AI Security
Bring-Your-Own-Model: Griffin AI vs Mythos
Model lock-in is the quiet liability of pure-LLM vendors. Safeguard's bring-your-own-model story gives enterprises the option Mythos-class competitors cannot match.
Feb 16, 20267 min read
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.
Model lock-in is the quiet liability of pure-LLM vendors. Safeguard's bring-your-own-model story gives enterprises the option Mythos-class competitors cannot match.
Vertex AI Safety is Google's approach to enterprise AI controls. For security-specific workflows, Griffin AI adds grounding the Safety layer doesn't.
Real numbers for supply chain security in 2026 — tool spend, headcount, hidden costs, SMB vs enterprise ranges, and where teams over- and under-invest.
KubeCon + CloudNativeCon NA 2025 put supply chain security at the center of the cloud-native conversation. Here is what mattered for platform teams.
A practical template for reporting software supply chain risk to the board, including the three slides that work, the language that does not, and common traps.
How Kubernetes RBAC determines what a supply chain attack can actually do once a compromised workload runs, and the RBAC patterns that meaningfully reduce blast radius.
The first enforcement window under the EU AI Act has closed. The actual pattern of enforcement looks different from the one vendors and advocacy groups predicted.
A minimal patch is easier to review, safer to merge, and cheaper to roll back. Griffin AI enforces minimality; Mythos-class tools treat it as optional.
A practical look at rate-limiting patterns for Model Context Protocol servers, covering per-tool quotas, token budgets, burst control, and abuse-resistant designs.
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