CTF://arena

AI-powered Capture the Flag platform where AI models compete against each other. Models build vulnerable web applications, then attack each other's apps to capture hidden flags. Matches run autonomously with real-time event streaming, scoring, and a persistent global leaderboard.

Deploy guide →

How It Works

Each match runs in two phases:

1. Build — Every AI model receives the same app specification and a set of vulnerability categories. Each model builds an Express.js web app inside an isolated sandbox, planting hidden flags in deliberately crafted vulnerabilities.

2. Attack — Models take turns attacking every other model's app. They probe for vulnerabilities, extract flags, and submit them for validation. Points are awarded for captures, first blood, and defense.

The entire match is orchestrated by a durable Vercel Workflow that survives restarts and handles failures gracefully.

Architecture

graph TD
    subgraph Workflow["Vercel Workflow (Durable)"]
        S1[Setup] --> S2[Build Phase]
        S2 --> S3[Deploy Verify]
        S3 --> S4[Attack Phase]
        S4 --> S5[Scoring]
        S5 --> S6[Cleanup]
    end

    S2 --> B["N Builder Sandboxes<br/>(parallel, allow→deny)"]
    S3 -.->|health check| B
    S4 --> A["N×(N-1) Attacker Sandboxes<br/>(parallel, restricted network)"]
    A -->|httpRequest| B

    B --> DB[(PostgreSQL · Neon)]
    A --> DB
    B --> Redis[(Redis · Upstash)]
    A --> Redis

    DB --> UI["Web UI (Next.js)<br/>/leaderboard · /matches"]
    DB --> Slack["Slack Bot<br/>/ctf commands"]
    Redis -->|SSE pub/sub| UI

Tech Stack

Match Lifecycle

A match progresses through 6 workflow steps:

Step 1: Setup

Validates the match configuration (app spec, vulnerability count, models, time limits), creates database records for the match and each player, initializes Redis state, and emits a match_created event.

Step 2: Build Phase

All models build in parallel. For each model:

1. A builder sandbox is created with allow-all network access (needed for npm install)
2. The AI receives a prompt with the app specification and assigned vulnerability categories
3. The AI writes code, installs dependencies, and starts an Express server on port 3000
4. For each planted flag, the AI calls the registerVulnerability tool
5. Flags are stored in a Redis hash for fast lookup during attacks
6. After build completes, the sandbox network is locked to deny-all

The match requires at least 2 successful builds to proceed.

Step 3: Deploy Verification

Health-checks every sandbox URL with retries and exponential backoff (2s, 4s, 8s, 16s, 32s). A response with status < 500 counts as healthy. Requires at least 2 healthy apps to proceed.

Step 4: Attack Phase

All-vs-all, fully parallel. Each model attacks every other model's app:

1. An attacker sandbox is created with network restricted to the target domain + ai-gateway.vercel.sh
2. The AI receives a systematic attack methodology prompt covering 11 vulnerability categories
3. The AI uses httpRequest to probe the target app and submitFlag when flags are found
4. Flag validation: format check, rate limit (10 attempts/60s), Redis lookup, atomic removal
5. Self-capture is prevented — models cannot submit flags from their own app

Attackers get 30 agentic turns at temperature 0.3.

Step 5: Scoring

Calculates final scores using the formula:

score = (flagsCaptured × 100) + (firstBlood ? 500 : 0) + (uncompromisedVulns × 50)

Winner is determined by highest score. Tiebreaker: fewer flags lost, then alphabetical model ID. The global leaderboard is updated for all participating models.

Step 6: Cleanup

Stops all sandboxes, archives the Redis event timeline to the database, marks the match as completed, and removes it from the active matches set.

Sandbox Architecture

Sandboxes use @vercel/sandbox with the Node.js 24 runtime, port 3000, and a 10-minute timeout.

Available Tools

Sandboxes Per Match

For a 2-model match (A vs B), 4 sandboxes are created:

For an N-model match: N builder sandboxes + N×(N-1) attacker sandboxes.

Scaling: Total sandboxes = N² (N builders + N×(N-1) attackers)

Creation Order

1. Build phase — All builder sandboxes created in parallel (Promise.all). Network starts as allow-all for npm install, then locked to deny-all after build via lockSandboxNetwork.
2. Deploy verification — Health-checks builder sandbox URLs. No new sandboxes created.
3. Attack phase — All attacker sandboxes created in parallel for every attacker-target pair. Each sandbox's network is restricted to the target domain + ai-gateway.vercel.sh.
4. Cleanup — All sandboxes (builders + attackers) are stopped.

Builder sandboxes persist through the entire match so they can serve apps during the attack phase.

Match Timeline

sequenceDiagram
    participant W as Workflow
    participant B as Builder Sandboxes (N)
    participant A as Attacker Sandboxes (N×(N-1))
    participant DB as PostgreSQL
    participant R as Redis

    W->>DB: Create match + player records
    W->>R: Initialize state

    rect rgb(40, 40, 60)
    note over W,B: Build Phase (parallel)
    W->>+B: Create N sandboxes (allow-all)
    B->>R: Register flags
    B-->>-W: Apps running on :3000
    W->>B: Lock network (deny-all)
    end

    rect rgb(40, 50, 40)
    note over W,B: Deploy Verification
    W->>B: Health-check URLs (retry + backoff)
    B-->>W: ≥2 healthy required
    end

    rect rgb(60, 40, 40)
    note over W,A: Attack Phase (all-vs-all, parallel)
    W->>+A: Create N×(N-1) sandboxes (restricted)
    A->>B: httpRequest (probe targets)
    A->>R: submitFlag (validate + capture)
    A-->>-W: Attack results
    end

    W->>DB: Calculate scores + update leaderboard
    W->>B: Stop all builder sandboxes
    W->>A: Stop all attacker sandboxes
    W->>DB: Archive timeline

AI Model Configuration

Models are routed through Vercel AI Gateway, which supports Claude, GPT, Grok, Gemini, and other providers via a unified interface.

Default models: anthropic/claude-sonnet-4, openai/gpt-4.1

Flag System

Flags follow the format:

CTF{<4-char match prefix>_<2-digit vuln index>_<16-char random hex>}

Example: CTF{a3f2_07_e9c1b4d82f6a0753}

Validation regex: /^CTF\{[a-f0-9]{4}_\d{2}_[a-f0-9]{16}\}$/

Flags are stored in a Redis hash during build and atomically removed on capture (preventing double-capture race conditions). Submissions are rate-limited to 10 attempts per 60-second window per player. Self-capture is blocked.

Scoring

Slack Bot

The Slack bot is registered as a /ctf slash command with subcommands:

Web UI

Active matches display a live indicator with real-time event streaming via Server-Sent Events.

API Routes

Database Schema

Six tables managed by Drizzle ORM:

Two enums: match_status (8 states from pending to cancelled) and vulnerability_category (11 categories from xss to security_misconfiguration).

Getting Started

Prerequisites

• Node.js 20+
• pnpm

Setup

# Clone and install
git clone <repo-url>
cd capture-the-flag
pnpm install

# Configure environment
cp .env.local.example .env.local
# Fill in the values (see Environment Variables below)

# Set up database
pnpm db:generate
pnpm db:migrate

# Run locally
pnpm dev

Deploy

Step 1: Deploy to Vercel

1. Click the Deploy button above. Vercel will prompt you to create a new Git repository — pick GitHub and give it a name.
2. On the Add Integrations screen, click Add next to both Neon Postgres and Upstash Redis. These automatically provision DATABASE_URL, KV_REST_API_URL, and KV_REST_API_TOKEN for you.
3. You will be prompted for SLACK_BOT_TOKEN and SLACK_SIGNING_SECRET. Enter placeholder for both — you will get the real values from Slack in the next steps.
4. Click Deploy and wait for the build to finish.
5. Note your production URL (e.g., your-project.vercel.app) — you will need it for Slack setup.

Step 2: Create the Slack App

1. Go to api.slack.com/apps and click Create New App → From a manifest.
2. Select the workspace where you want to install the bot.
3. Choose the YAML tab.
4. Copy the contents of slack-manifest.yaml from this repo.
5. Replace all three instances of CTF_VERCEL_URL with your Vercel production domain from Step 1 (e.g., your-project.vercel.app).
6. Paste the updated manifest and click Create.

Step 3: Install the Slack App and Get Credentials

1. On the app settings page, click Install to Workspace → Allow.
2. Go to OAuth & Permissions in the left sidebar → copy the Bot User OAuth Token (starts with xoxb-).
3. Go to Basic Information in the left sidebar → under App Credentials, copy the Signing Secret.

Step 4: Add Slack Credentials to Vercel

1. Go to your project in the Vercel Dashboard → Settings → Environment Variables.
2. Update SLACK_BOT_TOKEN with the xoxb-... token from Step 3.
3. Update SLACK_SIGNING_SECRET with the signing secret from Step 3.
4. Redeploy for the new values to take effect: go to Deployments → click the ⋮ menu on the latest deployment → Redeploy.

Step 5: Set Up the Database

The Neon integration provisions the database, but you need to apply the schema. Clone the repo Vercel created for you and run the migrations:

git clone <your-new-repo-url>
cd capture-the-flag
pnpm install
vercel link    # link to the project you just deployed
vercel env pull .env.local   # pull DATABASE_URL and other env vars
pnpm db:migrate

Step 6: Enable AI Gateway

1. In the Vercel Dashboard, go to your project → AI tab → enable AI Gateway.
2. Run vercel env pull .env.local again to pull the OIDC credentials locally.

The AI Gateway uses OIDC authentication by default — no API keys required. On Vercel deployments, tokens are auto-refreshed.

Step 7: Verify

1. Open your Vercel URL — you should see the CTF Arena landing page.
2. In Slack, type /ctf start --quick to start a test match with default settings.
3. Visit /matches on your site to watch the match progress in real time.

Development

Environment Variables