LegionForge

Legionforge

Local-First. Security-Native. AI Agents You Can Trust.

A hardened AI agent framework designed for teams that require real security guarantees.

🚧 Phase 1 in active development. Public release coming soon.

View Project on GitHub


Why Legionforge Exists

Modern AI agent frameworks ship fast and secure later — if ever.
Legionforge flips that model.

Security is enforced in the execution path, not layered on afterward.
Every tool invocation, privilege boundary, and mutation is governed by deterministic controls.

Result: predictable, auditable, failure-contained AI systems.


Core Capabilities

Deterministic Security Enforcement

No LLM involvement in security decisions.
Controls are fast, auditable, and resistant to prompt injection by design.

Task-Scoped Privilege Model

Permissions follow the task — not the agent.
Short-lived tokens define exact capability boundaries for each execution.

Cryptographic Tool Trust

Tools are validated by hash and signature.
Behavior changes cannot occur silently.

Human-Governed Mutations

Security policy changes require explicit approval.
Autonomous privilege escalation is impossible by design.


Threat Classes Addressed

Threat Severity
Tool Poisoning Critical
Rug-Pull Tool Behavior Critical
Prompt Injection (Direct + Indirect) Critical
Resource Exhaustion / Economic DOS High
Credential Exposure High
RAG / Memory Poisoning High
Multi-Agent Cascade Failure High
Supply Chain Risk Medium

Architecture Philosophy

Security must operate in the hot path of execution.
Failure handling must be tiered, not binary.
Privilege must be bounded and ephemeral.
Mutation must always be human-governed.


Roadmap

Phase Focus Status
0 — Infrastructure Core services, storage, model factory Complete
1 — First Agent + Security Foundation Researcher agent, validation, logging Active
2 — Guardian Security Layer Containerized execution, audit log Planned
3 — Access Control Model Task tokens, orchestrator pattern Planned
4 — Adaptive Threat Intelligence Threat Analyst agent Planned
5 — Signed Tool Ecosystem Verified tool distribution Planned
6 — Continuous Security Testing Air-gapped red-team agent Planned

Deployment Target

Designed for local execution on Apple Silicon.
No mandatory cloud dependency.
Security guarantees do not depend on external infrastructure.


Project Status

Codebase currently private during Phase 1 hardening.
Public repository release planned upon completion.

Follow development progress on GitHub.


Author

Jp Cruz
Security-focused AI systems engineering


License

AGPL-3.0 — open source with reciprocal guarantees.