Venkata Ramana Rao Gadde

18 papers A 9C 1Journal 4Unranked 4
YearRankTypeTitle / Venue / Authors
2013 A conf
INTERSPEECH
Yongxin Taylor Xi, Matthias Paulik, Venkata Ramana Rao Gadde, Ananth Sankar
2007 J jnl
EURASIP J. Audio Speech Music. Process.
Rajesh M. Hegde, Hema A. Murthy, Venkata Ramana Rao Gadde
2007 J jnl
IEEE Trans. Speech Audio Process.
Rajesh M. Hegde, Hema A. Murthy, Venkata Ramana Rao Gadde
2007 A conf
INTERSPEECH
Dimitra Vergyri, Izhak Shafran, Andreas Stolcke, Venkata Ramana Rao Gadde, Murat Akbacak, Brian Roark, Wen Wang
2006 J jnl
IEEE Trans. Speech Audio Process.
Andreas Stolcke, Barry Y. Chen, Horacio Franco, Venkata Ramana Rao Gadde, Martin Graciarena, Mei-Yuh Hwang, Katrin Kirchhoff, Arindam Mandal, Nelson Morgan, Xin Lei, Tim Ng, Mari Ostendorf, M. Kemal Sönmez, Anand Venkataraman, Dimitra Vergyri, Wen Wang, Jing Zheng, Qifeng Zhu
2006 conf
ICASSP (5)
Shrikanth S. Narayanan, Panayiotis G. Georgiou, Abhinav Sethy, Dagen Wang, Murtaza Bulut, Shiva Sundaram, Emil Ettelaie, Sankaranarayanan Ananthakrishnan, Horacio Franco, Kristin Precoda, Dimitra Vergyri, Jing Zheng, Wen Wang, Venkata Ramana Rao Gadde, Martin Graciarena, Victor Abrash, Michael W. Frandsen, Colleen Richey
2005 A conf
INTERSPEECH
Dimitra Vergyri, Katrin Kirchhoff, Venkata Ramana Rao Gadde, Andreas Stolcke, Jing Zheng
2004 A conf
INTERSPEECH
Anand Venkataraman, Andreas Stolcke, Wen Wang, Dimitra Vergyri, Jing Zheng, Venkata Ramana Rao Gadde
2004 A conf
INTERSPEECH
Rajesh Mahanand Hegde, Hema A. Murthy, Venkata Ramana Rao Gadde
2004 conf
ISCSLP
Mei-Yuh Hwang, Xin Lei, Tim Ng, Ivan Bulyko, Mari Ostendorf, Andreas Stolcke, Wen Wang, Jing Zheng, Venkata Ramana Rao Gadde, Martin Graciarena, Man-Hung Siu, Yan Huang
2004 A conf
INTERSPEECH
Hema A. Murthy, Rajesh Mahanand Hegde, Venkata Ramana Rao Gadde
2003 C conf
ISI
Sachin S. Kajarekar, M. Kemal Sönmez, Luciana Ferrer, Venkata Ramana Rao Gadde, Anand Venkataraman, Elizabeth Shriberg, Andreas Stolcke, Harry Bratt
2003 A conf
INTERSPEECH
Luciana Ferrer, Harry Bratt, Venkata Ramana Rao Gadde, Sachin S. Kajarekar, Elizabeth Shriberg, M. Kemal Sönmez, Andreas Stolcke, Anand Venkataraman
2003 conf
ICASSP (1)
Dimitra Vergyri, Andreas Stolcke, Venkata Ramana Rao Gadde, Luciana Ferrer, Elizabeth Shriberg
2002 A conf
INTERSPEECH
Venkata Ramana Rao Gadde, Andreas Stolcke, Dimitra Vergyri, Jing Zheng, M. Kemal Sönmez, Anand Venkataraman
2002 J jnl
Speech Commun.
Ananth Sankar, Venkata Ramana Rao Gadde, Andreas Stolcke, Fuliang Weng
2000 A conf
INTERSPEECH
Venkata Ramana Rao Gadde
1999 conf
EUROSPEECH
Ananth Sankar, Venkata Ramana Rao Gadde
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` |