Waqas Ali

35 papers C 4Misc 1Journal 27Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
PeerJ Comput. Sci.
Waqas Ali, Zeeshan Ramzan, Muhammad Shahbaz, Qamar Ul Zaman Bhutta, Muhammad Talha, Mohammed J. AlGhamdi
2026 J jnl
IEEE Robotics Autom. Lett.
Waqas Ali, Yixi Cai, Patric Jensfelt, Thien-Minh Nguyen
2026 J jnl
IEEE Access
Waqas Ali, Ara Bissal, Martin März
2026 J jnl
Knowl. Inf. Syst.
Waqas Ali, Bin Yao
2025 J jnl
IEEE Trans. Consumer Electron.
Waqas Ali, Muhammad Amin, Fawaz Khaled Alarfaj, Yasser D. Al-Otaibi, Sajid Anwar
2025 J jnl
Multiagent Grid Syst.
Hanaa Nafea, Awais Qasim, Syed Mustaghees Abbas, Waqas Ali
2025 J jnl
IEEE Access
Usman Ali, Muhammad Umer Ramzan, Waqas Ali, Khaled Al Jaafari
2025 J jnl
PeerJ Comput. Sci.
Waqas Ali, Wesam H. Al-Sabban, Muhammad Shahbaz, Ali Al-Laith, Bassam Almogadwy
2025 J jnl
Int. J. Inf. Comput. Secur.
Muhammad Kashif Azhar, Bin Yao, Muhammad Imran, Waqas Ali
2025 J jnl
CoRR
Usman Ali, Ali Zia, Waqas Ali, Muhammad Umer Ramzan, Abdul Rehman, Muhammad Tayyab Chaudhry, Wei Xiang
2025 J jnl
IEEE Access
Waqas Ali, Nizam-Uddin, Muhammad Zahid, Sultan Shoaib
2025 J jnl
Multiagent Grid Syst.
Hadia Noor, Muhammad Shahbaz, Waqas Ali
2024 J jnl
CoRR
Usman Ali, Waqas Ali, Muhammad Umer Ramzan
2024 J jnl
Complex Intell. Syst.
Jawad Ali, Waqas Ali, Haifa Alqahtani, Muhammed I. Syam
2024 conf
ITSC
Waqas Ali, Patric Jensfelt, Thien-Minh Nguyen
2024 J jnl
CoRR
Waqas Ali, Patric Jensfelt, Thien-Minh Nguyen
2024 J jnl
CoRR
Usman Ali, Sahil Ranmbail, Muhammad Nadeem, Hamid Ishfaq, Muhammad Umer Ramzan, Waqas Ali
2024 J jnl
J. Softw. Evol. Process.
Waqas Ali, Lili Bo, Xiaobing Sun, Xiaoxue Wu, Aakash Ali, Ying Wei
2023 J jnl
Int. J. Data Anal. Tech. Strateg.
Waqas Ali, Muhammad Saleem, Abdul Khaliq, Amanullah Yasin
2023 J jnl
Expert Syst. Appl.
Waqas Ali, Lili Bo, Xiaobing Sun, Xiaoxue Wu, Saifullah Memon, Saima Siraj, Ann Suwaree Ashton
2023 C conf
IECON
Fermín Gómez De León, Kedar Joshi, Ara Bissal, Waqas Ali, Maurizio Repetto
2022 J jnl
VLDB J.
Waqas Ali, Muhammad Saleem, Bin Yao, Aidan Hogan, Axel-Cyrille Ngonga Ngomo
2022 J jnl
IEEE Access
Muhammad Imran, Bin Yao, Waqas Ali, Adnan Akhunzada, Muhammad Kashif Azhar, Muhammad Junaid, Uzair Iqbal
2021 J jnl
CoRR
Waqas Ali, Peilin Liu, Rendong Ying, Zheng Gong
2021 J jnl
CoRR
Waqas Ali, Muhammad Saleem, Bin Yao, Aidan Hogan, Axel-Cyrille Ngonga Ngomo
2021 J jnl
CoRR
Waqas Ali, Peilin Liu, Rendong Ying, Zheng Gong
2021 C conf
IECON
Vishal K. A. Kushalappa, Ibrahim Elsabrouty, Waqas Ali, Ilknur Colak
2021 J jnl
Intell. Autom. Soft Comput.
Abdul Ghaffar, Saad Awadh Alanazi, Madallah Alruwaili, Mian Usman Sattar, Waqas Ali, Memoona Humayun, Shahan Yamin Siddiqui, Fahad Ahmad, Muhammad Adnan Khan
2021 C conf
IECON
Ahmed Meligy, Taoufik Qoria, Waqas Ali, Ilknur Colak
2020 J jnl
IEEE Access
Adnan Abid, Waqas Ali, Muhammad Shoaib Farooq, Uzma Farooq, Nabeel Sabir, Kamran Abid
2019 J jnl
Sensors
Muhammad Adeel Akram, Peilin Liu, Muhammad Owais Tahir, Waqas Ali, Yuze Wang
2019 Misc conf
FIT
Waqas Ali, Ghulam Abbas, Ziaul Haq Abbas
2017 conf
INTELLECT
Waqas Ali, Haroon Farooq, Atta Ur Rehman, Mohamed Emad Farrag
2014 conf
IFIP Int. Conf. Digital Forensics
Ahmad Raza Cheema, Mian Muhammad Waseem Iqbal, Waqas Ali
2010 C conf
ISDA
Sunila Saqib, Umair Bin Ali, Waqas Ali, Shoab A. Khan
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.