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.
Domain adaptation has quietly become the default for LLM-assisted vulnerability detection. A look at what works in 2026, what does not, and what teams should plan for next.
AI code assistants are writing a growing share of production code. The security implications are significant and largely unaddressed.
Prompt injection stopped being an LLM curiosity the moment agents started committing code. It is now a software supply chain risk and should be modeled as one.
A defender's glossary of AI security terms — prompt injection, model poisoning, AI-BOM, adversarial ML — with dated, real-world incidents behind each one.
AI source code analysis pairs LLMs with static analysis to cut false positives and speed triage -- but reachability data still decides what's real.
SPDX is the format auditors ask for, the format regulators reference, and the format most enterprise procurement teams standardize on. Griffin AI treats it as a first-class graph. Mythos-class tools treat it as a long document.
Gemini Code Assist makes developers faster. But faster is not safer. Here's how Griffin AI layers a security engine onto the same developer workflow.
Prompt injection is not a vulnerability that will be patched. It is what happens when a system cannot distinguish the instructions it is supposed to follow from the data it is supposed to process.
MCP server discovery turns a client connection string into a live capability graph. The protocol mechanics that make this convenient also widen the blast radius when discovery is spoofed, tampered with, or silently reshaped mid-session.
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