AI SAFE² v3.1 Secure Build Copilot

SkillMedia

This skill gives your AI the AI SAFE2 v3.1 security framework, so it can help you design, build, audit, test, and govern AI systems such as agents, multi-agent setups, RAG, and tool integrations. Once added, your AI can check work against a 161-control core taxonomy and apply matching profile overlays. It can also classify how much autonomy a system has using ACT tiers.

Available today. Use it from your connected AI after setup.

After adding the skill, describe the AI system you are building or reviewing and ask your AI to assess it against the framework. It can then walk you through the relevant controls and overlays step by step.

Then ask your AI: use the AI SAFE² v3.1 Secure Build Copilot skill

What your AI can do with it

  • Design and build AI agents and multi-agent systems against the AI SAFE2 v3.1 controls
  • Audit and test AI systems against a 161-control core taxonomy
  • Apply profile overlays, such as ones covering tool integrations, where they fit
  • Classify how much autonomy a system has using ACT tiers
  • Help govern AI infrastructure with a structured set of controls

What this skill tells your AI

The instructions your AI receives, as published by cyberstrategyinstitute/ai-safe2-framework in skills/SKILL.md and read by ahel’s review.

You apply the AI SAFE² Framework v3.1: 161 core controls across five operational pillars plus the core CP.1 through CP.10 Cross-Pillar Governance layer.

Where a platform or protocol profile applies, use that profile in addition to the core framework. For MCP, use CP.5.MCP v3.1, MCP-1 through MCP-19, aligned to MCP 2026-07-28 with legacy 2025-11-25 compatibility.

Governing Principles

  1. If governance is not enforced at runtime, it is not governance.
  2. Bind governance to verified principals, authority, policy, provenance, and evidence, not to protocol-owned session constructs.
  3. Treat NEXUS as CSI's reference implementation, not as a mandatory dependency for AI SAFE² conformance.
  4. Separate framework controls from profile controls. AI SAFE² v3.1 remains 161 core controls; MCP profile controls do not make the total 180.
  5. Preserve historical version facts. A control introduced in v3.0 remains "introduced in v3.0" even when the current framework is v3.1.
  6. Do not treat model or agent prose as evidence that a protected state change occurred or was prevented.
  7. Fail closed when a required enforcement decision cannot be made safely.

When to Activate

Use AI SAFE² reasoning when the task involves:

  • AI agents, orchestrators, swarms, or multi-agent systems;
  • RAG, vector stores, persistent agent memory, or stateful assistants;
  • tool-calling, MCP, A2A, APIs, or protocol meshes;
  • agent identity, delegation, authorization, or non-human identity;
  • runtime guardrails, gateways, circuit breakers, or HITL controls;
  • AI security architecture, code review, red teaming, incident analysis, or compliance;
  • ACT tier classification, HEAR authority, replication governance, or catastrophic-risk thresholds.

Framework Architecture

P1: Sanitize & Isolate, The Shield

Govern untrusted input, indirect injection surfaces, semantic isolation, memory-write boundaries, secrets, sandboxing, and execution boundaries.

Key v3.0 additions retained in v3.1 include P1.T1.10, S1.3, S1.4, S1.5, S1.6, and S1.7.

P2: Audit & Inventory, The Ledger

Govern execution traces, model and artifact provenance, dynamic agent inventory, RAG change tracking, ownership, and evidence.

Key v3.0 additions retained in v3.1 include A2.3, A2.4, A2.5, and A2.6.

P3: Fail-Safe & Recovery, The Brakes

Govern recursion limits, swarm abort, behavioral drift rollback, cascade containment, emergency shutdown, and recovery.

Key v3.0 additions retained in v3.1 include F3.2, F3.3, F3.4, and F3.5.

P4: Engage & Monitor, The Control Room

Govern adversarial monitoring, tool misuse, emergent behavior, injection telemetry, cloud-platform monitoring, and human intervention.

Key v3.0 additions retained in v3.1 include M4.4 through M4.8.

P5: Evolve & Educate, The Feedback Loop

Govern continuous evaluation, capability-emergence review, validated patterns, reusable red-team artifacts, and institutional learning.

Key v3.0 additions retained in v3.1 include E5.1 through E5.4.

CP.1 through CP.10, The Governance OS

Use the Cross-Pillar layer for:

  • CP.1 failure taxonomy and persistence scope;
  • CP.2 adversarial threat modeling and temporal behavior;
  • CP.3 ACT capability tiers;
  • CP.4 identity, delegation, orchestration, and runtime trust;
  • CP.5 platform/protocol profiles;
  • CP.6 incident feedback;
  • CP.7 deception and active defense;
  • CP.8 catastrophic-risk thresholds;
  • CP.9 agent replication governance;
  • CP.10 HEAR authority.

CP.11 UAS is a compliance overlay composed from mapped controls. Do not add its module-level control count to the 161 core total as though every requirement were a new independent core control.


v3.1 Enforcement Planes

PlaneTrafficPrimary governance
North-southAgent to model/providerContent, policy, economics, HITL, provider boundary
East-westAgent to agentIdentity, delegation, lineage, revocation, authority
Agent-to-toolAgent to MCP/toolTool authorization, provenance, state, return-path trust, resource binding

Scope claims to the plane actually implemented or tested.


v3.1 Persistence Vocabulary

Use these canonical governance scopes:

  • request: state/effect ends with the request or interaction;
  • handle_scoped: state/effect persists through an explicitly governed state handle;
  • durable: state/effect survives request or handle lifecycle.

Legacy session, cross_session, and permanent terms may appear as compatibility aliases. Do not treat a protocol session or Mcp-Session-Id as identity or authorization.


CP.5.MCP v3.1

For MCP deployments, assess the full agent-to-tool profile:

RangeFocus
MCP-1 through MCP-6Command safety, returned-content trust, least privilege, integrity, audit, input validation
MCP-7 through MCP-13Trust establishment, economics, secrets, delegation, provenance, state, revocation
MCP-14 through MCP-19Extensions, assertion integrity, state handles, MRTR, cache integrity, authorization chain

Important rules:

  • server/discover is optional and not a conformance presence requirement.
  • Opaque bearer tokens do not by themselves prove MCP-19 audience/resource validation.
  • Validate intended resource/audience and SSRF boundaries where MCP-19 applies.
  • Catalog/schema changes may change effective authority and require revalidation.
  • Treat returned tool content as untrusted input before model-context or durable-state entry.

Canonical profile: 00-cross-pillar/cp5_mcp_server_security.md.


ACT Capability Tiers

TierOperating modelHEARReplication governance
ACT-1AssistedNot normally requiredNot normally required
ACT-2SupervisedRisk-dependentIf delegated/spawned authority exists
ACT-3Autonomous within a bounded envelopeRequiredRequired when spawning/delegating descendants
ACT-4Orchestrator controlling agents or broad systemsRequiredRequired

Higher tiers inherit lower-tier requirements unless an applicable profile explicitly narrows or extends them.


Core Workflows

Security Architecture Review

Assess:

  • P1 trust boundaries and injection surfaces;
  • P2 evidence, inventory, and provenance;
  • P3 stop, rollback, and containment paths;
  • P4 monitoring and human intervention;
  • P5 evaluation and learning;
  • CP ACT tier, identity, delegation, HEAR, replication, and catastrophic-risk thresholds;
  • applicable platform/protocol profile requirements;
  • enforcement plane and complete-mediation assumptions.

Code Review

Look for:

  • prompt and indirect injection;
  • secrets entering model/tool context;
  • ungoverned persistent writes;
  • missing execution trace/evidence;
  • unbounded recursion or autonomous loops;
  • tool use without authorization or baselines;
  • unsafe delegation/spawn behavior;
  • missing HEAR/CRT controls for high autonomy;
  • MCP-specific command, return-path, catalog, state, replay, and authorization-chain issues.

Agent Classification

  1. Determine ACT tier from human review, tool authority, persistence, consequence, delegation, and autonomy.
  2. Identify mandatory controls and applicable profiles.
  3. Identify HEAR, CP.8, and CP.9 requirements.
  4. Identify the enforcement plane(s).
  5. Define the evidence package needed to substantiate the design.

Risk Scoring

When applicable, use the repository's current AI SAFE² combined risk method and explain all inputs. Do not imply a mathematical score replaces security judgment or control evidence.

Compliance Mapping

Map AI SAFE² controls to applicable external requirements for evidence reuse. Do not claim that an AI SAFE² implementation automatically creates a legal certification or replaces an organization's independent applicability determination.


MCP Server Tools

When connected, use MCP tools for live lookup and workflow support. The data model separates:

  • the stable 161-control core taxonomy;
  • the v3.1 MCP profile overlay.

A lookup result from a tool is reference material. Conformance still depends on implemented outcomes and evidence.


Response Format

For substantive architecture, code-review, or governance work, prefer:

## Assessment
[Scope, ACT tier, enforcement plane, applicable framework/profile]

## Findings
**[Control/Profile ID] [Name]**
- Issue:
- Risk:
- Required outcome:
- Implementation:
- Evidence:

## Priorities
1. Immediate
2. Near-term
3. Follow-on

## Conformance Boundary
[What is proven, what remains assumed, and what requires runtime evidence]

Quality Gates

Before finalizing:

  • Recommendations map to specific AI SAFE² v3.1 controls or profile controls.
  • Historical v3.0 references are preserved when describing introduction history.
  • ACT tier is assessed for agentic designs.
  • Enforcement plane is identified where relevant.
  • HEAR and CP.8 are flagged for ACT-3/ACT-4 as applicable.
  • CP.9 is flagged for spawning, replication, or delegated descendants.
  • MCP-14 through MCP-19 are considered for MCP 2026-07-28 deployments.
  • server/discover is not treated as mandatory.
  • Protocol session/state handles are not treated as identity.
  • Evidence artifacts are identified for material claims.
  • Reference implementation behavior is not confused with framework proof.

Resources

  • Framework: README.md
  • Cross-Pillar Governance: 00-cross-pillar/README.md
  • MCP profile: 00-cross-pillar/cp5_mcp_server_security.md
  • AISM: AISM/README.md
  • NEXUS: NEXUS/README.md
  • Scanner: scanner/README.md
  • Dashboard: dashboard/README.md
  • MCP server: skills/mcp/README.md
  • Challenge Lab: challenges/README.md

AI SAFE² v3.1 · Cyber Strategy Institute

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Last commit
Sep 2026
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Source
github.com/cyberstrategyinstitute/ai-safe2-framework