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ciberbal-ai

ciberbal-ai cybersecurity agent ecosystem

Configure your AI coding agents for authorized cybersecurity work: pentesting methodology, persistent memory, curated skills, MCP tools, and reproducible workflows.

Release License: MIT Go 1.24+ Platform


What It Does

ciberbal-ai is a configuration platform for AI-assisted cybersecurity work. It takes the AI agents you already use and installs a consistent operating environment for authorized pentesting, lab work, security research, evidence handling, and technical reporting.

It configures agent prompts, skills, MCP servers, persistent memory, model routing, backups, and reproducible workflows so the agent behaves less like a generic chatbot and more like a disciplined security assistant.

Before: "I installed Claude Code / OpenCode / Cursor, but it's just a chatbot."

After: Your agent has scope-aware guardrails, repeatable methodology, persistent context, security skills, MCP tools, and reporting-oriented workflows for authorized engagements.

8 Supported Agents

Agent Delegation Model Key Feature
Claude Code Full (Task tool) Sub-agents, output styles
OpenCode Full (multi-mode overlay) Per-phase model routing
Gemini CLI Full (experimental) Custom agents in ~/.gemini/agents/
Cursor Full (native subagents) 9 SDD agents in ~/.cursor/agents/
VS Code Copilot Full (runSubagent) Parallel execution
Codex Solo-agent CLI-native, TOML config
Windsurf Solo-agent Plan Mode, Code Mode, native workflows
Antigravity Solo-agent + Mission Control Built-in Browser/Terminal sub-agents

Scope: ciberbal-ai is intended for authorized security work only: owned environments, labs, CTFs, training platforms, and engagements with written permission or a defined rules of engagement.


Quick Start

Recommended path: clone the repository and run the install script for your platform.

macOS / Linux

git clone https://github.com/Balthael/ciberbal-ai.git
cd ciberbal-ai
chmod +x scripts/install.sh
./scripts/install.sh

Windows

git clone https://github.com/Balthael/ciberbal-ai.git
cd ciberbal-ai
.\scripts\install.ps1

Or run it remotely: irm https://raw.githubusercontent.com/Balthael/ciberbal-ai/main/scripts/install.ps1 | iex

After install: project-level setup

Once your agents are configured, open your AI agent in a project and run these two commands to register the project context:

Command What it does When to re-run
/sdd-init Detects stack, testing capabilities, activates Strict TDD Mode if available When your project adds/removes test frameworks, or first time in a new project
skill-registry Scans installed skills and project conventions, builds the registry After installing/removing skills, or first time in a new project

These are not required for basic usage. The SDD orchestrator runs /sdd-init automatically if it detects no context. But if something changed in your project (new test runner, new dependencies), re-running them manually ensures the agents have up-to-date context.

Default operating model

ciberbal-ai is designed to support a fast full-stack install for authorized cybersecurity and pentesting workflows:

  • Quick install configures the full ecosystem by default
  • no specialty prompt is required during the quick path
  • Advanced install preserves granular configuration when you need it
  • the long-term target is one setup usable across web, API, mobile, cloud, AD/internal, reporting, and general security workflows

Pentesting capability model

The install flow does not split users into specialties. Instead, ciberbal-ai is moving toward a unified capability model where the default install provisions all major pentesting layers together:

  • Web
  • API
  • Mobile
  • AD/Internal
  • WiFi/Wireless
  • Cloud
  • Recon
  • Reporting

See Pentesting Domains for the canonical domain and engagement-phase mapping.

The full-pentest preset now bundles post-install capability packs for each canonical domain plus workflow packs for scoping, recon, enumeration, exploitation, post-exploitation, evidence, and reporting.


Install

Important: the primary supported install flow is repository clone + platform install script. Release archives are optional, but package-manager distribution is not part of the current model.

Local development / testing

go test ./...
go run ./cmd/ciberbal-ai

Recommended install (macOS / Linux)

git clone https://github.com/Balthael/ciberbal-ai.git
cd ciberbal-ai
chmod +x scripts/install.sh
./scripts/install.sh

Recommended install (Windows)

git clone https://github.com/Balthael/ciberbal-ai.git
cd ciberbal-ai
.\scripts\install.ps1

Alternative: run install script without cloning

curl -fsSL https://raw.githubusercontent.com/Balthael/ciberbal-ai/main/scripts/install.sh | bash
irm https://raw.githubusercontent.com/Balthael/ciberbal-ai/main/scripts/install.ps1 | iex

Windows (PowerShell — alternative)

# Option 1: PowerShell installer (downloads binary from GitHub Releases)
irm https://raw.githubusercontent.com/Balthael/ciberbal-ai/main/scripts/install.ps1 | iex

From releases

Download the binary for your platform from GitHub Releases.


Backups

Every install, sync, and upgrade automatically snapshots your config files. Backups are compressed (tar.gz), deduplicated (identical configs are not re-backed up), and auto-pruned (keeps the 5 most recent). Pin important backups via the TUI (p key) to protect them from pruning.

See Backup & Rollback Guide for details.


Documentation

Topic Description
Intended Usage How ciberbal-ai is meant to be used — the mental model
Agents Supported agents, feature matrix, config paths, and per-agent notes
Components, Skills & Presets All components, GGA behavior, skill catalog, and preset definitions
Pentesting Domains Canonical domains and engagement phases for the full-stack pentesting model
Usage Persona modes, interactive TUI, CLI flags, and dependency management
Backup & Rollback Backup retention, compression, dedup, pinning, and restore
Platforms Supported platforms, Windows notes, security verification, config paths
Architecture & Development Codebase layout, testing, and relationship to Gentleman.Dots

Credits

ciberbal-ai is derived from an MIT-licensed AI agent configuration framework originally created by Gentleman Programming.

This project adapts that foundation for cybersecurity and pentesting workflows, preserving the original MIT license while extending the platform with a security-focused install flow, Ciberbal branding, domain-specific skills, and engagement workflow support.

License and Attribution

This repository includes work derived from the original Gentleman Programming framework, Copyright (c) 2025 Gentleman Programming, used under the MIT License.

The original copyright notice and permission notice are preserved in LICENSE, as required by the license terms.


License: MIT

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