# adversarial-ml
4 articlestagged with “adversarial-ml”
Adversarial ML: Core Concepts
History and fundamentals of adversarial machine learning — perturbation attacks, evasion vs poisoning, robustness — bridging classical adversarial ML to LLM-specific attacks.
Foundations
Essential building blocks for AI red teaming, covering red team methodology, the AI landscape, how LLMs work, embeddings and vector systems, AI system architecture, and adversarial machine learning concepts.
Lab: Adversarial ML From Scratch
Hands-on expert lab for implementing gradient-based adversarial attacks against language models from scratch without frameworks, building intuition for how adversarial perturbations exploit model gradients.
Counterfit Walkthrough
Complete walkthrough of Microsoft's Counterfit adversarial ML testing framework: installation, target configuration, running attacks against ML models, interpreting results, and automating adversarial robustness assessments.