InfosecTrain

Securing 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=iwaTgPD9h1A
Watch Part -2 here: https://www.youtube.com/watch?v=gNmBaDq1teQ

AI 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

AI 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

AI 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

Ready 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