fuzzforge_ai/workers

FuzzForge Vertical Workers

This directory contains vertical-specific worker implementations for the Temporal architecture.

Architecture

Each vertical worker is a long-lived container pre-built with domain-specific security toolchains:

workers/
├── rust/           # Rust/Native security (AFL++, cargo-fuzz, gdb, valgrind)
├── android/        # Android security (apktool, Frida, jadx, MobSF)
├── web/            # Web security (OWASP ZAP, semgrep, eslint)
├── ios/            # iOS security (class-dump, Clutch, Frida)
├── blockchain/     # Smart contract security (mythril, slither, echidna)
└── go/             # Go security (go-fuzz, staticcheck, gosec)

How It Works

1. Worker Startup: Worker discovers workflows from /app/toolbox/workflows
2. Filtering: Only loads workflows where metadata.yaml has vertical: <name>
3. Dynamic Import: Dynamically imports workflow Python modules
4. Registration: Registers discovered workflows with Temporal
5. Processing: Polls Temporal task queue for work

Adding a New Vertical

Step 1: Create Worker Directory

mkdir -p workers/my_vertical
cd workers/my_vertical

Step 2: Create Dockerfile

# workers/my_vertical/Dockerfile
FROM python:3.11-slim

# Install your vertical-specific tools
RUN apt-get update && apt-get install -y \
    tool1 \
    tool2 \
    tool3 \
    && rm -rf /var/lib/apt/lists/*

# Install Python dependencies
COPY requirements.txt /tmp/
RUN pip install --no-cache-dir -r /tmp/requirements.txt

# Copy worker files
COPY worker.py /app/worker.py
COPY activities.py /app/activities.py

WORKDIR /app
ENV PYTHONPATH="/app:/app/toolbox:${PYTHONPATH}"
ENV PYTHONUNBUFFERED=1

CMD ["python", "worker.py"]

Step 3: Copy Worker Files

# Copy from rust worker as template
cp workers/rust/worker.py workers/my_vertical/
cp workers/rust/activities.py workers/my_vertical/
cp workers/rust/requirements.txt workers/my_vertical/

Note: The worker.py and activities.py are generic and work for all verticals. You only need to customize the Dockerfile with your tools.

Step 4: Add to docker-compose.yml

Add profiles to prevent auto-start:

worker-my-vertical:
  build:
    context: ./workers/my_vertical
    dockerfile: Dockerfile
  container_name: fuzzforge-worker-my-vertical
  profiles:          # ← Prevents auto-start (saves RAM)
    - workers
    - my_vertical
  depends_on:
    temporal:
      condition: service_healthy
    minio:
      condition: service_healthy
  environment:
    TEMPORAL_ADDRESS: temporal:7233
    WORKER_VERTICAL: my_vertical  # ← Important: matches metadata.yaml
    WORKER_TASK_QUEUE: my-vertical-queue
    MAX_CONCURRENT_ACTIVITIES: 5
    # MinIO configuration (same for all workers)
    STORAGE_BACKEND: s3
    S3_ENDPOINT: http://minio:9000
    S3_ACCESS_KEY: fuzzforge
    S3_SECRET_KEY: fuzzforge123
    S3_BUCKET: targets
    CACHE_DIR: /cache
  volumes:
    - ./backend/toolbox:/app/toolbox:ro
    - worker_my_vertical_cache:/cache
  networks:
    - fuzzforge-network
  restart: "no"      # ← Don't auto-restart

Why profiles? Workers are pre-built but don't auto-start, saving ~1-2GB RAM per worker when idle.

Step 5: Add Volume

volumes:
  worker_my_vertical_cache:
    name: fuzzforge_worker_my_vertical_cache

Step 6: Create Workflows for Your Vertical

mkdir -p backend/toolbox/workflows/my_workflow

metadata.yaml:

name: my_workflow
version: 1.0.0
vertical: my_vertical  # ← Must match WORKER_VERTICAL

workflow.py:

from temporalio import workflow
from datetime import timedelta

@workflow.defn
class MyWorkflow:
    @workflow.run
    async def run(self, target_id: str) -> dict:
        # Download target
        target_path = await workflow.execute_activity(
            "get_target",
            target_id,
            start_to_close_timeout=timedelta(minutes=5)
        )

        # Your analysis logic here
        results = {"status": "success"}

        # Cleanup
        await workflow.execute_activity(
            "cleanup_cache",
            target_path,
            start_to_close_timeout=timedelta(minutes=1)
        )

        return results

Step 7: Test

# Start services
docker-compose -f docker-compose.temporal.yaml up -d

# Check worker logs
docker logs -f fuzzforge-worker-my-vertical

# You should see:
# "Discovered workflow: MyWorkflow from my_workflow (vertical: my_vertical)"

Worker Components

worker.py

Generic worker entrypoint. Handles:

• Workflow discovery from mounted /app/toolbox
• Dynamic import of workflow modules
• Connection to Temporal
• Task queue polling

No customization needed - works for all verticals.

activities.py

Common activities available to all workflows:

• get_target(target_id: str) -> str: Download target from MinIO
• cleanup_cache(target_path: str) -> None: Remove cached target
• upload_results(workflow_id, results, format) -> str: Upload results to MinIO

Can be extended with vertical-specific activities:

# workers/my_vertical/activities.py

from temporalio import activity

@activity.defn(name="my_custom_activity")
async def my_custom_activity(input_data: str) -> str:
    # Your vertical-specific logic
    return "result"

# Add to worker.py activities list:
# activities=[..., my_custom_activity]

Dockerfile

Only component that needs customization for each vertical. Install your tools here.

Configuration

Environment Variables

All workers support these environment variables:

Variable	Default	Description
TEMPORAL_ADDRESS	localhost:7233	Temporal server address
TEMPORAL_NAMESPACE	default	Temporal namespace
WORKER_VERTICAL	rust	Vertical name (must match metadata.yaml)
WORKER_TASK_QUEUE	{vertical}-queue	Task queue name
MAX_CONCURRENT_ACTIVITIES	5	Max concurrent activities per worker
S3_ENDPOINT	http://minio:9000	MinIO/S3 endpoint
S3_ACCESS_KEY	fuzzforge	S3 access key
S3_SECRET_KEY	fuzzforge123	S3 secret key
S3_BUCKET	targets	Bucket for uploaded targets
CACHE_DIR	/cache	Local cache directory
CACHE_MAX_SIZE	10GB	Max cache size (not enforced yet)
LOG_LEVEL	INFO	Logging level

Scaling

Vertical Scaling (More Work Per Worker)

Increase concurrent activities:

environment:
  MAX_CONCURRENT_ACTIVITIES: 10  # Handle 10 tasks at once

Horizontal Scaling (More Workers)

# Scale to 3 workers for rust vertical
docker-compose -f docker-compose.temporal.yaml up -d --scale worker-rust=3

# Each worker polls the same task queue
# Temporal automatically load balances

Troubleshooting

Worker Not Discovering Workflows

Check:

1. Volume mount is correct: ./backend/toolbox:/app/toolbox:ro
2. Workflow has metadata.yaml with correct vertical: field
3. Workflow has workflow.py with @workflow.defn decorated class
4. Worker logs show discovery attempt

Cannot Connect to Temporal

Check:

1. Temporal container is healthy: docker ps
2. Network connectivity: docker exec worker-rust ping temporal
3. TEMPORAL_ADDRESS environment variable is correct

Cannot Download from MinIO

Check:

1. MinIO is healthy: docker ps
2. Buckets exist: docker exec fuzzforge-minio mc ls fuzzforge/targets
3. S3 credentials are correct
4. Target was uploaded: Check MinIO console at http://localhost:9001

Activity Timeouts

Increase timeout in workflow:

await workflow.execute_activity(
    "my_activity",
    args,
    start_to_close_timeout=timedelta(hours=2)  # Increase from default
)

Best Practices

1. Keep Dockerfiles lean: Only install necessary tools
2. Use multi-stage builds: Reduce final image size
3. Pin tool versions: Ensure reproducibility
4. Log liberally: Helps debugging workflow issues
5. Handle errors gracefully: Don't fail workflow for non-critical issues
6. Test locally first: Use docker-compose before deploying

On-Demand Worker Management

Workers use Docker Compose profiles and CLI-managed lifecycle for resource optimization.

How It Works

1. Build Time: docker-compose build creates all worker images
2. Startup: Workers DON'T auto-start with docker-compose up -d
3. On Demand: CLI starts workers automatically when workflows need them
4. Shutdown: Optional auto-stop after workflow completion

Manual Control

# Start specific worker
docker start fuzzforge-worker-ossfuzz

# Stop specific worker
docker stop fuzzforge-worker-ossfuzz

# Check worker status
docker ps --filter "name=fuzzforge-worker"

CLI Auto-Management

# Auto-start enabled by default
ff workflow run ossfuzz_campaign . project_name=zlib

# Disable auto-start
ff workflow run ossfuzz_campaign . project_name=zlib --no-auto-start

# Auto-stop after completion
ff workflow run ossfuzz_campaign . project_name=zlib --wait --auto-stop

Resource Savings

• Before: All workers running = ~8GB RAM
• After: Only core services running = ~1.2GB RAM
• Savings: ~6-7GB RAM when idle

Examples

See existing verticals for examples:

• workers/rust/ - Complete working example
• backend/toolbox/workflows/rust_test/ - Simple test workflow