Flashcards
11,105 cards in 101 decks, written from the same source as the concepts. Space to flip, arrows to move, K and R to sort what you know from what you do not. Progress lives in your browser.
Security, Privacy & Adversarial ML
Attacks on models, data and the supply chain, and the defences that survive contact.
Adversarial Robustness
Perturbation attacks, adversarial training, certified defences, and the robustness-accuracy tradeoff.
Privacy-Preserving ML
Differential privacy accounting, federated learning, secure aggregation, and the utility cost of each guarantee.
LLM Application Security
Injection across trust boundaries, tool and sandbox escape, secret exposure and threat modelling for agents.
Model Provenance & Watermarking
Output watermarking, content credentials, fingerprinting weights and detecting extraction.
ML Supply Chain Security
Untrusted weights and datasets, deserialisation risk, dependency and registry attacks, and signing artefacts.