SentinelCLI

Problem statement

Security assessment workflows often rely on ad hoc tool execution without consistent scope validation, policy control or normalised findings history.

Engineering objective

1. Defined authorised target and scope validation requirements.
2. Mapped approved tool adapters and finding normalisation needs.
3. Scoped audit trail and SQLite history for repeatable runs.
4. Preserved authorised-use restrictions in product positioning.

Architecture and approach

A Python orchestration prototype that validates scope, applies a policy engine, runs approved tool adapters, normalises findings and records audit history for authorised assessment workflows.

• Policy engine and scope validation before execution.
• Adapters for Nmap, WhatWeb, testssl, Nikto and Gobuster.
• Finding normalisation and SQLite run history.
• Human confirmation for higher-impact actions.

How it works

Python CLI and orchestration layer.

SQLite history store.

Adapter pattern for approved security tools.

Controls and constraints

• Authorised target and scope validation enforced before runs.
• Not positioned as certified penetration testing or offensive-security services.
• Audit trail retained for assessment traceability.

What the system includes

• Policy-controlled orchestration CLI.
• Tool adapters and finding normalisation.
• Audit history and run records.

Product and system views

A policy-controlled Python orchestration layer for authorised security assessment tooling and auditability.

Evaluation and results

• Demonstrates security automation R&D with explicit authorised-use framing.
• Shows how tool orchestration and auditability can be engineered without overstating service credentials.

Validation and testing

• Policy and scope validation paths in orchestration design.
• Adapter-based tool execution with normalised outputs.

Limitations

• Security Automation R&D prototype only.
• Does not represent Omnific Hand certified offensive-security delivery.