Podcast
InfosecTrain
Hosted by InfosecTrain · EN
InfosecTrain is one of the finest Security and Technology Training and Consulting organization, focusing on a range of IT Security Trainings and Information Security Services. InfosecTrain was established in the year 2016 by a team of experienced and enthusiastic professionals, who have more than 15 years of industry experience. We provide professional training, certification & consulting services related to all areas of Information Technology and Cyber Security.
Website: https://www.infosectrain.com
74episodes
Episodes
Newest firstAll episodes
AI Powered SOC Analyst Roadmap 2026-27
4d ago01:12:42Tap to summarizeThe future of cybersecurity isn't just faster detection - it's AI that predicts, investigates, and responds before attackers succeed. In this masterclass episode, InfosecTrain breaks down how AI is revolutionizing Security Operations Centers (SOCs) through intelligent threat triage, automated investigations, and SIEM log analysis.The "course titled" SOC Analyst Training Program accelerates your career in modern AI-driven cyber defense.📘 What You’ll Learn:SOC Fundamentals: Building a solid foundation in core Security Operations Center processes, roles, and workflows.AI-Driven Threat Detection: Integrating machine learning algorithms to automate triage and reduce alert fatigue.SIEM & AI Log Analysis: Leveraging intelligent analytics across SIEM tools like Splunk and Elastic to uncover hidden threats faster.Automated Incident Response: Combining threat intelligence feeds with automated playbooks for rapid breach containment.The 2026 Career Roadmap: Step-by-step guidance, certification paths, and practical hands-on strategies to become a modern SOC analyst. 🎧 Essential listening for SOC analysts, incident responders, blue teamers, and aspiring cybersecurity professionals looking to master AI-enhanced security operations.Watch full episode here: https://www.youtube.com/watch?v=WM6FlGifOoM
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Securing AI Systems Attack Surfaces & Defenses | Part - 2
5d ago00:46:49Tap to summarizeSecuring AI extends beyond immediate code patches - it demands structured governance, continuous auditability, and clear career specializations. In Part 2 of this masterclass series, InfosecTrain breaks down AI compliance frameworks, regulatory readiness, evidence collection, and tailored learning paths.The "course titled" Practical AI Security Engineering Program helps architects build resilient AI controls.Listen Part - 1 here: Securing AI Systems Attack Surfaces & Defenses | Part - 1📘 What You’ll Learn:AI Security Governance: Implementing structured compliance frameworks to ensure continuous auditability across enterprise AI implementations.Evidence Collection & Audit Readiness: Gathering verifiable technical artifacts to satisfy evolving AI regulations and internal risk thresholds.Accountability & Responsible Use: Establishing clear ownership metrics for AI outcomes across developers, security teams, and executive stakeholders.Role-Based Learning Pathways: Navigating specialized roadmaps designed for security engineers, system architects, auditors, and GRC leads.Career Transition Strategies: Skills and credentials needed to transition into high-demand AI security engineering and oversight roles.🎧 Essential listening for security engineers, auditors, GRC leads, AppSec teams, and tech leaders building structured AI defense programs.Watch Part - 1 here: https://www.youtube.com/watch?v=iwaTgPD9h1AWatch Part -2 here: https://www.youtube.com/watch?v=gNmBaDq1teQ
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Securing AI Systems Attack Surfaces & Defenses | Part - 1
6d ago01:32:51Tap to summarizeAI systems represent the new digital attack surface. As organizations deploy complex models, securing the underlying architecture is critical. In this masterclass episode, InfosecTrain breaks down the full AI security lifecycle, from threat modeling to deploying practical defenses against machine learning and LLM exploits.The "course titled" Practical AI Security Engineering Program provides hands-on expertise to defend your AI pipelines.📘 What You’ll Learn:Foundations of AI Security: Mapping out unique AI attack surfaces, threat modeling approaches, and fundamental security controls.Exploiting AI Vulnerabilities: Real-world breakdown of how adversaries target machine learning models, LLMs, and autonomous agentic AI workflows.Defending AI Pipelines: Applying end-to-end security controls across data pipelines, model training environments, and production endpoints.LLM & AppSec Safeguards: Securing generative AI applications against prompt injections, data poisoning, and model inversion attacks.Governance & Responsible Adoption: Integrating risk frameworks to support secure, compliant, and scalable enterprise AI deployment.🎧 Essential listening for security engineers, AppSec teams, AI developers, SOC analysts, and GRC leaders building next-generation AI defenses.Watch Full video here: https://www.youtube.com/watch?v=iwaTgPD9h1A
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AI-Powered Cloud Security for Engineers
1w ago01:10:23Tap to summarizeAI is changing cloud infrastructure, but how do you secure AI-assisted workflows? In this episode of InfosecTrain TechTalks: Real World Decoded, host Payal Pawar sits down with Cloud Architect Chitra Nair to discuss AI-powered cloud security.The "course titled" AWS Certified Solutions Architect Associate Training helps engineers master secure cloud design. 📘 What You’ll Learn:AI-Assisted Automation Risks: Balancing rapid cloud deployment automation with strict security and governance boundaries.Tackling Cloud Misconfigurations: How machine learning tools detect and remediate infrastructure-as-code errors across AWS, Azure, and GCP.Identity & Access Management: Securing service accounts, API tokens, and AI agents within complex Kubernetes and Terraform environments.DevOps to DevSecOps: Embedding AI-driven security checks directly into modern CI/CD pipelines without slowing down deployments.Maintaining Cloud Compliance: Leveraging automated governance monitoring to meet global regulatory requirements across multi-cloud setups.🎧 Essential listening for cloud engineers, DevOps practitioners, security architects, and infrastructure leads navigating the AI security era.Watch Full episode here: https://www.youtube.com/watch?v=_58rAy159yI
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Mastering AAISM: The AI Security Leader Blueprint
2w ago00:43:39Tap to summarizeAI is transforming cybersecurity, but who is securing the AI? Organizations urgently need leaders to manage AI security, governance, and risk. In this episode of TechTalks, InfosecTrain breaks down why the ISACA Advanced in AI Security Management (AAISM) credential is fast becoming essential for modern security leaders. 📘 What You’ll Learn:Why AI Security Leadership Matters: Understanding the shift from reactive IT defense to strategic, enterprise-wide AI risk oversight. The AI Threat Landscape: Navigating unique vulnerabilities, data poisoning, model drift, prompt injections, and emerging regulatory requirements.The Security Leader's Role: Establishing policy, accountability models, and risk thresholds across complex AI lifecycles.Core Competencies for 2026: Mastering the balance between AI technologies, data controls, and executive governance strategies. ISACA AAISM Blueprint: Exploring the three core domains (Governance, Risk, and Controls) required to pass the credential exam. 🎧 Essential listening for CISOs, CISM/CISSP holders, GRC managers, and cybersecurity leaders looking to champion AI governance.Watch full episode here: https://www.youtube.com/watch?v=Aw0MSKSKSnw
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AWS AI Practitioner Exam Roadmap
2w ago01:25:49Tap to summarizeReady to build intelligent cloud applications? The AWS Certified AI Practitioner credential validates fundamental cloud AI expertise. In this episode of TechTalks, InfosecTrain delivers an exam-oriented walkthrough to help you pass on your first attempt. The "course titled" AWS Certified AI Practitioner Training accelerates your study through real-world architectures, Amazon Bedrock, SageMaker, prompt optimization, and token management.📘 What You’ll Learn:Core Machine Learning Concepts: Demystifying the operational differences between supervised learning, deep learning, and generative AI within enterprise environments.Responsible AI & Risk Management: Understanding AWS best practices for identifying model bias, ensuring data safety, and upholding governance standards. Prompt Engineering Strategies: Mastering context optimization, token usage mechanics, and structured templates to maximize foundation model outputs.AWS Managed AI Suite: A hands-on overview of integrating Bedrock, SageMaker, Rekognition, and Comprehend into enterprise workflows.First-Attempt Exam Strategy: Proven test-taking tips, domain weighting breakdowns, and preparation roadmaps to pass with flying colors.🎧 Essential listening for cloud practitioners, developers, IT architects, and tech professionals looking to gain a competitive edge in AWS AI architectures.Watch full episode here: https://www.youtube.com/watch?v=l3NnHV-09_s
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Al-Driven Identity Governance Explained | What's Next in 2026?
3w ago00:33:39Tap to summarizeIn 2026, the biggest identity challenge won't be people - it will be AI agents, machines, and non-human identities. The security landscape is shifting rapidly as automated bots, API tokens, and service accounts become primary attack vectors for modern adversaries. In this forward-looking masterclass episode, InfosecTrain breaks down the expanding risks associated with unmanaged programmatic assets and analyzes why traditional, human-centric security models fail to protect them. The "course titled" SailPoint IdentityIQ Training Program offers an essential foundational framework for security architects racing to close these visibility gaps. We move beyond manual access review spreadsheets to explore automated lifecycle management engineered for the machine-to-machine era. Discover how to deploy intelligent security architectures to defend complex automated pipelines, establish clear human ownership over autonomous agents, and transition your business into a resilient Zero Trust posture. 📘 What You’ll Learn:The 2026 Identity Landscape: Mapping the rapid expansion of non-human identities (NHIs) and understanding why they outnumber human accounts 10:1 in cloud-native organizations. AI vs. AI Defense: Deploying intelligent, machine-learning security analytics to monitor, detect, and isolate anomalous behaviors across autonomous systems in real time. Governing Automated Access: Establishing rigorous inventory, classification, and clear human accountability baselines for every running workload and service account. Next-Generation Lifecycle Management: Architecting the secure birth, continuous credential rotation, and prompt deprovisioning of machine identities without disrupting live production environments.Preventing Lateral Movement: Implementing proactive policy restrictions that block high-privilege service accounts created without verified governance approvals. 🎧 Essential listening for security professionals, IAM architects, cloud engineers, and cybersecurity leaders preparing their infrastructure for the realities of autonomous enterprise workloads.Watch full episode here: https://www.youtube.com/watch?v=STMABBbQh_I
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AI Governance for CISOs: Decoding ISO 27001 vs. ISO 42001
3w ago00:39:33Tap to summarizeAI Governance Is No Longer Optional for CISOs. As artificial intelligence becomes deeply embedded in business operations, automated decision-making, and enterprise risk management, today's security leaders face a new challenge - not just securing data, but governing algorithmic models responsibly. In this episode of InfosecTrain TechTalks: Real World Decoded, host Payal Pawar sits down with Gaurav Sinha, a leading AI Governance and Cybersecurity Consultant, to explore how security executives can move beyond compliance checklists and build operational frameworks using global standards.The "course titled" ISO 42001 Lead Implementer Training serves as an indispensable blueprint for teams trying to draw clear boundaries between traditional IT security and algorithmic risk. While legacy frameworks excel at data confidentiality, they struggle with the fluid, non-deterministic behaviors unique to machine learning pipelines. We map out how to build dedicated AI risk registers, align controls with standard information security management systems, and translate technical AI vulnerabilities into business risk narratives that ensure courtroom and boardroom readiness.📘 What You’ll Learn:The New CISO Mandate: Unpacking why AI oversight has shifted from a data science experiment to an immediate, high-priority priority for corporate infosec.ISO 27001 vs. ISO 42001: A strategic comparison between managing generalized information security and building a dedicated AI Management System (AIMS).Algorithmic Risk Architecture: Practical guidance on constructing AI risk registers that specifically account for data bias, model drift, and prompt injection vectors.Operationalizing AI Governance: Seamlessly embedding AI-specific safety controls into your existing corporate workflows without strangling innovation.Boardroom Communication Strategies: Translating complex technical machine learning metrics into clear compliance and financial risk parameters for executive stakeholders.🎧 Essential listening for CISOs, CIOs, GRC professionals, and compliance experts looking to lead the next evolution of enterprise security architecture.Watch full episode here: https://www.youtube.com/watch?v=qe5NEStgJ6Q
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Crack CISSP in Your First Attempt in 2026
3w ago00:55:13Tap to summarizeThinking like a security leader is the absolute secret to conquering the CISSP exam. The primary reason candidates struggle with the test is that they answer questions from a purely technical perspective instead of adopting a managerial mindset. This session is designed to shift your perspective and build the exact strategy needed for success.Passing the exam on your first attempt requires a structured approach that respects the Computerized Adaptive Testing mechanics and the 2026 content updates.The 4-Phase Roadmap to Success1. Establish a Baseline: Weeks 1-2Take a full length diagnostic practice test before studying. Identify your weakest areas among the eight domains so you can allocate your study hours efficiently.2. Master Core Domains: Weeks 3-10Dive deep into high weight areas like Security and Risk Management. Pay close attention to modern topics integrated across the domains, including cloud native architectures, zero trust frameworks, and generative AI risk governance.3. Adopt the Managerial Mindset: Weeks 11-12Practice shifting your focus from fixing technical problems to selecting answers that protect the business mission, satisfy regulatory compliance, and mitigate systemic enterprise risk.4. Simulate Exam Dynamics: Weeks 13-14Take adaptive style mock exams. Because the testing algorithm adjusts question difficulty based on your answers and does not allow you to return to previous items, practice pacing yourself carefully through scenario based questions.Crucial 2026 Rule: Technical knowledge is the floor, but business leadership is the ceiling. Always choose the option that fixes the root process over the one that simply patches the immediate technical bug.To fast-track your journey and gain the comprehensive mentorship needed to conquer the eight domains, exploring structured training is your best next step.For an extensive deeper dive into the exact domain changes, exam mechanics, and preparation paths, check out this comprehensive 2026 CISSP Exam Strategy Video Guide which highlights how recent experience waiver updates and new governance models alter your study path.Watch Full Episode here: https://www.youtube.com/watch?v=3QpAPEmMOhc
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Implementing an AI Management System: A Practical Roadmap
4w ago00:30:28Tap to summarizeAI success isn't just about innovation - it's about governance, accountability, and trust. As enterprises rapidly transition from testing machine learning models to deploying them across live production environments, unstructured experimentation must give way to a rigorous framework. In this foundational masterclass, InfosecTrain provides a step-by-step strategic roadmap for constructing an enterprise-grade Artificial Intelligence Management System (AIMS).The "course titled" ISO/IEC 42001:2023 Lead Auditor Training is an essential asset for professionals who want to lead these governance architectures. We pull back the curtain on how to systematically translate abstract ethical standards into concrete operational baselines. Learn how to navigate the core clauses of the international standard, establish solid accountability lines across data science teams, and build a scalable compliance program that protects your enterprise from model risk while accelerating business growth.📘 What You’ll Learn:Defining True AI Governance: Demystifying what it means to govern automated systems and understanding the commercial value of building consumer trust.Core Requirements Walkthrough: A comprehensive breakdown of the necessary structures, lifecycle controls, and continuous oversight tools mandated by an AIMS.The Implementation Roadmap: A logical, multi-phase action plan designed to guide your organization smoothly from isolated machine learning sandboxes to enterprise-wide compliance.Responsible AI Practices: Setting clear parameters around algorithmic transparency, explainability, data pedigree, and model monitoring.Preparing for the Audit: Keys to aligning internal validation controls with external international auditing requirements.🎧 Essential listening for compliance officers, GRC professionals, AI product leaders, and cybersecurity managers ready to establish bulletproof governance frameworks.Watch full epidose here: https://www.youtube.com/watch?v=KeUcqmoJEE0
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