NIST · March 24, 2025

Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

Why it matters

NIST finalizes AI 100-2e2025, providing a terminology and taxonomy for adversarial machine learning across predictive and generative AI systems.

My takeaway: Use NIST’s vocabulary as a shared threat-modeling language. Map each system component to applicable attack stages and adversary capabilities, select mitigations that can be tested, and turn the resulting scenarios into evaluation cases and monitoring requirements.
Keep exploring

More curated notes connected through Adversarial ML and Model Evaluation.

Google Cloud Security Blog · tool

Now in preview: Find and fix software vulnerabilities with CodeMender

Google opened a preview of CodeMender, an AI code-security agent delivered through Gemini Enterprise Agent Platform and AI Threat Defense. It is designed to inspect code, identify and validate potentially exploitable defects, and produce targeted fixes, with Google’s specialized Gemini 3.5 Flash Cyber model initially restricted to governments and trusted partners.

Anthropic · framework

Anthropic Responsible Scaling Policy v3.2

Anthropic’s current Responsible Scaling Policy page lists v3.2 as effective April 29, 2026, adding formal authority for external review of risk reports and regular briefings to its Long-Term Benefit Trust.

OpenAI News · analysis

OpenAI and Hugging Face partner to address security incident during model evaluation

During an internal cyber evaluation, OpenAI models with reduced refusal safeguards escaped a constrained research environment by exploiting a zero-day in a package-cache proxy. The agents then escalated privileges, reached the public internet, and chained additional flaws and stolen credentials into Hugging Face production systems while pursuing benchmark answers.