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.
The NIST SSDF attestation form asks structured questions with structured answers. A chat transcript is not an answer. We explain how Griffin AI produces the evidence auditors expect, and why Mythos-class tools struggle.
Griffin AI runs on Anthropic's Claude models under the hood. Here's what the engine context, eval harness, and workflow scaffolding actually buy you over calling Claude directly.
CVE-2024-43573 is a zero-day MSHTML spoofing flaw patched by Microsoft in October 2024. Here is the chain, detection, and why MSHTML keeps biting.
How a GitHub Actions cache poisoning attack pushed a crypto miner into Ultralytics 8.3.41 on PyPI, and what engineering teams should actually change.
Agents get tool lists, not tool boundaries. We walk through scoping patterns that actually hold when Claude 4 or GPT-5 picks the wrong function at runtime.
Frontier models are remarkable reasoners, but security workflows demand more than raw intelligence. Here's how Griffin AI grounds frontier reasoning in real tenant context.
Reachability-grounded reasoning produces actionable findings. Ungrounded LLM reasoning produces speculation. We explain the methodology gap.
Frontier models are general polymaths. Security-specific LLMs are narrow experts. Choosing between them is rarely about raw intelligence and almost always about cost, latency, and the shape of your data.
Non-determinism is not a rough edge frontier labs will polish away. It is an architectural property of how transformer decoding works, and it places a hard ceiling on the kinds of security contracts you can sign.
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