Not a policy deck.
Every resource should give you a test, checklist, Skill, or workflow pattern you can use.
Free Agentic AI Security Field Guide
Secure the agents before they touch the workflow.
VibeSec Advisory publishes practical research, reusable Skills, workflow patterns, agent reviews, MCP notes, prompt injection tests, CLI security guides, AI red-team lessons, and market news for builders working with AI systems.
No pricing, SOWs, paid assessments, workshops, retainers, or service funnel. Just security-focused content you can use to test and improve what you are building.
Not AI hype.
Workflow controls come before tool recommendations.
Not unmanaged automation.
Actions, approvals, and recovery paths stay visible before AI gets more authority.
Short answer
What does VibeSec Advisory help builders do?
VibeSec Advisory helps builders understand and test the risks created by agents, MCP servers, AI coding tools, prompt injection, and AI-generated workflows.
Browse the Skill LibraryLatest field notes
Practical notes on agents, MCPs, prompt injection, AI coding tools, and safer workflows.
Essays, checklists, Skills, and field notes for people building and testing AI systems.
MCP And Tooling
MCP Roots Need a File Access Review
MCP roots expose filesystem boundaries to servers. Review each root path, resource path, tool path, sensitive file class, and log before approving it.
Read field noteMCP And Tooling
MCP Elicitation Needs a Sensitive Data Gate
MCP elicitation lets servers ask users for structured input. Treat it as a permissioned data request with sensitive-field blocks, decline paths, rate limits, and logs.
Read field noteMCP And Tooling
MCP Sampling Needs Its Own Approval Gate
MCP sampling lets a server ask the client to run a model call. Treat it as a separate approval gate before you expose context, tools, or returned responses.
Read field noteThe problem
AI adoption without workflow design creates invisible risk.
People are using copilots, agents, and MCP-connected tools inside live business processes. The question is no longer whether AI is being used. The question is whether the workflow has a baseline, reusable skills, permissions, review points, and a measurement loop.
Workflow first
Start with the process, owner, inputs, approvals, and failure modes before tools.
Business metrics first
Good workflow review starts with the current metric, owner, and target state.
Guardrails by design
Human checkpoints, data boundaries, action limits, escalation, and security are mapped together.
Evidence before claims
Write down what you tested, what failed, what changed, and what still needs review.
Use The Field Guide
Start with free research, Skills, and workflow artifacts.
The public front door is the research archive, the VibeSec Advisory Skill Library, and the workflow examples. Each resource should help you understand a risk, test an agent, review a tool, or improve a workflow.
Free first step
FreeAgentic AI Security Research
Read field notes on agents, MCPs, prompt injection, AI coding tools, generated code, and practical security workflows.
- Prompt injection tests
- MCP security notes
- AI red-team lessons
Operating artifacts
FreePublic Skill Library
Browse reusable AI workflow skills, guardrails, examples, and implementation patterns that show how governed work should be captured.
- Reusable procedures
- Review gates
- Data boundaries
Workflow artifacts
FreeWorkflow Examples
- Review gates
- Data boundaries
- Reusable outputs
- Failure checks
FORGE
A six-pillar model for agent-ready work.
FORGE remains a historical and educational model for thinking about governed workflows. The active VibeSec Advisory direction is a free field guide for securing agentic AI.
FORGE pillar
Baseline
Current workflow, owner, source system, pain point, and target metric.
FORGE pillar
Skills
Reusable instructions that capture how expert work should be done and reviewed.
FORGE pillar
Agents
Automation only where the tool boundary, action limit, and recovery path are known.
FORGE pillar
Guardrails
Data boundaries, approval gates, escalation rules, and security controls.
FORGE pillar
Schedule
Triggers, cadence, dependencies, and failure handling for repeatable work.
FORGE pillar
Capture
Evidence, lessons, regression checks, and the next measurable improvement.
How we work
Less strategy theater. More usable operating artifacts.
Capture
Capture reusable Skills, source boundaries, review gates, and test results so workflow knowledge compounds.
Map
Map agents to concrete steps, owners, tools, review points, and failure modes before trusting automation.
Contain
Guardrails are designed as blast-radius controls, not vague policy language.
Measure
Every artifact should include a way to test, review, or improve the workflow.
Start with the systems your agents can touch.
Read the latest field notes, then use the Skills and workflow examples to test your own agentic AI systems.