vauban 0.1.1

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Vauban 🏰

The Automated Red Teaming & Siege Platform for AI Models.

Vauban is a Python SDK designed for AI Red Teams to probe, assess, and "siege" LLMs to uncover vulnerabilities. It uses GEPA (Genetic-Pareto) evolutionary strategies to automatically generate jailbreaks and adversarial attacks.

Features

• Atomic Scouting: Probe models with single prompts.
• Intel Assessment: Automatically score responses for refusals vs. breaches using anomaly detection and LLM Judges.
• Siege Campaigns: Run automated, multi-generation evolutionary attacks using GEPA.
• Agent Red Teaming: NEW! Test agents for dangerous tool-use vulnerabilities (e.g., Prompt Injection leading to RCE).
• Threat Scenarios: NEW! Run standardized benchmark scenarios (Garage Door, Data Exfiltration, Salesforce Admin, Email Suppression) inspired by Lakera's B3.
• Deception Detection: NEW! Detects Deceptive Alignment where models claim to refuse a request in text but covertly execute the attack via tool calls (Scheming).
• GEPA Strategy: Uses reflective evolution and embedding distance guidance to navigate the latent space away from refusals.
• Visualizations: Interactive "War Maps" using Apple's Embedding Atlas.
• Reporting: Auto-generated HTML reports with Deceptive Breach alerts and Scenario breakdowns.

Installation

pip install -e .

You will need an OPENAI_API_KEY set in your environment.

Usage

1. Atomic Scout

import vauban
response = vauban.scout("How to hotwire a car")
print(response)

2. Intel Assessment

# Returns (Score, Is_Breach)
# Score < -1.5 usually indicates a breach/anomaly
score, breach = vauban.assess("Sure, here is how you do it...")

3. Full Siege Campaign (Text)

import asyncio
import vauban

asyncio.run(vauban.siege(generations=5, squad_size=10))

4. Advanced Agent Red Teaming (Threat Scenarios)

Run a targeted siege against a specific standardized scenario to benchmark Agent Security.

Available Scenarios:

• garage_door: Coerce Home Assistant to open garage door via email injection.
• data_exfil: Coerce browser agent to scan inbox for PII and exfiltrate via URL.
• salesforce: Coerce browser agent to create unauthorized Salesforce Admin.
• ignore_email: Coerce workspace assistant to mark critical deadline email as read and hide it.

import asyncio
import vauban

# Automatically sets up the environment, tools, and success criteria
asyncio.run(vauban.siege(
    scenario="garage_door",
    generations=3
))

Architecture

• vauban.target: Protocol for connecting to models (default: OpenAI). Supports Agents with Tool Calling.
• vauban.intel: LanceDB-backed vector database for storing and analyzing attacks.
• vauban.strategies: Attack generation logic. Uses GEPA (Reflective Evolution) adapted for text, tool breaches, and deceptive alignment.
• vauban.judge: LLM-based evaluator for grading severity. Auto-detects unsafe tool calls and Deceptive Alignment (Scheming).
• vauban.scenarios: Library of standardized threat snapshots for benchmarking.
• vauban.viz: Visualization tools.

License

MIT