Prompt Injection Defence Training Course

Prompt Injection Defence Training Course

Introduction

Prompt Injection Defence Training Course is designed to equip professionals with advanced skills to identify, prevent, and mitigate prompt injection attacks targeting Large Language Models (LLMs), Generative AI applications, AI agents, and enterprise AI systems. As organizations rapidly adopt AI-powered assistants, copilots, and autonomous agents, attackers are developing sophisticated techniques to manipulate AI behavior, bypass security controls, extract sensitive information, and compromise AI workflows. This course focuses on AI threat intelligence, LLM security engineering, adversarial AI defence, secure prompt architecture, AI governance, and responsible AI deployment.

Participants will gain practical expertise in building resilient AI systems through prompt validation, input sanitization, context isolation, model alignment, AI application security testing, red teaming, and continuous AI risk monitoring. Using real-world case studies, hands-on exercises, and industry frameworks, learners will understand emerging attack patterns such as direct prompt injection, indirect prompt injection, jailbreak attacks, data exfiltration attempts, tool manipulation, and agent hijacking while developing effective defence strategies for modern AI environments.

Course Duration

5 days

Course Objectives

By the end of this course, participants will be able to:

1. Understand the fundamentals of prompt injection attacks and their impact on AI security. 
2. Identify direct and indirect prompt injection vulnerabilities in LLM applications. 
3. Apply LLM security engineering principles to protect AI systems. 
4. Develop secure prompt design and prompt governance frameworks. 
5. Implement AI application security controls against malicious inputs. 
6. Perform AI red teaming and adversarial testing for prompt-based threats. 
7. Analyze jailbreak techniques and model manipulation strategies. 
8. Apply secure AI architecture patterns for enterprise deployments. 
9. Design input validation, filtering, and monitoring mechanisms. 
10. Protect AI agents from tool abuse and unauthorized actions. 
11. Apply AI governance, compliance, and risk management frameworks. 
12. Improve organizational readiness through AI threat intelligence practices. 
13. Build proactive Responsible AI security strategies for emerging AI ecosystems. 

Target Audience

1. Cybersecurity professionals and security analysts 
2. AI security engineers and machine learning engineers 
3. Application security specialists 
4. SOC analysts and threat intelligence teams 
5. Cloud security architects 
6. AI developers and software engineers 
7. Risk, compliance, and governance professionals 
8. Technology leaders responsible for enterprise AI adoption 

Course Modules

Module 1: Introduction to Prompt Injection and AI Security Threats

• Understanding Generative AI security challenges and attack surfaces 
• Evolution of prompt injection attacks against LLM systems 
• Direct versus indirect prompt injection techniques 
• AI application vulnerabilities and security implications 
• Case Study: Chatbot manipulation attacks causing unauthorized information disclosure 

Module 2: Anatomy of Prompt Injection Attacks

• Attack lifecycle and attacker methodologies 
• Malicious instruction overriding and context manipulation 
• Hidden instructions embedded in documents and external sources 
• Social engineering techniques targeting AI systems 
• Case Study: Indirect prompt injection through malicious web content consumed by AI assistants 

Module 3: Large Language Model (LLM) Security Fundamentals

• Understanding LLM architecture and security weaknesses 
• Model behavior, alignment, and instruction hierarchy 
• Context windows and security limitations 
• AI security controls and defensive architecture 
• Case Study: Enterprise LLM deployment exposed through weak security boundaries 

Module 4: Prompt Engineering for Secure AI Applications

• Secure prompt design principles and best practices 
• Creating robust system prompts and guardrails 
• Prompt validation and structured output enforcement 
• Reducing ambiguity and unintended model behavior 
• Case Study: Designing secure AI customer support assistants 

Module 5: AI Red Teaming and Prompt Injection Testing

• AI penetration testing methodologies 
• Adversarial prompt creation and testing techniques 
• Jailbreak detection and mitigation approaches 
• Security assessment frameworks for LLM applications 
• Case Study: Red team evaluation of an enterprise AI copilot 

Module 6: Defending AI Agents Against Prompt Attacks

• Agent security architecture and autonomous AI risks 
• Protecting AI tools, APIs, and external integrations 
• Preventing unauthorized agent actions 
• Identity, access control, and permission management 
• Case Study: AI agent manipulation leading to unintended workflow execution 

Module 7: Monitoring, Detection, and Incident Response for Prompt Attacks

• Building AI security monitoring capabilities 
• Detecting suspicious prompts and abnormal AI behavior 
• Logging, auditing, and forensic analysis 
• AI security operations centre (AI-SOC) practices 
• Case Study: Detecting repeated prompt injection attempts against an internal AI platform 

Module 8: AI Governance, Compliance, and Future Defence Strategies

• Establishing enterprise AI security policies 
• AI risk management and governance frameworks 
• Responsible AI principles and security alignment 
• Continuous improvement of AI defence strategies 
• Case Study: Implementing an AI governance program for a regulated organization 

Training Methodology

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.