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CAISR CERTIFICATION

Certified AI Security Researcher

Validate advanced, practical skills in AI and LLM security through hands-on exploitation of production-grade AI environments.

24-Hour Exam + 24hr Reporting
Dedicated AI Lab Environment

Overview

The Certified AI Security Researcher (CAISR) certification is a fully hands-on, scenario-driven credential designed to validate advanced, practical skills in AI and Large Language Model (LLM) security. It is built for security researchers and practitioners working with modern AI systems.

Rather than testing theory, CAISR challenges candidates to operate as real AI security researchers. You will analyze and exploit vulnerable AI applications, navigate complex systems, compromise RAG pipelines, exploit MCP servers, and attack autonomous agent workflows in environments that reflect how AI is actually deployed today.

Who Should Take This

  • Experienced security engineers and penetration testers
  • AI and LLM red teamers
  • Vulnerability researchers working with AI systems
  • AI developers responsible for security
  • AI security consultants

Benefits

Stand Out in AI Security

Signal verified expertise in AI and LLM security as organizational adoption outpaces skill benchmarks.

Real-World Capability

Prove you can assess, exploit, and secure complex production AI systems, not just isolated demos.

Specialized Security Roles

Strengthen your profile for AI security researcher, LLM red teamer, and AI application security engineer roles.

Attacker Mindset

Develop understanding of how modern AI systems fail in practice, including cross-component attack paths.

Production Experience

Gain experience transferring directly to auditing deployed AI services and agent platforms.

Peer Recognition

Use the certification as a concrete signal of technical credibility in this emerging niche.

Exam Objectives

1

LLM Architecture and Exploitation: Demonstrate mastery of transformer architectures, attention mechanisms, and inference pipelines.

2

Prompt Injection and Jailbreaking: Execute advanced prompt injection attacks and bypass safety guardrails in real-world AI applications.

3

MCP Server Security: Identify and exploit vulnerabilities in Model Context Protocol servers including authentication bypasses.

4

RAG System Vulnerabilities: Compromise vector databases, perform knowledge base poisoning, and exploit semantic search mechanisms.

5

AI Agent Security: Attack autonomous agent workflows, exploit tool-use confusion, and manipulate agent communication protocols.

6

AI-Generated Code Analysis: Identify vulnerabilities in AI-generated applications and exploit common AI coding mistakes.

7

Production AI Infrastructure: Assess and exploit vulnerabilities in LangChain, LlamaIndex deployments, and model serving infrastructure.

8

AI Agent Development: Create AI agents to automate security-related operations.

Exam Format

24 hrs + 24hr Reporting

Exam Duration

Report

Final Deliverable

The 24-hour exam is entirely hands-on. You will receive access to a dedicated vulnerable AI environment containing multiple LLM endpoints, RAG pipelines, MCP servers, and autonomous agent systems. An additional 24 hours is provided for report preparation.

Passing Criteria: Your submission is a comprehensive security research report documenting identified vulnerabilities, exploitation methodology, attack chains, proof-of-concepts, impact analysis, and practical remediation guidance.

Certificate: Successful candidates are awarded the 8kSec Certified AI Security Researcher certification, showcasing proficiency in AI and LLM security.

Lab Environment

During the exam, you will have access to a dedicated lab environment containing vulnerable AI applications, LLM endpoints, MCP servers, and agent systems with full instructions.

Prerequisites

  • Strong background in penetration testing and red teaming
  • Solid understanding of LLM architectures
  • Experience securing AI-enabled applications and infrastructure
  • Practical skills in exploiting LLM-based systems and bypassing guardrails
  • Familiarity with LangChain, LlamaIndex, MCP, RAG systems, and Python

Recommended Training

Practical AI Security: Attacks, Defenses, and Applications

Covers modern AI security architectures, offensive exploitation techniques, and defensive design patterns. Work directly with vulnerable systems, develop exploit tooling, and build security-focused AI agents.

Learn More

Frequently Asked Questions

Who is this Certification intended for?
Intended for experienced security engineers, penetration testers, vulnerability researchers, and AI developers who work with modern AI and LLM-based systems.
Is prior experience required?
Yes. The exam assumes hands-on experience with application security and a solid understanding of LLM architectures. This is not an entry-level certification.
How long does it take to prepare?
Preparation time varies based on your individual learning pace. On average, participants spend a few days to several weeks preparing. It is recommended to spend at least 2-3 weeks practicing before attempting the exam.
Is training mandatory before taking the exam?
The certification is currently offered upon successful completion of the accompanying training class.
Do I need to set up my own labs?
No, we will provide you access to our lab environment and an instruction guide during the exam.
How long does it take to get results?
Once you submit your report, a member of our review board will review it and provide results within 5 business days.
Take the Next Step

Ready to Get CAISR Certified?

Prove your expertise with an industry-recognized certification from 8kSec.