Tag
Shieldstral is the 3B safety classifier Mistral released in August 2026: it answers yes or no to a policy written in plain language. Converted to GGUF Q8_0 with llama.cpp and served on a CPU, it blocked no legitimate one among the 100 Spanish and English prompts I prepared, but let 8 of 17 injections through.
LLM red teaming has gone from an esoteric activity to a mandatory practice. With the OWASP Agentic Top 10 and the CSA Agentic AI Red Teaming Guide converging on shared vocabulary, this is the operational playbook any team deploying agents needs to have.
After two years of pilots and a year of agents in production, governance has moved from an aspirational committee to an operational control. What audits ask for, what broke in 2025, and which guardrails absorb most incidents.
Guardrails frameworks promise to filter language-model inputs and outputs to block data leaks, harmful content, or hallucinations. After evaluating four of the most popular ones in production, I cover what they actually do, what latency and billing cost they add, and when they pay off over simpler controls.
LLM agent security became a real incident category the moment assistants gained tool access. Agents that call tools expose a far wider attack surface than chatbots, and it now carries assigned CVEs, published audit reports, and its own OWASP Top 10. The spread of the Model Context Protocol and agent-driven corporate workflows built that surface in under 18 months.
Adversarial machine learning studies deliberate attacks on AI systems (evasion, poisoning and model extraction) and the defenses used to resist them, chiefly adversarial training, robustness certification and monitoring the distribution of production input data.
