Attended the free webinar? This programme teaches you to build the governance framework around every risk you saw demonstrated, with real compliance mapping and audit-ready deliverables. Haven't attended yet? Start there.
AI Security
GRC
Implement AI governance, risk management, and compliance frameworks. Map controls to NIST AI RMF and ISO/IEC 42001, build AI risk registers, and establish audit-ready AI security posture.
Eight weekends. Zero filler.
Each module builds from framework foundations to hands-on implementation. By the end, you will have not generic security theory re-labeled as “AI.”
NIST AI Risk Management Framework
- AI RMF structure: Govern, Map, Measure, Manage functions
- AI risk taxonomy and impact categorization
- AI system lifecycle and accountability mapping
- Identifying AI risk owners and governance responsibilities
- Documentation requirements and evidence collection
Apply the AI RMF Map function to a sample enterprise AI deployment. Produce a complete context and risk identification output.
ISO/IEC 42001 AI Management System
- ISO 42001 structure: scope, clauses, and control objectives
- AI policy development and management system design
- Conformance assessment methodology and gap analysis
- Relationship between ISO 42001, ISO 27001, and ISO 31000
- Internal audit design for AI management systems
Draft an AI security policy document with controls mapped to ISO 42001 requirements. Produce a gap analysis for a sample organization.
AI Risk Registers & Compliance Mapping
- Building and maintaining AI risk registers
- Control mapping across NIST AI RMF, ISO 42001, and OWASP
- EU AI Act overview: risk categories and compliance obligations
- Vendor and third-party AI risk assessment frameworks
- Audit evidence requirements and documentation standards
Build a complete risk register for a real-world AI deployment scenario. Map risks to controls across NIST AI RMF and ISO 42001.
Governance Implementation & Audit Readiness
- AI governance committee structure and operating model
- Board-level AI risk reporting and executive communication
- Continuous compliance monitoring for deployed AI systems
- Audit preparation methodology and readiness reviews
- Capstone: end-to-end GRC programme implementation
Capstone: produce a complete GRC deliverable set: risk register, AI policy, NIST AI RMF alignment map, ISO 42001 gap assessment, and audit checklist.
Walk out with a complete AI GRC programme.
- Implement NIST AI RMF across the full AI system lifecycle
- Map AI security controls to ISO/IEC 42001 requirements
- Build and maintain AI risk registers aligned to organizational risk appetite
- Develop AI governance policies and operational procedures
- Assess third-party and vendor AI risks systematically
- Prepare an organization for AI security audits and regulatory reviews
What you need coming in.
- Familiarity with security governance concepts (ISO 27001 or similar is helpful)
- Understanding of organizational risk management processes
- GRC, compliance, or audit background is beneficial
- No coding or technical engineering background required
- GRC professionals building AI governance and risk programs
- Compliance officers responsible for AI system oversight
- Risk managers assessing AI deployments and vendor risks
- CISOs and security leaders shaping AI security strategy
- Audit professionals preparing for AI-related assessments
AI is deployed. Security is an afterthought.
Every security team is being asked to review AI systems they have never tested. LLMs are shipped into production daily, with no threat model, no red team, no security review.
Traditional security training has not kept up. VAPT courses teach web apps. AppSec programmes cover OWASP Top 10. None of them touch what actually happens when an attacker targets an LLM, a RAG pipeline, or an autonomous agent.
This programme was built to close that gap, for practitioners who want to be the person in the room who actually understands AI Security, not just knows the acronyms.
Security teams have zero hands-on experience testing AI. Attackers are already exploiting this.
Most courses teach AI security as theory. No labs. No real systems. No way to verify you can actually do it.
You break a real AI system. Then you secure it. Then you map it to a governance framework. In one structured journey.
Not a course. A transformation.
There are courses that teach AI Security. There are none that teach you to break it, secure it, and govern it end to end, in labs, with real evaluation.
Browser-based labs. Ready in seconds.
No setup. No installation. No wasted time configuring environments. Every lab runs in your browser, fully pre-configured, with a real vulnerable AI application waiting for you.
You break real systems. Not toy examples.
Pre-built vulnerable AI applications designed to mirror production deployments: an LLM chatbot, a RAG pipeline, an autonomous agent. You attack them the same way an adversary would.
Attack → Defend → Govern. One journey.
Not three separate courses. A single, structured learning arc that takes you from exploiting a vulnerability to securing it to mapping it to a compliance framework. Nothing else does this.
OSCP-style rigour. Not attendance-based.
You earn your certificate by passing a real evaluation, not by showing up. The exam tests whether you can actually execute what you learned, against an unseen target system.
Structured like SANS. Not a YouTube playlist.
Eight weekends of deliberate, sequenced learning. Each module builds on the last. No fragmented content. No jumping between topics. A real curriculum with real progression.
Built on industry frameworks.
Every concept maps to NIST AI RMF, MITRE ATLAS, ISO/IEC 42001, and OWASP LLM Top 10. You leave with vocabulary and structure that translates directly to professional work.
You do not read about attacks. You execute them.
The lab environment is the programme. Every concept taught in a session has a corresponding lab that runs the same day. Theory without practice is not security training.
Pre-built Vulnerable AI Applications
Every lab runs against a real application: a production-style LLM chatbot with RAG, an autonomous agent with tool access, or an AI API with authentication. These are not toy examples. They model how AI is actually deployed.
Browser-Based. No Setup Required.
Labs spin up in your browser in under 60 seconds. No Docker. No VMs. No stack traces at 10pm. You land on the lab and start attacking. The environment handles everything else.
Guided Exploitation Paths
Every lab includes a structured exploitation path: a sequence of steps that takes you from reconnaissance to confirmed exploit to findings documentation. You learn technique, not just outcome.
Open-Ended Challenges
Beyond the guided path, each lab contains open-ended challenges: edge cases, multi-step attack chains, and scenarios that require you to think, not just follow instructions.
On-Demand Lab Access Throughout
Every lab environment stays available for the full duration of your programme, not just during class. Revisit, retry, and explore at your own pace. AI security is learned by doing, and doing takes time.
The real test is a real system.
The capstone is the full programme in one exercise. You assess a complete AI system, end to end. Threat model it. Break it. Secure it. Govern it. This is what professional AI security work looks like.
Threat Model the System
You receive a real-world AI application: a fully deployed LLM system with RAG, agents, and API integrations. Your first task: map the attack surface, identify trust boundaries, and produce a complete threat model using MITRE ATLAS and NIST AI RMF.
Exploit It
Now you attack. Using your threat model as a guide, you attempt to execute real vulnerabilities: prompt injection, agent manipulation, data exfiltration, guardrail bypass. Every finding is documented with severity, reproduction steps, and evidence.
Secure It
You switch sides. For each confirmed vulnerability, you design and implement a defence: guardrail updates, input validation, system prompt hardening, monitoring rules. You re-run your own attacks to verify the fix holds.
Map It to Governance
Finally, you document everything: risk register, control mappings to NIST AI RMF and ISO/IEC 42001, residual risk assessment, and remediation roadmap. A deliverable you can walk into any organisation and present.
What You Submit
You earn it. You don't just receive it.
Attendance-based certificates signal nothing to an employer. Real AI Security skill is demonstrated under examination conditions, against a system you have never seen.
Participation Certificate
Awarded on completing all programme sessions and lab exercises. Confirms you completed the training, the baseline that every graduate receives.
Exam Clearance Certificate
Awarded on passing the final assessment: a timed, practical examination against an unseen AI system. This certificate signals genuine, demonstrated competence, not attendance.
How the Exam Works
The final examination is a structured, time-bound practical challenge. You receive access to an unseen AI system and a set of objectives: find vulnerabilities, demonstrate exploitation, document findings, and propose remediation. Results are evaluated on technical accuracy and quality of deliverables, not multiple-choice.
The smartest investment in your AI security career.
sudolearning is priced at 3× less than the nearest comparable training, and delivers more: live labs, real systems, and an exam that proves you can do it.
No dedicated AI Security track. No hands-on AI labs. Expensive travel and exam fees not included.
No labs. No evaluation. No instructor. No capstone. Certificates that mean nothing.
One-day exposure. No structured curriculum. No follow-up labs or evaluation.
48 hours live. Browser-based labs. Real system capstone. OSCP-style exam. A fraction of SANS pricing.
What you are actually paying for
Early cohort pricing available. 100+ professionals already registered.
Govern the AI risk landscape.
100+ professionals already registered. Seats are filling fast.
Register for cohort dates and demo webinar access. Flagship programme graduates receive a participation certificate. Passing the final assessment earns an exam clearance certificate.