Kai Gao

35 papers A* 6A 1B 6Journal 15Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Inf.
Qiao Li, Kai Gao
2025 J jnl
IEEE Trans. Dependable Secur. Comput.
Shenshen Chen, Jian Luo, Dong Guo, Kai Gao, Yang Richard Yang
2024 J jnl
Comput. Networks
Jie Chen, Jian Luo, Kai Gao
2024 J jnl
RFC
Kai Gao, Roland Schott, Yang Richard Yang, Lauren Delwiche, Lachlan Keller
2024 J jnl
IEEE Commun. Mag.
Berta Serracanta, Kai Gao, Jordi Ros-Giralt, Alberto Rodríguez-Natal, Luis Contreras, Yang Richard Yang, Albert Cabellos
2024 J jnl
CoRR
Berta Serracanta, Kai Gao, Jordi Ros-Giralt, Alberto Rodríguez-Natal, Luis M. Contreras, Y. Richard Yang, Albert Cabellos
2023 A* conf
SIGCOMM
Dong Guo, Jian Luo, Kai Gao, Y. Richard Yang
2022 J jnl
RFC
Wendy Roome, Sabine Randriamasy, Yang Richard Yang, Jingxuan Jensen Zhang, Kai Gao
2022 J jnl
RFC
Kai Gao, Young Lee, Sabine Randriamasy, Yang Richard Yang, Jingxuan Jensen Zhang
2022 A* conf
SIGCOMM
Dong Guo, Shenshen Chen, Kai Gao, Qiao Xiang, Ying Zhang, Y. Richard Yang
2022 J jnl
IEEE/ACM Trans. Netw.
Zhaowei Xi, Yu Zhou, Dai Zhang, Kai Gao, Chen Sun, Jiamin Cao, Yangyang Wang, Mingwei Xu, Jianping Wu
2022 conf
NAI@SIGCOMM
Jacob Dunefsky, Mahdi Soleimani, Ryan Yang, Jordi Ros-Giralt, Mario Lassnig, Inder Monga, Frank K. Würthwein, Jingxuan Zhang, Kai Gao, Y. Richard Yang
2021 conf
NAI@SIGCOMM
Kai Gao
2021 B conf
IM
Jingxuan Zhang, Luis M. Contreras, Kai Gao, Francisco Cano, Patricia Cano, Anais Escribano, Yang Richard Yang
2020 conf
NAI@SIGCOMM
Kai Gao, Luis M. Contreras, Sabine Randriamasy
2020 J jnl
IEEE J. Sel. Areas Commun.
Yu Zhou, Jun Bi, Tong Yang, Kai Gao, Jiamin Cao, Dai Zhang, Yangyang Wang, Cheng Zhang
2020 conf
ANRW
Danny Alex Lachos Perez, Christian Esteve Rothenberg, Qiao Xiang, Yang Richard Yang, Börje Ohlman, Sabine Randriamasy, Luis M. Contreras, Kai Gao
2020 A conf
CoNEXT
Yu Zhou, Dai Zhang, Kai Gao, Chen Sun, Jiamin Cao, Yangyang Wang, Mingwei Xu, Jianping Wu
2020 J jnl
IEEE/ACM Trans. Netw.
Jingxuan Zhang, Kai Gao, Yang Richard Yang, Jun Bi
2020 A* conf
INFOCOM
Qiao Xiang, Jingxuan Zhang, Kai Gao, Yeon-Sup Lim, Franck Le, Geng Li, Yang Richard Yang
2020 J jnl
IEEE J. Sel. Areas Commun.
Kai Gao, Taishi Nojima, Haitao Yu, Yang Richard Yang
2019 J jnl
IEEE/ACM Trans. Netw.
Kai Gao, Qiao Xiang, Xin Wang, Yang Richard Yang, Jun Bi
2019 conf
SOSR
Christopher Leet, Shenshen Chen, Kai Gao, Yang Richard Yang
2019 J jnl
IEEE J. Sel. Areas Commun.
Menghao Zhang, Jun Bi, Kai Gao, Yi Qiao, Guanyu Li, Xiao Kong, Zhaogeng Li, Hongxin Hu
2018 conf
APNet
Zhilong Zheng, Jun Bi, Chen Sun, Heng Yu, Hongxin Hu, Zili Meng, Shuhe Wang, Kai Gao, Jianping Wu
2018 B conf
ICNP
Zhilong Zheng, Jun Bi, Haiping Wang, Chen Sun, Heng Yu, Hongxin Hu, Kai Gao, Jianping Wu
2018 B conf
ICNP
Yu Zhou, Jun Bi, Tong Yang, Kai Gao, Cheng Zhang, Jiamin Cao, Yangyang Wang
2018 A* conf
INFOCOM
Kai Gao, Jingxuan Zhang, Yang Richard Yang, Jun Bi
2018 A* conf
SIGCOMM
Kai Gao, Taishi Nojima, Yang Richard Yang
2017 B conf
IWQoS
Kai Gao, Qiao Xiang, Xin Wang, Yang Richard Yang, Jun Bi
2017 conf
SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI
Qiao Xiang, Shenshen Chen, Kai Gao, Harvey B. Newman, Ian J. Taylor, Jingxuan Zhang, Yang Richard Yang
2016 A* conf
SIGCOMM
Kai Gao, Chen Gu, Qiao Xiang, Yang Richard Yang, Jun Bi
2016 B conf
ICNP
Kai Gao, Chen Gu, Qiao Xiang, Xin Wang, Yang Richard Yang, Jun Bi
2015 J jnl
IEEE Trans. Netw. Serv. Manag.
Yonghong Fu, Jun Bi, Ze Chen, Kai Gao, Baobao Zhang, Guangxu Chen, Jianping Wu
2014 B conf
ICNP
Yonghong Fu, Jun Bi, Kai Gao, Ze Chen, Jianping Wu, Bin Hao
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.