AI/LLM Security
A comprehensive guide to securing artificial intelligence and large language model systems — from understanding how LLMs work to attack vectors, penetration testing, red teaming, and defense strategies.
What is AI & LLMs
Understanding artificial intelligence, large language models, transformer architecture, and the modern AI ecosystem.
12 min readWhat is AI/LLM Security
Defining AI security, understanding why it differs from traditional software security, and mapping the AI threat landscape.
10 min readOWASP Top 10 for LLM Applications
The 2025 OWASP Top 10 risks for LLM applications — each vulnerability explained with real-world examples and mitigations.
18 min readAI/LLM Attack Vectors
A detailed breakdown of attack techniques targeting AI systems — from prompt injection and jailbreaking to data poisoning, model extraction, and supply chain attacks.
20 min readSecurity Frameworks & Standards
Key frameworks for AI security — MITRE ATLAS, NIST AI RMF, OWASP guides, EU AI Act, and ISO/IEC 42001.
15 min readAI/LLM Penetration Testing
Methodologies and techniques for penetration testing AI and LLM systems — from scope definition to active testing and reporting.
18 min readAI/LLM Red Teaming
Red teaming methodologies for AI systems — Microsoft, Google DeepMind, and Anthropic approaches, plus tools and real-world case studies.
16 min readDefenses & Mitigations
Defense strategies for AI/LLM systems — input/output filtering, guardrails, alignment techniques, architectural defenses, and monitoring.
15 min readTools & Resources
Essential tools for AI security testing — vulnerability scanners, red teaming frameworks, guardrails, plus key research papers and community resources.
14 min readReal-World Incidents & Case Studies
Notable AI security incidents and breaches — from ChatGPT data leaks and Samsung source code exposure to indirect prompt injection exploits.
16 min read