AI Security
In-depth guides and analysis on ai security from the Safeguard engineering team.
676 articles
Guardrails for Autonomous Code-Fixing Agents
AI agents can now open pull requests that patch vulnerabilities on their own. Without guardrails — scoped permissions, test gates, human merge approval — they can also break builds and introduce new flaws at machine speed.
Enterprise AI Center Of Excellence Blueprint
An AI Center of Excellence is not a committee. It is the function that makes AI adoption coherent across business units. The blueprint is specific.
ROI Timeline: Griffin AI vs Mythos
The honest answer to "when does this pay back?" is where sales decks and procurement reality diverge. Griffin AI and Mythos-class tools have different ROI shapes.
Griffin AI vs Open Weights: Supply Chain Risks
Open-weight models give you total deployment control. They also give you a new supply chain to secure. The tradeoff is worth being explicit about.
AI Scaffold Prompts: Enterprise Governance
System prompts that scaffold AI assistants are now load-bearing enterprise assets. A framework for versioning, reviewing, and governing them as seriously as source code.
Regression Gate Design Patterns For Security LLMs
A release gate that fails on regression is the most important operational control for AI-for-security tools. The design patterns are specific and worth copying.
Griffin AI vs Claude Citations: Advisory Work
Claude's citations feature makes the model say where its claims come from. Griffin AI uses it for advisory workflows where traceability is the entire point.
Securing MCP Servers: A Practical Checklist
MCP servers are runtime dependencies your agent trusts implicitly. Here is a concrete checklist for auth, tool pinning, sandboxing, and monitoring before you ship one.
Griffin AI vs OpenAI Pricing: Security Workloads
Per-token pricing on the OpenAI API looks cheap on a single call and expensive on a year-long security workload. Griffin AI's pricing reflects the architecture.
Small Language Models: Security Use-Case Fit
Small language models aren't a worse version of large ones. For specific security workflows, they're the right tool — if you know which workflows.
Zero-Day Triage Without Drowning Engineers
A zero-day discovery pipeline is only as useful as the triage process around it. Here is what triage looks like when the pipeline gives engineers something they can defend.
Claude MCP Tool Poisoning Threat Model 2026
A senior engineer's threat model for Claude MCP tool poisoning in 2026, covering malicious servers, description hijacking, and the authorization patterns that actually help.