Ramanarayanan Viswanathan

36 papers B 1Misc 10Journal 16Unranked 8
YearRankTypeTitle / Venue / Authors
2025 Misc conf
CISS
Lei Cao, Ramanarayanan Viswanathan
2025 J jnl
IEEE Signal Process. Lett.
Lei Cao, Ramanarayanan Viswanathan
2023 Misc conf
CISS
Lei Cao, Ramanarayanan Viswanathan
2023 Misc conf
CISS
Xingjian Sun, Lei Cao, Ramanarayanan Viswanathan
2023 J jnl
CoRR
Lei Cao, Ramanarayanan Viswanathan
2022 J jnl
IEEE Trans. Wirel. Commun.
Lei Cao, Ramanarayanan Viswanathan
2022 J jnl
IEEE Access
Xingjian Sun, Shailee Yagnik, Ramanarayanan Viswanathan, Lei Cao
2021 Misc conf
CISS
Xingjian Sun, Shailee Yagnik, Lei Cao, Ramanarayanan Viswanathan
2021 conf
MILCOM
Xingjian Sun, Lei Cao, Ramanarayanan Viswanathan
2021 conf
WTS
Lei Cao, Ramanarayanan Viswanathan
2021 conf
DySPAN
Sudat Tuladhar, Lei Cao, Ramanarayanan Viswanathan
2021 conf
ICSPCS
Shailee Yagnik, Ramanarayanan Viswanathan, Lei Cao
2020 Misc conf
CISS
Shailee Yagnik, Ramanarayanan Viswanathan, Lei Cao
2019 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Hadi Kasasbeh, Lei Cao, Ramanarayanan Viswanathan
2018 conf
WiSEE
Hadi Kasasbeh, Sushmita Challa, Lei Cao, Ramanarayanan Viswanathan
2018 Misc conf
CogSIMA
Xingjian Sun, Lei Cao, Ramanarayanan Viswanathan
2018 conf
ICC
Adham Hagag, Osama Amin, Lei Cao, Ramanarayanan Viswanathan, Mohamed-Slim Alouini
2018 Misc conf
CogSIMA
Sudat Tuladhar, Lei Cao, Ramanarayanan Viswanathan
2017 B conf
WCNC
Hadi Kasasbeh, Feng Wang, Lei Cao, Ramanarayanan Viswanathan
2017 J jnl
IEEE Signal Process. Lett.
Hadi Kasasbeh, Ramanarayanan Viswanathan, Lei Cao
2017 Misc conf
CISS
Hadi Kasasbeh, Lei Cao, Ramanarayanan Viswanathan
2016 Misc conf
CISS
Roopashree Rajanna, Lei Cao, Ramanarayanan Viswanathan
2016 Misc conf
CISS
Hadi Kasasbeh, Lei Cao, Ramanarayanan Viswanathan
2016 J jnl
J. Electronic Imaging
Saheed Olanigan, Lei Cao, Ramanarayanan Viswanathan
2014 ch.
Computer Vision, A Reference Guide
Ramanarayanan Viswanathan
2014 J jnl
IEEE Trans. Signal Process.
Lei Cao, Ramanarayanan Viswanathan
2011 conf
Integrated Network Management
Anil Mehta, Neda Hantehzadeh, Vijay K. Gurbani, Tin Kam Ho, Jun Koshiko, Ramanarayanan Viswanathan
2000 J jnl
IEEE Trans. Inf. Theory
Viswanath Annampedu, Vladimir V. Roganov, Ramanarayanan Viswanathan
1998 conf
ICC
C. H. Gowda, Viswanath Annampedu, Ramanarayanan Viswanathan
1998 J jnl
IEEE Commun. Lett.
C. H. Gowda, Viswanath Annampedu, Ramanarayanan Viswanathan
1997 J jnl
Proc. IEEE
Ramanarayanan Viswanathan, Pramod K. Varshney
1995 J jnl
IEEE Trans. Inf. Theory
C. H. Gowda, Ramanarayanan Viswanathan
1993 J jnl
IEEE Trans. Inf. Theory
Ramanarayanan Viswanathan
1992 J jnl
IEEE Trans. Signal Process.
Valentine Aalo, Ramanarayanan Viswanathan
1988 J jnl
IEEE Trans. Commun.
Ramanarayanan Viswanathan, Kashfieh Taghizadeh
1984 J jnl
IEEE Trans. Inf. Theory
Ramanarayanan Viswanathan
yara/README.md
← Index yara/README.md markdown
# YARA Rules Directory

This folder contains YARA rules for scanning binary samples.

## Setting Up YARA-Forge Rules

To use the YARA-Forge rules from [https://github.com/YARAHQ/yara-forge](https://github.com/YARAHQ/yara-forge):

```bash
# Download the latest release
cd /path/to/redb/yara
# wget https://github.com/YARAHQ/yara-forge/releases/latest/download/yara-forge-rules-core.zip
wget https://github.com/YARAHQ/yara-forge/releases/latest/download/yara-forge-rules-extended.zip

# Extract rules
# unzip yara-forge-rules-core.zip
unzip yara-forge-rules-extended.zip
```

Available packages:
- `yara-forge-rules-core.zip` - Core rules (~5,000 rules)
- `yara-forge-rules-extended.zip` - Extended rules (~10,000 rules)
- `yara-forge-rules-full.zip` - Full rules (~11,000+ rules)

## Pre-compiling Rules (Recommended for Production)

For large rulesets like YARA-Forge, pre-compiling rules significantly improves startup time:

```bash
# Pre-compile all rules into a single .yarac file
python -m redb.extractors.yara --compile

# Or specify custom paths
python -m redb.extractors.yara --compile --rules-path /path/to/rules --output /path/to/output.yarac
```

This creates `yara/compiled_rules.yarac` which is loaded automatically on subsequent runs.

### Performance Comparison

| Method | First Scan Startup | Subsequent Scans |
|--------|-------------------|------------------|
| Source files (.yar) | ~10-30 seconds (11k rules) | Instant (cached) |
| Pre-compiled (.yarac) | ~1-2 seconds | Instant (cached) |

## Directory Structure

```
yara/
├── README.md
├── .gitkeep
├── compiled_rules.yarac    # (optional) Pre-compiled rules
├── packages/               # YARA-Forge packages
│   └── core/
│       └── *.yar
└── custom/                 # Your custom rules
    └── my_rules.yar
```

Rules are loaded in this priority:
1. `compiled_rules.yarac` (if exists) - fastest
2. All `.yar` and `.yara` files recursively - compiles on first run

## Usage

### Scan with YARA only

```bash
# Scan local files
python start.py --path /path/to/samples -y --repo my_repo --index_prefix redb

# Scan S3 samples
python start.py --s3 --repo bazaar -y --index_prefix redb

# Dry-run (print results instead of storing in ClickHouse)
python start.py --path /path/to/samples -y --dry-run --repo test --index_prefix redb
```

### Scan already-analyzed samples

Run YARA on samples that were previously analyzed (already in `basic_properties`).
Deduplication is handled by the `yara_matches` table — samples already scanned are
automatically excluded before processing begins:

```bash
# Scan all analyzed macho samples with YARA
python start.py --analyzed --magika macho -y --index_prefix redb

# Scan all analyzed PE samples with YARA
python start.py --analyzed --magika pe -y --index_prefix redb

# Scan all analyzed samples (no filetype filter)
python start.py --analyzed -y --index_prefix redb
```

### Partition large YARA runs by date

Combine `--analyzed` with `--range` to partition millions of samples into
manageable batches. Only samples in `basic_properties` AND within the date
range (by `first_seen` in `catalog_samples`) are processed:

```bash
# Scan analyzed PE samples from Feb 2025
python start.py --range 2025-02-01 2025-02-28 --analyzed --magika pebin -y --index_prefix redb

# Scan analyzed PE samples from first week of March 2025
python start.py --range 2025-03-01 2025-03-08 --analyzed --magika pebin -y --index_prefix redb
```

YARA dedup still applies — re-running a range safely skips already-scanned samples.

### Combined Features + YARA

Run feature extraction and YARA scanning together on the same samples:

```bash
# Local files with features + YARA
python start.py --path /path/to/samples --with-yara --repo my_repo --index_prefix redb

# S3 samples with features + YARA
python start.py --s3 --repo bazaar --with-yara --index_prefix redb
```

### Pre-compile Rules

```bash
# Compile and save to default location (yara/compiled_rules.yarac)
python -m redb.extractors.yara --compile

# Compile with custom paths
python -m redb.extractors.yara --compile --rules-path ./my_rules --output ./compiled.yarac
```

### Sync Rules to Database

Before batch scanning, sync rules to ensure all rule metadata is stored:

```bash
# Sync rules to database
python -m redb.extractors.yara --sync-rules

# Sync with custom source collection name
python -m redb.extractors.yara --sync-rules --source-collection yara-forge-core

# Compile and sync in one command
python -m redb.extractors.yara --compile --sync-rules
```

## ClickHouse Table Schema

YARA data uses a **normalized schema** with two tables for efficient storage.

### Matches Table: `yara_matches`

Stores one row per sample-rule match (optimized with binary sha256 and rule_id):

| Column | Type | Description |
|--------|------|-------------|
| sha256 | FixedString(32) | Binary SHA256 (32 bytes, use `hex(sha256)` to display) |
| rule_id | UInt64 | Unique rule identifier (xxHash64 of canonical rule content) |
| rule_name | LowCardinality(String) | YARA rule name (denormalized for convenience) |
| scan_date | DateTime64(3, 'UTC') | Scan timestamp |
| match_strings | Array(String) | Matched string identifiers |

### Rules Table: `yara_rules`

Stores rule metadata once per unique rule (deduplicated by rule_id):

| Column | Type | Description |
|--------|------|-------------|
| rule_id | UInt64 | Unique rule identifier (xxHash64 of canonical rule content) |
| rule_name | String | YARA rule name |
| source_collection | LowCardinality(String) | Source collection (e.g., 'yara-forge-core', 'malpedia') |
| ingested_at | DateTime64(3, 'UTC') | When this rule was ingested |
| rule_text | String | Full rule source code |
| rule_meta | JSON | Rule metadata (author, description, reference, etc.) |
| rule_tags | Array(LowCardinality(String)) | Rule tags |

### Schema Benefits

- **Binary SHA256**: 32 bytes vs 64 bytes (50% storage savings on hash columns)
- **UInt64 rule_id**: Fast joins and lookups via integer key
- **Content-based rule_id**: xxHash64 of canonical rule content (excluding metadata) for deduplication
- **Denormalized rule_name**: Allows queries without joins for common use cases

### Example Queries

```sql
-- Get matches with hex sha256
SELECT
    hex(m.sha256) as sha256,
    m.rule_name,
    m.match_strings
FROM yara_matches m
WHERE m.sha256 = unhex('abc123...')

-- Join with rules for full metadata
SELECT
    hex(m.sha256) as sha256,
    m.rule_name,
    m.match_strings,
    r.rule_meta,
    r.source_collection
FROM yara_matches m
JOIN yara_rules r ON m.rule_id = r.rule_id
WHERE m.sha256 = unhex('abc123...')

-- Find all samples matching a specific rule
SELECT hex(sha256), scan_date
FROM yara_matches
WHERE rule_name = 'APT_Lazarus_Loader'
ORDER BY scan_date DESC
```

## Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| `YARA_RULES_PATH` | Override the YARA rules directory | `yara/` |
| `YARA_COMPILED_RULES` | Compiled rules filename | `compiled_rules.yarac` |
| `YARA_SOURCE_COLLECTION` | Default source collection name | `default` |