Hailin Zou

30 papers Journal 20Unranked 10
YearRankTypeTitle / Venue / Authors
2025 J jnl
Eng. Appl. Artif. Intell.
Zijie Chen, Hailin Zou, Tao Hu, Xiaofen Fang, Jiexin Zheng, Jianqing Li, Yuanyuan Pan
2025 J jnl
J. Comput. Methods Sci. Eng.
Hailin Zou, Qinlan Wu, Zhicheng Wen
2025 J jnl
Comput. Secur.
Zijie Chen, Hailin Zou, Tao Hu, Xun Yuan, Xiaofen Fang, Yuanyuan Pan, Jianqing Li
2024 J jnl
Sensors
Jing Zhang, Guocai Zhang, Zijie Chen, Hailin Zou, Shuai Xue, Jianjie Deng, Jianqing Li
2024 J jnl
IEEE Trans. Emerg. Top. Comput. Intell.
Hailin Zou, Zijie Chen, Jing Zhang, Lei Wang, Fuchun Zhang, Jianqing Li, Yuanyuan Pan
2023 conf
ICCIP
Binbin Wang, Anran Yuan, Hailin Zou, Zijie Chen, Jianqing Li
2023 J jnl
IEEE ACM Trans. Comput. Biol. Bioinform.
Zhengsen Pan, Shusen Zhou, Hailin Zou, Chanjuan Liu, Mujun Zang, Tong Liu, Qingjun Wang
2020 J jnl
IEEE Access
Shusen Zhou, Hailin Zou, Chanjuan Liu, Mujun Zang, Tong Liu
2018 J jnl
Expert Syst. Appl.
Mujun Zang, Dunwei Wen, Tong Liu, Hailin Zou, Chanjuan Liu
2018 J jnl
Int. J. Grid Util. Comput.
Chanjuan Liu, Tongtong Chen, Hailin Zou, Xinmiao Ding, Yuling Wang
2016 J jnl
Multim. Tools Appl.
Chanjuan Liu, Tongtong Chen, Xinmiao Ding, Hailin Zou, Yan Tong
2016 J jnl
Int. J. Grid Util. Comput.
Ying Liu, Chanjuan Liu, Hailin Zou
2016 J jnl
Int. J. Commun. Networks Distributed Syst.
Hailin Zou, Chanjuan Liu, Qian Shen, Shusen Zhou, Mujun Zang
2016 J jnl
计算机科学
Tongtong Chen, Xinmiao Ding, Chanjuan Liu, Hailin Zou, Shusen Zhou, Ying Liu
2015 conf
INCoS
Qian Shen, Chanjuan Liu, Hailin Zou, Shusen Zhou, Tongtong Chen
2015 conf
BWCCA
Tongtong Chen, Chanjuan Liu, Xinmiao Ding, Hailin Zou, Qian Shen, Ying Liu
2015 conf
INCoS
Ying Liu, Chanjuan Liu, Hailin Zou, Shusen Zhou, Qian Shen, Tongtong Chen
2015 J jnl
J. Ambient Intell. Humaniz. Comput.
Chanjuan Liu, Hailin Zou, Caixia Li, Ying Liu, Yilei Wang, Shixiang Jia, Shusen Zhou
2015 J jnl
IEEE Trans. Syst. Man Cybern. Syst.
Huixia Liu, Keyi Xing, Weimin Wu, MengChu Zhou, Hailin Zou
2015 J jnl
KSII Trans. Internet Inf. Syst.
Yanping Ma, Hailin Zou, Hongtao Xie, Qingtang Su
2015 conf
BWCCA
Qian Shen, Chanjuan Liu, Hailin Zou, Ying Liu, Tongtong Chen
2015 J jnl
计算机科学
Guangjie Kou, Yunyan Ma, Jun Yue, Hailin Zou
2014 J jnl
Multim. Tools Appl.
Qingtang Su, Yugang Niu, Hailin Zou, Yongsheng Zhao, Tao Yao
2013 J jnl
Appl. Math. Comput.
Qingtang Su, Yugang Niu, Hailin Zou, Xianxi Liu
2013 J jnl
CoRR
Menghui Li, Hailin Zou, Shuguang Guan, Xiaofeng Gong, Kun Li, Zengru Di, Choy Heng Lai
2013 conf
ICIC (2)
Wenjing Tang, Caiming Zhang, Hailin Zou
2013 conf
ITQM
Zhiwang Zhang, Xinseng Li, Hailin Zou, Shiyong Kang, Guangxia Gao
2011 conf
ICAIC (3)
Hailin Zou, Chanjuan Liu
2009 conf
CIS (1)
Hui Shao, Hailin Zou, Yincheng Liang, Wenjun Li, Qian Gao
2007 conf
RSEISP
Xiaofeng Zhang, Yongsheng Zhao, Hailin Zou
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.