring methods, different language, and different assumptions.That is why David emphasizes the importance of building:Common risk languageAgreed definitionsClear governance levelsDecision-making authorityRisk ownershipBusiness-aligned impact and likelihood matricesOne-page executive risk summariesLinkedin Profilehttps://www.linkedin.com/in/vohradsky/In this episode, we discuss:How to build a risk management program from scratchWhy risk management must start with business objectivesWhy common language and agreed definitions matterHow risk appetite and risk tolerance should be explained to business teamsWhy scoping is critical before risk assessmentHow to understand business processes before identifying risksHow to collect relevant data about assets, processes, systems, and peopleHow to design impact and likelihood matrices for different organizational levelsWhy risk assessment should support decision-making, not only documentationHow to present risk to executives in language they understandWhy CFOs care about financial exposureWhy CEOs and boards care about strategic impactHow one-page summaries help executives take clear decisionsWhy accountability and decision points must be visibleWhat first artifacts can help when starting a risk programWhy a charter, risk taxonomy, and control profile are usefulHow AI risk management is changing GRC thinkingWhy cultural adoption is one of the hardest parts of risk managementWhat young GRC professionals should focus on to grow in this fieldDavid also shares an important career lesson for young GRC professionals:Do not remain limited to templates and control checklists.Understand one business process deeply.Work closely with business teams.Learn how they think, how they make decisions, and what uncertainty means for them.The key takeaway from this session is simple:Risk management is not only about documenting risk. It is about helping the business make better decisions in uncertainty.This episode is useful for:AAISM Playlisthttps://www.youtube.com/playlist?list=PL0hT6hgexlYwHFcnBpXG2zuM7inotM0z3GRC Interview Playlisthttps://www.youtube.com/playlist?list=PL0hT6hgexlYxM5P9v7aEYBTJl7iJyK2uKAI Practicalhttps://www.youtube.com/playlist?list=PL0hT6hgexlYwHLdZR_oHvEKN_8IiAMBcUISO 27001 Playlisthttps://www.youtube.com/watch?v=tvd1MUf3aHE&list=PL0hT6hgexlYys_9UWhal1kr9Gkz0ms0sM&pp=sAgC#EnterpriseRiskManagement #GRC #RiskManagement #CyberRisk #CISO #CyberSecurity #Governance #Compliance #AI Governance #CoffeeWithPrabh

In this podcast, Prabh speaks with Chinmay, who has tested more than 100 automated controls, to explain IT Application Controls using a practical payroll process case study.

https://www.linkedin.com/in/chinmaykulkarni22/https://chinmaykulkarni22.substack.com/Chinmay explains that application controls are automated actions within systems that help prevent or detect errors without manual intervention. Unlike IT General Controls, which are more standardized across applications, IT Application Controls are specific to a business process, system logic, workflow, configuration, and transaction flow.The biggest lesson from this session is simple:Do not start with a checklist. Start with the business risk.In this episode, we discuss:What IT Application Controls areDifference between ITGC and IT Application ControlsWhy application controls are specific to business processesHow payroll risks translate into application controlsInput validation controlsCalculation and processing controlsInterface controlsOutput controlsAuthorization workflow controlsData validation controlsITGC dependency for application controlsHow SOC reports support third-party control relianceHow to test automated controlsWhy production screenshots and configuration evidence matterWhen one sample may be enough for fully automated controlsHow to prepare a lead sheet for application control testingWhy auditors must understand risk before testing controlsPlaylisthttps://www.youtube.com/watch?v=gaClcfhfWFM&list=PL0hT6hgexlYyNWBcGYfabwumCr0GKmLWv&pp=sAgChttps://www.youtube.com/watch?v=mq_vSLHm4r0&list=PL0hT6hgexlYztA41j1bceTfVagP9mtq28&pp=sAgCChinmay also walks through a practical lead sheet structure covering risk statements, walkthrough details, automated control descriptions, trigger types, reference data, attributes, configuration inspection, and testing scenarios.#ITAudit #ITGC #ApplicationControls #GRC #SOX #Audit #CyberSecurity #Big4 #CoffeeWithPrabh

AI is moving from simple human-to-system interaction to agentic AI, where machines interact with other machines, take actions, exchange data, and influence business decisions.This creates a major challenge for cybersecurity, GRC, audit, compliance, and assurance professionals:

Priyank Sonihttps://www.linkedin.com/in/priyank-soni-iima/How do you audit an AI system when you cannot fully see the model, logic, architecture, or internal decision-making process?In this podcast, Prabh speaks with Priyank Soni, a cybersecurity, AI/ML, digital trust, governance, and assurance leader, about auditing AI systems in critical sectors.Priyank explains why traditional audit approaches are not enough when AI systems become black boxes, especially in sectors where trust, safety, compliance, and accountability matter.In this episode, we discuss:Why AI audit is becoming important in critical sectorsHow AI is moving toward agentic and machine-to-machine interactionsWhy zero-trust architecture must evolve for AI agentsWhy AI systems require stronger documentation and evidenceHow ISO/IEC 42001 is shaping AI governance and audit expectationsWhy auditors must understand data flow, model behavior, and system boundariesHow to audit black box AI systemsWhy AI audits should start with inventory and classificationWhy data mapping is critical for AI assuranceHow to assess AI vendor and supply chain riskWhy SBOM and ABOM may become important for AI system auditsHow to handle trade secret challenges when vendors do not share model detailsWhy auditor, vendor, and internal team collaboration is requiredWhat performance metrics auditors should reviewHow to test bias, fairness, and reliabilityWhy adversarial input testing mattersWhy human oversight must be validated, not just mentioned in policyWhy AI systems need continuous monitoring after deploymentWhy AI audits may need to happen more frequently than traditional IT auditsPriyank also explains that AI auditing is still in an early maturity phase. Many organizations, vendors, and auditors are learning together. That makes documentation, risk assessment, monitoring, and evidence collection even more important.#AIAudit #AIGovernance #ISO42001 #AISecurity #CyberSecurity #GRC #DigitalTrust #ResponsibleAI #CriticalInfrastructure #VendorRiskManagement #CoffeeWithPrabh

AI adoption is accelerating across enterprises, but most security programs were not designed for the speed, scale, and complexity of AI-driven threats.In this CISO Masterclass episode, Prabh speaks with Agnidapta Sarkar, a seasoned cybersecurity evangelist and digital resilience strategist, about how CISOs must evolve their security programs for the AI era.Agni explains why organizations must first understand their digital assets, business impact, material risk, and enterprise architecture before rushing into AI adoption or AI security controls.The discussion goes deep into why traditional visibility-focused security is no longer enough. Modern attackers increasingly use valid credentials, legitimate tools, automation, and faster attack paths. With AI, the challenge becomes even more serious because attacks can happen with greater speed, scale, and depth.In this episode, we discuss:* How CISOs should evolve their security programs for AI threats* Why architecture must come before governance* Why organizations must map digital assets to business impact* How AI changes the speed, scale, and complexity of attacks* Why identity is becoming one of the biggest attack targets* Why Zero Trust needs practical implementation, not just discussion* The role of enhanced identity governance* How micro-segmentation reduces blast radius* Why software-defined perimeters matter in modern defense* Why AI agents need the same access controls as human users* Why proactive governance must monitor ongoing access, not only initial approval* How CISOs should think about resilience before a breach happens* Why incident learnings must feed back into architecture and governance improvementAgni also explains why many organizations struggle with AI security because they do not fully understand their business problems, data flows, access paths, and architectural weaknesses.This episode is highly useful for CISOs, security leaders, enterprise architects, GRC professionals, cyber risk managers, IAM professionals, SOC leaders, AI governance teams, and board-level cybersecurity stakeholders.The key message from this conversation is simple:Before AI governance can succeed, enterprise architecture must be understood, controlled, and resilient.Watch the full episode and comment below:What should CISOs fix first in the AI era — architecture, identity, governance, or resilience?Subscribe for more CISO Masterclass episodes, AI security discussions, cybersecurity leadership insights, GRC content, and practical enterprise security conversations.#aisecurity #ciso #infose #aigovernance

In many organizations, OT security is still discussed at a very high level. But when we go into the real world, the challenge is different:How do we actually assess cyber risk in an OT environment where safety, uptime, legacy systems, plant operations, and business impact all come together?

In this session, Sajath walked through a very practical approach to OT cybersecurity risk assessment — not just theory, but how to think through:OT asset identificationBusiness and operational impactThreat scenariosVulnerability and exposureLikelihood and impact scoringRisk matrix creationSafety and reputational impactControl prioritizationPractical documentation for decision-makingWhat I really liked about this discussion was the focus on practical risk thinking.OT cybersecurity is not only about firewalls, segmentation, or compliance checklists. It is about understanding what can stop operations, affect safety, damage reputation, or create real business disruption.A big thank you to Sajath Sathar for sharing his experience and making the session highly practical for learners and professionals Shivhttps://www.youtube.com/watch?v=qjJvK7nB3VI&t=1047s&pp=ygURT1QgU0VDVVJJVFkgUFJBQkg%3DOT Security Program with Manjunathhttps://www.youtube.com/watch?v=nSyAmYgtWeg&t=340s&pp=ygURT1QgU0VDVVJJVFkgUFJBQkg%3DHow to Build OT Security https://www.youtube.com/watch?v=XDA0QGC1W_s&t=3s&pp=ygURT1QgU0VDVVJJVFkgUFJBQkg%3D#OTSecurity #ICSSecurity #CyberSecurity #RiskAssessment #IEC62443 #GRC #IndustrialCyberSecurity #Podcast #PrabhNair #InfosecTrain

In this special cybersecurity podcast episode, Prabh interviews Sarang, a seasoned cybersecurity expert popularly known as “Cyber Insane,” to discuss practical red teaming, enterprise attack simulations, web application security, and real-world attack kill chain thinking.

https://www.linkedin.com/in/sarang-tumne-cyber-insane-a1681827/https://m.youtube.com/@redteamgarage-rtg?ra=m📚 RTG – Practical Red Teaming Book copies are now available!✅ Physical Book: ₹899 (Free delivery across India)✅ PDF Copy: ₹499 (Instant download)🎁 Special for Prabh’s community: Get 15% OFF using coupon code: RTG15📩 DM for physical and PDF copies at +91 9137495772📖 Amazon Kindle Edition (₹499):https://amzn.in/d/0bvHeFaM📖 Google Books Edition (₹499):https://books.google.co.in/books/about/Practical_Red_Teaming_Field_Tested_Strat.html?id=4L_rEAAAQBAJ&redir_esc=y⚠️ Coupon code is applicable only for physical/PDF copies and not for Kindle or Google Books editionsThis session goes beyond theory. Sarang explains how red teamers think, how enterprise attacks are planned, and why organizations must go beyond basic vulnerability scanning and traditional penetration testing.

Are you interested in bug bounty hunting but confused about where to start?In this podcast session, Prabh speaks with Monish about the real beginner roadmap for learning bug bounty, web security, XSS, SQL injection, Burp Suite, vulnerability reporting, and practical web application testing.This session is designed for beginners who want to learn bug bounty the right way. Instead of directly jumping into advanced tools and random payloads, Monish explains why every beginner must first understand how websites actually work.Before you start hunting bugs, you need to understand the basics of HTML, CSS, JavaScript, HTTP requests and responses, cookies, browser developer tools, frontend logic, backend logic, databases, authentication, sessions, and website technology stacks.Monish explains how these foundations help you understand real vulnerabilities like Cross-Site Scripting XSS, SQL Injection, misconfigurations, broken access control, and other common web security issues.The discussion also covers how beginners can use platforms like W3Schools, Juice Shop, OWASP practice labs, PortSwigger Web Security Academy, TryHackMe, Hack The Box, HackTricks, and Burp Suite to build practical skills in a safe and legal way.One of the most important parts of this episode is the discussion on why many bug bounty reports get rejected. Monish explains common mistakes such as submitting duplicate vulnerabilities, depending only on automated scanners, using AI without understanding the finding, missing business impact, weak proof of concept, and losing patience too early.This video is useful for cybersecurity beginners, bug bounty learners, web security students, ethical hacking aspirants, penetration testing beginners, college students interested in cybersecurity, and anyone who wants to learn bug bounty legally and practically.Bug bounty is not about randomly running tools. It is about understanding applications, finding real security impact, documenting evidence properly, and reporting vulnerabilities responsibly.Watch the full session and comment below with the next bug bounty topic you want Monish and Prabh to cover.Subscribe for more practical cybersecurity podcasts, bug bounty learning, ethical hacking guidance, web security training, SOC content, GRC insights, and real-world career advice#BugBounty #EthicalHacking #WebSecurity #CyberSecurity #PenetrationTesting