AI Red Team Engineering notes, research references, and field notes on AI systems, responsible AI, governance, and compliance.
Global search

Search AI Red Team

Search across the complete knowledge base.

Enter at least two characters to begin.
↑↓ select Enter open Browse the full research archive
NVIDIA AI Red Team · June 27, 2024

Secure LLM Tokenizers to Maintain Application Integrity

analysis AI Red TeamingAI EngineeringAdversarial ML
Why it matters

NVIDIA demonstrates a model supply-chain attack in which a privileged adversary edits a tokenizer JSON file so visible words map to different token IDs. The change can make the model interpret "deny" as "allow" or corrupt decoded output while leaving the model weights untouched.

My takeaway: Version, sign, inventory, and verify tokenizers together with model weights and code. Check artifact integrity again at runtime, protect remote repositories and local caches, and log token IDs or tokenizer versions alongside input and output strings so an encoding or decoding mismatch remains visible during investigation.
Keep exploring

More curated notes connected through AI Red Teaming and AI Engineering.

OpenAI News · framework

OpenAI’s Frontier Governance Framework

OpenAI's 22-page Frontier Governance Framework maps its frontier-model processes to California's Transparency in Frontier AI Act and the EU AI Act's general-purpose AI code. It documents lifecycle risk assessment, cyber-offense and other risk tiers, mitigation and residual-risk decisions, critical-incident handling, security risk management, model reporting, external review, responsibility allocation, and change control.

OpenAI News · framework

Cybersecurity in the Intelligence Age

OpenAI proposes a five-pillar strategy for AI-enabled cyber defense: tiered access for trusted defenders, faster government-industry coordination, stronger protection of frontier models and infrastructure, risk-scaled deployment monitoring, and broader defensive support for individuals and small organizations.

OWASP GenAI Security Project · guide

OWASP Top 10 for Agentic Applications for 2026

OWASP's community guide organizes agentic-system risk into ten categories, including goal hijacking, tool misuse, identity and privilege abuse, memory poisoning, insecure inter-agent communication, cascading failures, and rogue-agent behavior. It provides a shared taxonomy and mitigation starting point rather than a certification checklist or evidence that a deployed system is secure.