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Assured Agent Execution

CI Core: REMORA, pinned Paper (PDF) License: BUSL-1.1

Controlled execution for AI-agent tool calls.

Powered by REMORA.

Assured Agent Execution (AAE) governs how AI agents interact with tools and operational systems.

Every proposed tool call receives one of four decisions:

Decision Action
ACCEPT Execute automatically
VERIFY Require approval
ABSTAIN Stop
ESCALATE Route to a higher authority

AAE binds authorization to the exact tool call, separates approval from execution, verifies selected effects against the system of record, and records the complete execution lifecycle.

Architecture

flowchart LR
    A[AI agent or application] --> B[AAE control plane]

    R[Pinned REMORA core] --> B
    T[Signed ToolPack] --> B
    I[Authority source] --> B

    B --> D{Decision}

    D -->|ACCEPT| X[Execute]
    D -->|VERIFY| V[Required approval]
    D -->|ABSTAIN| S[Stop]
    D -->|ESCALATE| H[Higher authority]

    V --> X
    H --> V

    X --> O[System of record]
    O --> P[Read-only effect verification]

    B --> E[Audit and evidence]
    P --> E
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Core capabilities

  • Four-way decision routing
  • Exact-payload approval binding
  • Separate identities for proposing, approving and executing
  • Deployment-controlled ToolSpecs
  • Pinned and verified REMORA artifacts
  • Read-only postcondition verification
  • Replay-resistant execution grants
  • Lifecycle and evidence export

Quickstart

Requirements

  • Docker with Docker Compose
  • Python 3.11 or newer
  • Authenticated GitHub CLI (gh)
git clone https://github.com/darklordVirtual/assured-agent-execution
cd assured-agent-execution

python run.py up
python run.py scenarios

python run.py up:

  1. fetches and verifies the pinned REMORA artifacts;
  2. creates installation-specific credentials;
  3. signs the ToolPack;
  4. builds the containers;
  5. applies the database migrations;
  6. starts the control plane and the assurance console.

The API and console URLs are printed when startup completes.

Reference scenarios

The included work-order ToolPack demonstrates the complete execution flow:

ACCEPT     Grounded read executes automatically
VERIFY     Production write requires approval
ABSTAIN    Unresolved authority stops the request
ESCALATE   Destructive action requires senior authority
BINDING    Approval cannot be reused for another payload
ROLES      An approver cannot execute its own approval

The main governed path is:

propose → assess → approve → execute → verify effect → record

To try to get past these controls yourself, see Attack the demo.

REMORA integration

AAE runs REMORA's governance engine, consumed as a fixed set of released artifacts rather than from its main branch. Every artifact is verified before anything uses it, and the install refuses on a mismatch.

Which artifacts, the current values, and how to move to a newer release: The pinned core.

Repository structure

src/aae/                  CLI, configuration, evidence and verification
toolpacks/work_order/     Reference ToolPack
db/workorders/            Example system-of-record schema
console/                  Read-only assurance console
docker/                   Container definitions
product/                  Pinned REMORA artifacts and metadata
tests/compatibility/      Core compatibility tests
tests/e2e/                Execution and security tests
docs/                     Architecture, security model and operations

Commands

python run.py up          # Start the stack
python run.py scenarios   # Run the reference scenarios
python run.py doctor      # Inspect the deployment
python run.py check-sign  # Verify the ToolPack
python run.py check       # Contract tests, no Docker required
python run.py verify      # Contract and end-to-end tests
python run.py down        # Stop the stack
python run.py reset       # Stop and remove all volumes

backup, restore, sbom, sign and reseed are documented in Operations.

Documentation

Security

Report suspected vulnerabilities to support@luftfiber.no rather than in a public issue. SECURITY.md states the scope; docs/security-model.md states control by control what is enforced and what is only declared.

Non-claims

AAE does not claim that agents are always correct, that all tools can be effect-verified, that safety is guaranteed, or that bypass is impossible when an agent retains direct tool credentials.

License

Source-available under the Business Source License 1.1.

See LICENSING.md for permitted use and commercial terms. The pinned REMORA core is a separate Licensed Work under the same licensor.

About

Controlled execution for AI-agent tool calls. A reference runtime that routes every proposed tool call to ACCEPT, VERIFY, ABSTAIN or ESCALATE through a hash-pinned REMORA core, binds approval to the exact payload, and verifies the effect against the system of record.

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