Rajai Nasser

56 papers A* 5B 16Journal 34
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Marissa A. Weis, Maciej Wolczyk, Rajai Nasser, Rif A. Saurous, Blaise Agüera y Arcas, João Sacramento, Alexander Meulemans
2025 J jnl
CoRR
Alexander Meulemans, Rajai Nasser, Maciej Wolczyk, Marissa A. Weis, Seijin Kobayashi, Blake A. Richards, Guillaume Lajoie, Angelika Steger, Marcus Hutter, James Manyika, Rif A. Saurous, João Sacramento, Blaise Agüera y Arcas
2024 A* conf
ICML
Vincent Cohen-Addad, Tommaso d'Orsi, Silvio Lattanzi, Rajai Nasser
2024 J jnl
CoRR
Vincent Cohen-Addad, Tommaso d'Orsi, Silvio Lattanzi, Rajai Nasser
2023 A* conf
SODA
Tommaso d'Orsi, Rajai Nasser, Gleb Novikov, David Steurer
2022 B conf
ISIT
Rajai Nasser, Ibrahim Issa, Ibrahim C. Abou-Faycal
2022 J jnl
CoRR
Rajai Nasser, Ibrahim Issa, Ibrahim C. Abou-Faycal
2022 J jnl
CoRR
Tommaso d'Orsi, Rajai Nasser, Gleb Novikov, David Steurer
2022 J jnl
IEEE Trans. Inf. Theory
Elie Najm, Emre Telatar, Rajai Nasser
2022 A* conf
COLT
Rajai Nasser, Stefan Tiegel
2022 J jnl
CoRR
Rajai Nasser, Stefan Tiegel
2021 A* conf
NeurIPS
Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel
2021 J jnl
CoRR
Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel
2021 A* conf
FOCS
Jingqiu Ding, Tommaso d'Orsi, Rajai Nasser, David Steurer
2021 J jnl
CoRR
Jingqiu Ding, Tommaso d'Orsi, Rajai Nasser, David Steurer
2020 J jnl
IEEE Trans. Inf. Theory
Elie Najm, Rajai Nasser, Emre Telatar
2019 B conf
ISIT
Rajai Nasser
2019 B conf
ISIT
Rajai Nasser
2019 B conf
ISIT
Elie Najm, Emre Telatar, Rajai Nasser
2019 J jnl
CoRR
Elie Najm, Emre Telatar, Rajai Nasser
2018 J jnl
IEEE Trans. Inf. Theory
Rajai Nasser
2018 B conf
ISIT
Elie Najm, Rajai Nasser, Emre Telatar
2018 J jnl
CoRR
Elie Najm, Rajai Nasser, Emre Telatar
2018 J jnl
Entropy
Rajai Nasser
2018 J jnl
CoRR
Rajai Nasser
2018 J jnl
CoRR
Rajai Nasser
2018 J jnl
IEEE Trans. Inf. Theory
Rajai Nasser, Joseph M. Renes
2018 J jnl
Entropy
Rajai Nasser
2017 J jnl
CoRR
Rajai Nasser
2017 B conf
ISIT
Rajai Nasser
2017 J jnl
IEEE Trans. Inf. Theory
Rajai Nasser
2017 J jnl
CoRR
Rajai Nasser
2017 B conf
ISIT
Rajai Nasser
2017 J jnl
IEEE Trans. Inf. Theory
Rajai Nasser, Emre Telatar
2017 J jnl
CoRR
Rajai Nasser
2017 B conf
ISIT
Rajai Nasser
2017 J jnl
CoRR
Rajai Nasser, Joseph M. Renes
2017 B conf
ISIT
Rajai Nasser, Joseph M. Renes
2017
Rajai Nasser
2017 J jnl
CoRR
Rajai Nasser
2017 B conf
ISIT
Rajai Nasser
2016 J jnl
CoRR
Elie Najm, Rajai Nasser
2016 B conf
ISIT
Elie Najm, Rajai Nasser
2016 J jnl
IEEE Trans. Inf. Theory
Rajai Nasser
2016 J jnl
CoRR
Rajai Nasser
2016 B conf
ISIT
Rajai Nasser
2016 J jnl
IEEE Trans. Inf. Theory
Rajai Nasser, Emre Telatar
2015 B conf
ISIT
Rajai Nasser
2015 B conf
ISIT
Rajai Nasser
2015 J jnl
CoRR
Rajai Nasser, Emre Telatar
2015 B conf
ISIT
Rajai Nasser, Emre Telatar
2014 J jnl
CoRR
Rajai Nasser
2014 J jnl
CoRR
Rajai Nasser
2013 J jnl
CoRR
Rajai Nasser, Emre Telatar
2013 B conf
ISIT
Rajai Nasser, Emre Telatar
2011 J jnl
CoRR
Rajai Nasser
Docker-README.md
← Index Docker-README.md markdown
# REDB Docker Setup

This document describes the Docker containerization for the REDB malware analysis framework.

## Overview

REDB has been containerized as a single unified image that supports both feature extraction and decompilation analysis. The container is stateless, processes files from S3 or local mounts, and exports results to ClickHouse database or via API callbacks.

## Architecture

- **Single Unified Container**: One image handles both feature extraction and decompilation
- **Runtime Tool Installation**: Tools (CAPA, DIE, Binary Ninja) installed at runtime from host snapshots
- **Stateless Processing**: No persistent storage required between runs
- **Multiple Invocation Modes**: Supports `--nomad-job`, `--s3`, `--s3-solo`, and `--path` modes
- **External Dependencies**: Connects to external ClickHouse and S3 services

## Files Structure

```
├── Dockerfile                 # Single unified container definition
├── docker-build.sh            # Build script with Docker Desktop bug workaround
├── docker-push.sh             # Push script to registry
├── test-docker.sh             # Container testing script
├── test-nomad.sh              # Nomad job mode testing
├── .dockerignore              # Build context exclusions
└── scripts/
    └── setup-and-run.sh       # Runtime tool setup entrypoint
```

## Tool Installation Strategy

The container uses a **runtime installation** approach:

1. **Base Image**: Contains Python dependencies and REDB code
2. **Runtime Setup**: `scripts/setup-and-run.sh` configures tools at container start
3. **Host Snapshots**: Binary Ninja installed from `/opt/binaryninja` if available
4. **System Tools**: CAPA and DIE expected at `/usr/bin/capa` and `/usr/bin/nfdc`

## Build and Run

### 1. Build Container

```bash
# Build unified image
./docker-build.sh

# Manual build
docker build --platform linux/amd64 -f Dockerfile -t redb:latest .
```

### 2. Run Modes

#### Nomad Job Mode (Primary)
```bash
# Feature extraction
docker run --rm \
  -e JOB_ID="analysis_001" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="feature_extraction" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="BasicPropertiesExtractor,PEFeaturesExtractor" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e S3_ACCESS_KEY="your-key" \
  -e S3_SECRET_KEY="your-secret" \
  redb:latest python3 start.py --nomad-job

# Decompilation (same container, different flags)
docker run --rm \
  -e JOB_ID="analysis_002" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="decompilation" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="all" \
  -v /opt/binaryninja:/opt/binaryninja:ro \
  redb:latest python3 start.py --nomad-job --decompile
```

#### S3 Solo Mode
```bash
# Process single sample by S3 key (standard sharded path)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Process private sample (with prepath)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

#### Local Files Mode
```bash
# Mount local samples
docker run --rm \
  -v /path/to/samples:/samples:ro \
  -v ./logs:/app/logs \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  redb:latest python3 start.py --path /samples --repo local_test --index_prefix redb
```

## Environment Variables

### Required for Nomad Job Mode
- `JOB_ID` - Unique job identifier
- `S3_KEY` - S3 object key for sample
- `S3_BUCKET` - S3 bucket name
- `WORKER_TYPE` - "feature_extraction" or "decompilation"
- `CALLBACK_URL` - API endpoint for results
- `ANALYSIS_MODULES` - Comma-separated extractor list or "all"

### Database Configuration
- `CLICKHOUSE_HOST` - ClickHouse server hostname
- `CLICKHOUSE_PORT` - Port (default: 8123)
- `CLICKHOUSE_USER` - Database user (default: default)
- `CLICKHOUSE_PASSWORD` - Database password
- `CLICKHOUSE_DATABASE` - Database name (default: default)

### S3 Configuration
- `S3_ENDPOINT` - S3 endpoint URL
- `S3_ACCESS_KEY` - S3 access key
- `S3_SECRET_KEY` - S3 secret key
- `S3_SECURE` - "true" or "false" for HTTPS

### Processing Configuration
- `INDEX_PREFIX` - Database table prefix (default: redb)
- `REPO` - Repository identifier for this analysis batch
- `BATCH_SIZE` - Processing batch size (default: 10)
- `REDB_TIMEOUT` - Analysis timeout in seconds (default: 300)

### Tool Timeouts
- `CAPA_TIMEOUT` - CAPA analysis timeout (default: 300)
- `DIE_TIMEOUT` - DIE analysis timeout (default: 180)
- `BINJA_TIMEOUT` - Binary Ninja timeout (default: 1200)
- `DECOMPILE_EXTRACTOR_TIMEOUT` - Decompilation timeout (default: 2580)

## Binary Ninja Setup

For decompilation capabilities, mount Binary Ninja from host:

```bash
# Mount Binary Ninja installation
-v /opt/binaryninja:/opt/binaryninja:ro

# Mount license file
-v /path/to/license.dat:/home/analyzer/.binaryninja/license.dat:ro
```

The container will automatically detect and configure Binary Ninja at runtime.

## Registry Deployment

### Push to Registry
```bash
# Tag and push
./docker-push.sh

# Or manually
docker tag redb:latest your-registry/redb:latest
docker push your-registry/redb:latest
```

### Pull and Run
```bash
docker pull your-registry/redb:latest
docker run your-registry/redb:latest python3 start.py --nomad-job
```

## Testing

### Container Functionality Test
```bash
# Test with S3 key (standard sharded path)
./test-docker.sh "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Test with private sample S3 key
./test-docker.sh "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

### Nomad Job Architecture Test
```bash
# Test Nomad job mode
./test-nomad.sh
```

## Development

### Interactive Container
```bash
# Debug container interactively
docker run -it --entrypoint /bin/bash redb:latest

# Check tool availability
docker run --rm redb:latest which python3
docker run --rm redb:latest ls -la /usr/bin/capa
```

### Build Troubleshooting

The build script includes workarounds for Docker Desktop bugs:

```bash
# If build hangs at "exporting to image", press Ctrl+C
# The image will still be created and tagged automatically
./docker-build.sh
```

### Container Logs
```bash
# View logs from mounted directory
docker run -v ./logs:/app/logs redb:latest python3 start.py --path /samples
tail -f logs/*.txt
```

## Production Notes

### Resource Requirements
- **Memory**: 2-4GB recommended (8GB for decompilation)
- **CPU**: 2+ cores recommended
- **Disk**: Minimal (stateless container)
- **Network**: Access to ClickHouse and S3 services

### Security
- Container runs as non-root user `analyzer` (UID 1000)
- Sample files should be mounted read-only
- No persistent state between container runs
- Isolated processing environment for malware analysis

### Deployment Architecture

This container is designed for:
- **Nomad job dispatch**: Single-use containers processing one sample each
- **Kubernetes jobs**: Batch processing with external orchestration
- **CI/CD pipelines**: Automated analysis in build systems
- **Development**: Local testing and debugging

The unified container approach means the same image handles both feature extraction and decompilation - the difference is only in the command-line flags used when starting the container.