Chandramani Singh

65 papers A* 3A 2B 10C 1Misc 2Journal 31Unranked 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Ankita Koley, Anu Krishna, Chandramani Singh, V. Mahendran
2026 J jnl
IEEE Trans. Netw.
Ankita Koley, Chandramani Singh
2026 J jnl
IEEE Trans. Mob. Comput.
S. Arthi, Neelesh B. Mehta, Chandramani Singh
2025 B conf
WiOpt
Aniket Mukherjee, Joy Kuri, Chandramani Singh
2025 J jnl
CoRR
Aniket Mukherjee, Joy Kuri, Chandramani Singh
2025 conf
TMA
Joydeep Pal, Sruthi G. S, T. V. Prabhakar, Chandramani Singh
2025 J jnl
IEEE Trans. Mob. Comput.
Vinay U. Pai, Neelesh B. Mehta, Chandramani Singh
2025 J jnl
CoRR
Harsha Yelchuri, Diwakar Kumar Singh, Nithish Krishnabharathi Gnani, T. V. Prabhakar, Chandramani Singh
2024 J jnl
CoRR
Ankita Koley, Chandramani Singh
2024 conf
INFOCOM (Workshops)
Nithish Krishnabharathi Gnani, Joydeep Pal, Deepak Choudhary, Himanshu Verma, Soumya Kanta Rana, Kaushal S. Mhapsekar, T. V. Prabhakar, Chandramani Singh
2024 J jnl
CoRR
Ankita Koley, Chandramani Singh
2024 J jnl
Perform. Evaluation
Ankita Koley, Chandramani Singh
2024 conf
ICC
Vinay U. Pai, Neelesh B. Mehta, Chandramani Singh
2024 conf
CASE
Amal Roy, Chandramani Singh, Y. Narahari
2024 conf
INFOCOM (Workshops)
Joydeep Pal, Deepak Choudhary, Nithish Krishnabharathi Gnani, T. V. Prabhakar, Chandramani Singh, Hari Krishna Atluri, Arumugam Paventhan
2024 conf
VALUETOOLS
Anu Krishna, Ankita Koley, Chandramani Singh
2023 conf
ICCCNT
Laxmi Vatsalya Daita, Manoj Kumar Panda, Chandramani Singh
2023 conf
VALUETOOLS
K. J. Pavamana, Chandramani Singh
2023 B conf
WiOpt
Anu Krishna, Chandramani Singh
2023 J jnl
CoRR
Nithish Krishnabharathi Gnani, Joydeep Pal, Deepak Choudhary, Himanshu Verma, Soumya Kanta Rana, Kaushal Mhapsekar, Tamma V. Prabhakar, Chandramani Singh
2023 C conf
LANMAN
Soumya Kanta Rana, Himanshu Verma, Joydeep Pal, Deepak Choudhary, T. V. Prabhakar, Chandramani Singh
2023 conf
Q2SWinet
Rushabha Balaji, Neelesh B. Mehta, Chandramani Singh
2023 J jnl
ACM Trans. Model. Perform. Evaluation Comput. Syst.
Ashok Krishnan K. S., Chandramani Singh, Siva Theja Maguluri, Parimal Parag
2023 A conf
ITC
Ankita Koley, Chandramani Singh
2023 J jnl
IEEE Trans. Netw. Serv. Manag.
Haritha K, Chandramani Singh
2023 J jnl
CoRR
Joydeep Pal, Deepak Choudhary, Nithish Krishnabharathi Gnani, Chandramani Singh, T. Venkata Prabhakar
2022 J jnl
IEEE Trans. Netw. Serv. Manag.
Kurian Polachan, Joydeep Pal, Chandramani Singh, Prabhakar Venkata Tamma
2022 J jnl
ACM Trans. Internet Techn.
Kurian Polachan, Chandramani Singh, Tamma V. Prabhakar
2022 J jnl
Perform. Evaluation
Ashok Krishnan K. S., Chandramani Singh, Siva Theja Maguluri, Parimal Parag
2022 J jnl
CoRR
Amal Roy, Chandramani Singh, Y. Narahari
2022 J jnl
CoRR
Haritha K, Chandramani Singh
2022 J jnl
CoRR
Ramya Burra, Chandramani Singh, Joy Kuri
2022 J jnl
Perform. Evaluation
Ramya Burra, Chandramani Singh, Joy Kuri
2022 J jnl
CoRR
Haritha K, Vineeth Bala Sukumaran, Chandramani Singh
2022 J jnl
Perform. Evaluation
Vineeth Bala Sukumaran, Chandramani Singh
2022 J jnl
IEEE/ACM Trans. Netw.
Kurian Polachan, Joydeep Pal, Chandramani Singh, Prabhakar Venkata Tamma, Fernando A. Kuipers
2021 conf
ANTS
Sahil Bhandary Karnoor, Prahadheeswaran Mathiyazhagan, Haresh Dagale, Chandramani Singh
2021 B conf
WiOpt
Anu Krishna, Ramya Burra, Chandramani Singh
2021 B conf
IM
Kurian Polachan, Chandramani Singh, Prabhakar T. V
2021 J jnl
CoRR
Ashok Krishnan K. S., Chandramani Singh, Siva Theja Maguluri, Parimal Parag
2021 J jnl
IEEE Trans. Netw. Sci. Eng.
Ramya Burra, Chandramani Singh, Joy Kuri
2021 J jnl
CoRR
Ramya Burra, Chandramani Singh, Joy Kuri
2020 conf
ICCPS
Kurian Polachan, Belma Turkovic, Prabhakar T. Venkata, Chandramani Singh, Fernando A. Kuipers
2020 B conf
WiOpt
Ashok Krishnan K. S., Chandramani Singh, Siva Theja Maguluri, Parimal Parag
2019 A conf
ITC
Haritha K, Chandramani Singh
2019 conf
Allerton
Ramya Burra, Chandramani Singh, Joy Kuri
2019 B conf
SECON
Kurian Polachan, Prabhakar T. Venkata, Chandramani Singh, Deepak Panchapakesan
2019 J jnl
CoRR
Kurian Polachan, Joydeep Pal, Chandramani Singh, Prabhakar T. V
2019 conf
Allerton
Haritha K, Chandramani Singh
2019 A* conf
INFOCOM
Ramya Burra, Chandramani Singh, Joy Kuri
2019 Misc conf
COMSNETS
Kurian Polachan, Prabhakar T. V, Chandramani Singh, Fernando A. Kuipers
2018 conf
LION
Akshita Bhandari, Chandramani Singh
2018 J jnl
CoRR
Akshita Bhandari, Chandramani Singh
2018 conf
EITEC@CPSWeek
Arjun N, Ashwin S. M, Kurian Polachan, Prabhakar T. Venkata, Chandramani Singh
2018 B conf
WiOpt
Haritha K, Chandramani Singh
2018 B conf
WiOpt
Vineeth Bala Sukumaran, Chandramani Singh
2017 J jnl
IEEE Access
Daniel van den Berg, Rebecca Glans, Dorian De Koning, Fernando A. Kuipers, Jochem Lugtenburg, Kurian Polachan, Prabhakar T. Venkata, Chandramani Singh, Belma Turkovic, Bryan Van Wijk
2017 B conf
WiOpt
R. Divya, Amar Prakash Azad, Chandramani Singh
2017 Misc conf
COMSNETS
Sarath Yasodharan, Vineeth Bala Sukumaran, Chandramani Singh
2014 A* conf
INFOCOM
François Baccelli, Bartlomiej Blaszczyszyn, Chandramani Singh
2014 A* conf
INFOCOM
Chandramani Singh, Angelia Nedic, R. Srikant
2014 conf
CDC
Chandramani Singh, Angelia Nedic, R. Srikant
2013 J jnl
CoRR
François Baccelli, Chandramani Singh
2013 B conf
WiOpt
François Baccelli, Chandramani Singh
2013 J jnl
CoRR
François Baccelli, Bartlomiej Blaszczyszyn, Chandramani Singh
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.