SubDepthTag / #ai-security
Tagged #ai-security
A narrower slice of the archive collected around one repeated concern.
I Monitored a Chinese AI Model for Bias. Here's What I Found.
GLM 4.6 monitoring revealed 12% geographic bias, narrative injection, and trust-building patterns. Empirical security research on lower-cost AI model behavior.
Prompt Injection: The SQL Injection of AI (But Unsolvable)
Prompt injection is the defining LLM vulnerability with no parameterized query fix. Unlike SQL injection, it may be theoretically impossible to solve.
Why AI Security Broke Traditional InfoSec Playbooks
Traditional CISSP frameworks fail against prompt injection and unsolvable AI vulnerabilities. Here's why agility matters more than stability in AI security.
10 Lessons from Building an AI Agent Security Lab
Lab lessons: prompt injection unsolvable, vendor lock-in is operational risk, agility is control. Breaking systems teaches security faster than theory.
AI Security Challenges We're Not Ready For
Unprepared for autonomous agents, model poisoning, deepfakes, and AI arms races. Security frameworks, certifications, and playbooks lag behind capabilities.
From USS Tennessee to AI Security: A Cybersecurity Journey
From USS Tennessee ISSM to AI security: how traditional cybersecurity expertise became both foundation and limitation for securing AI systems.
How to Structure Data for AI Without Creating Security Nightmares
Balance AI context with security: structured data, sanitization, RAG, and least-privilege. Practical patterns for safe AI without data exfiltration risks.
Vendor Lock-In is Your Biggest AI Security Risk
Cloud AI providers control your infrastructure completely. Multi-vendor architecture isn't optional; it's a security control for operational resilience.