Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
On May 5, 2026, NIST's CAISI signed pre-deployment evaluation agreements with Google DeepMind, Microsoft, and xAI, bringing five frontier labs into a government testing program covering cyber, bio, and chemical risk.
AI agents pull tools, models, and data from a sprawling chain of upstream providers. In 2026 attackers learned to poison that chain — and the fallout is shaping how enterprises buy and operate agentic systems.
Agent runaway is no longer a theoretical risk — it is a line item on quarterly variance reports. The 2026 trend in agentic AI is less about model capability and more about who pays when an agent loops.
MCP servers went from a niche protocol to standard agent infrastructure in under two years. The vulnerability disclosure landscape is catching up — fast, messily, and with patterns worth tracking.
AI coding assistants are now standard developer tooling. The incident data from 2025 and early 2026 shows a recurring pattern of source code, credential, and customer data leaking through them.
Multi-repo security reasoning is a graph problem, not a retrieval problem. How Griffin AI's engine scales where pure-LLM products flatten into guesswork.
An attacker who can swap the model behind an API call can read every prompt and shape every response. The emerging trend in 2026 is model substitution as an attack class with its own techniques and disclosures.
Fine-tuning to improve one task frequently regresses others. Without eval harnesses, the regressions ship. The measurable drift is larger than vendors admit.
The difference between grounded reasoning and hallucinated reasoning is not eloquence — it's citation. A look at how Griffin AI anchors every claim.
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