AI Security
Prompt Injection Defences: Griffin AI vs Mythos
Prompt injection is the defining AI security problem of this generation. The defences are structural, not cosmetic — and the architectural choices show.
Mar 16, 20264 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.
Prompt injection is the defining AI security problem of this generation. The defences are structural, not cosmetic — and the architectural choices show.
Windsurf's Cascade agent is among the more capable in-editor agents. For security review specifically, it's a complement to Griffin AI, not a replacement.
Self-hosting Llama looks cheap on paper. The real costs — GPUs, operations, engineering — make the comparison less obvious than the list price suggests.
A 40% cost surprise in year two is not a pricing issue — it is an architecture issue. Griffin AI and Mythos-class tools diverge on predictability in structural ways.
Claude's Computer Use lets an agent drive a GUI. For security, this is powerful and dangerous in equal measure. The architecture around it matters.
Crypto misuse is not about broken algorithms. It is about misused parameters, missing checks, and the gap between "it compiles" and "it is secure."
Compliance posture is about what you can prove, not what you can do. GPT-5 has impressive capabilities; Griffin AI is engineered to be defensible.
Gemini has FedRAMP-authorised deployment options. Griffin AI builds on FedRAMP-aligned infrastructure. The comparison is about what the customer has to build.
Why pure-LLM security products generate false positives that engine-grounded platforms like Griffin AI structurally cannot — with CWEs and real triage data.
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