Igor Fedorov

58 papers A* 6A 1B 2Misc 4Journal 33Unranked 11
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Hanxian Huang, Igor Fedorov, Andrey Gromov, Bernard Beckerman, Naveen Suda, David Eriksson, Maximilian Balandat, Rylan Conway, Patrick Huber, Chinnadhurai Sankar, Ayushi Dalmia, Zechun Liu, Lemeng Wu, Tarek Elgamal, Adithya Sagar, Vikas Chandra, Raghuraman Krishnamoorthi
2025 J jnl
CoRR
Patrick Huber, Ernie Chang, Wei Wen, Igor Fedorov, Tarek Elgamal, Hanxian Huang, Naveen Suda, Chinnadhurai Sankar, Vish Vogeti, Yanghan Wang, Alex Gladkov, Kai Sheng Tai, Abdelrahman Elogeel, Tarek Hefny, Vikas Chandra, Ahmed Aly, Anuj Kumar, Raghuraman Krishnamoorthi, Adithya Sagar
2025 A* conf
ICLR
Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort
2025 J jnl
CoRR
Hanqing Zhu, Zhenyu Zhang, Hanxian Huang, DiJia Su, Zechun Liu, Jiawei Zhao, Igor Fedorov, Hamed Pirsiavash, Zhizhou Sha, Jinwon Lee, David Z. Pan, Zhangyang Wang, Yuandong Tian, Kai Sheng Tai
2025 J jnl
Trans. Mach. Learn. Res.
Payman Behnam, Uday Kamal, Sanjana Vijay Ganesh, Zhaoyi Li, Michael Jurado, Alind Khare, Igor Fedorov, Gaowen Liu, Alexey Tumanov
2024 B conf
IEEE Big Data
Tunhou Zhang, Wei Wen, Igor Fedorov, Xi Liu, Buyun Zhang, Fangqiu Han, Wen-Yen Chen, Yiping Han, Feng Yan, Hai Li, Yiran Chen
2024 J jnl
CoRR
Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo Latapie, Myungjin Lee, Alexey Tumanov
2024 conf
ECCV (89)
Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo Latapie, Myungjin Lee, Alexey Tumanov
2024 J jnl
CoRR
Igor Fedorov, Kate Plawiak, Lemeng Wu, Tarek Elgamal, Naveen Suda, Eric Smith, Hongyuan Zhan, Jianfeng Chi, Yuriy Hulovatyy, Kimish Patel, Zechun Liu, Changsheng Zhao, Yangyang Shi, Tijmen Blankevoort, Mahesh Pasupuleti, Bilge Soran, Zacharie Delpierre Coudert, Rachad Alao, Raghuraman Krishnamoorthi, Vikas Chandra
2024 A* conf
ICML
Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra
2024 J jnl
CoRR
Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra
2024 conf
WWW (Companion Volume)
Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen
2024 A* conf
KDD
Hua Zheng, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Wen-Yen Chen, Wei Wen
2024 J jnl
CoRR
Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort
2023 J jnl
CoRR
Tunhou Zhang, Wei Wen, Igor Fedorov, Xi Liu, Buyun Zhang, Fangqiu Han, Wen-Yen Chen, Yiping Han, Feng Yan, Hai Li, Yiran Chen
2023 A* conf
ICLR
Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama
2023 J jnl
CoRR
Yuji Chai, Devashree Tripathy, Chuteng Zhou, Dibakar Gope, Igor Fedorov, Ramon Matas Navarro, David Brooks, Gu-Yeon Wei, Paul N. Whatmough
2023 J jnl
CoRR
Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen
2023 J jnl
CoRR
Hua Zheng, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Wen-Yen Chen, Wei Wen
2022 J jnl
Symmetry
Konstantin V. Zhukovsky, Igor Fedorov
2022 conf
Odyssey
Nikita Kuzmin, Igor Fedorov, Alexey Sholokhov
2022 J jnl
CoRR
Nikita Kuzmin, Igor Fedorov, Alexey Sholokhov
2022 J jnl
CoRR
Kartikeya Bhardwaj, James Ward, Caleb Tung, Dibakar Gope, Lingchuan Meng, Igor Fedorov, Alex Chalfin, Paul N. Whatmough, Danny Loh
2022 A* conf
NeurIPS
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
2022 J jnl
CoRR
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
2021 J jnl
J. Imaging
Hiba H. Alqaysi, Igor Fedorov, Faisal Z. Qureshi, Mattias O'Nils
2021 J jnl
IEEE Trans. Instrum. Meas.
Igor Fedorov, Benny Thörnberg, Hiba H. Alqaysi, Najeem Lawal, Mattias O'Nils
2021 J jnl
ACM J. Emerg. Technol. Comput. Syst.
Urmish Thakker, Igor Fedorov, Chu Zhou, Dibakar Gope, Matthew Mattina, Ganesh Dasika, Jesse G. Beu
2021 conf
MLSys
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
2021 J jnl
Symmetry
Konstantin V. Zhukovsky, Igor Fedorov
2020 J jnl
CoRR
Sandeep Singh Sandha, Mohit Aggarwal, Igor Fedorov, Mani B. Srivastava
2020 Misc conf
ICASSP
Sandeep Singh Sandha, Mohit Aggarwal, Igor Fedorov, Mani B. Srivastava
2020 J jnl
CoRR
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
2020 Misc conf
ICASSP
Ching Hua Lee, Igor Fedorov, Bhaskar D. Rao, Harinath Garudadri
2020 A conf
INTERSPEECH
Igor Fedorov, Marko Stamenovic, Carl Jensen, Li-Chia Yang, Ari Mandell, Yiming Gan, Matthew Mattina, Paul N. Whatmough
2020 J jnl
CoRR
Igor Fedorov, Marko Stamenovic, Carl Jensen, Li-Chia Yang, Ari Mandell, Yiming Gan, Matthew Mattina, Paul N. Whatmough
2019 J jnl
CoRR
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Chu Zhou, Igor Fedorov, Ganesh Dasika, Matthew Mattina
2019 conf
ICDSC
Hiba H. Alqaysi, Najeem Lawal, Igor Fedorov, Benny Thörnberg, Mattias O'Nils
2019 conf
EMC2@NeurIPS
Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina
2019 J jnl
CoRR
Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina
2019 A* conf
NeurIPS
Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough
2019 J jnl
CoRR
Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough
2018 J jnl
Signal Process.
Igor Fedorov, Alican Nalci, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen, Harinath Garudadri
2018 conf
ICDSC
Hiba H. Alqaysi, Najeem Lawal, Igor Fedorov, Mattias O'Nils
2018 J jnl
CoRR
Igor Fedorov, Bhaskar D. Rao
2018 J jnl
CoRR
Igor Fedorov, Bhaskar D. Rao
2018 J jnl
IEEE Trans. Signal Process.
Alican Nalci, Igor Fedorov, Maher Al-Shoukairi, Thomas T. Liu, Bhaskar D. Rao
2018
Igor Fedorov
2018 conf
ICDSC
Igor Fedorov, Najeem Lawal, Benny Thörnberg, Hiba H. Alqaysi, Mattias O'Nils
2017 conf
ICDSC
Hiba H. Alqaysi, Najeem Lawal, Igor Fedorov, Mattias O'Nils
2017 Misc conf
ICASSP
Igor Fedorov, Bhaskar D. Rao, Truong Q. Nguyen
2017 conf
ICDSC
Igor Fedorov, Najeem Lawal, Mattias O'Nils, Hiba H. Alqaysi
2017 J jnl
CoRR
Igor Fedorov, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen
2017 Misc conf
ACSSC
Igor Fedorov, Sebastian Obrzut, Bongyong Song, Bhaskar D. Rao
2016 J jnl
CoRR
Alican Nalci, Igor Fedorov, Bhaskar D. Rao
2016 J jnl
CoRR
Igor Fedorov, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen
2016 B conf
ICIP
Igor Fedorov, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen
2011 conf
ICEAC
Pradeep S. Shenoy, Igor Fedorov, Tyler Neyens, Philip T. Krein
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` |