Adversarial ML
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Evasion Attacks in Production ML: Malware, Spam, and Fraud
Deployed ML classifiers in malware, spam, and fraud detection face evasion attacks where the attacker has a clear payoff.
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Web-Scale Dataset Poisoning: Split-View and Frontrunning
Split-view attacks exploit mutable web content, while frontrunning targets timed snapshots to poison datasets without training pipeline access.
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Adversarial Examples Against Vision Models in 2026
Where physical-world adversarial patches and digital attacks stand against modern vision models, what has been hardened, and what red teams should test.
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Jailbreaking Multimodal Models: Visual Prompt Injection
How attackers use images, typography, and adversarial perturbations to bypass safety guardrails in multimodal models, and why vision widens the surface.
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Model Extraction via Black-Box Query Attacks
How attackers reconstruct model behavior and decision boundaries through query-only access, the economics of the attack, and what stolen models enable.
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Model Inversion and Membership Inference in LLMs
How membership inference reveals whether specific data trained a model, and how inversion reconstructs private text from gradients and model outputs.
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Supply Chain Attacks on AI Models: Poisoning and Backdoors
How attackers compromise models before production through dataset poisoning, malicious fine-tuning, and serialization exploits, and how to detect it.