Xianfeng Song

31 papers B 2C 5Journal 19Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Neurocomputing
Xianfeng Song, Yi Zou, Zheng Shi
2026 J jnl
Neural Networks
Xianfeng Song, Yi Zou, Zheng Shi, Zheng Liu
2025 J jnl
CoRR
Xianfeng Song, Yi Zou, Zheng Shi
2025 B conf
IJCNN
Guohua Wen, Yi Zou, Xianfeng Song
2024 J jnl
Remote. Sens.
Panli Cai, Jingxian Guo, Runkui Li, Zhen Xiao, Haiyu Fu, Tongze Guo, Xiaoping Zhang, Yashuai Li, Xianfeng Song
2024 J jnl
IEEE Trans. Parallel Distributed Syst.
Zheng Shi, Yi Zou, Xianfeng Song, Shupeng Li, Fangming Liu, Quan Xue
2024 C conf
ISPA
Junfeng Hu, Yi Zou, Xianfeng Song, Yiqiu Liu
2024 J jnl
CoRR
Xianfeng Song, Yi Zou, Zheng Shi, Zheng Liu
2024 J jnl
Remote. Sens.
Tongze Guo, Runkui Li, Zhen Xiao, Panli Cai, Jingxian Guo, Haiyu Fu, Xiaoping Zhang, Xianfeng Song
2024 J jnl
Remote. Sens.
Afera Halefom, Yan He, Tatsuya Nemoto, Lei Feng, Runkui Li, Venkatesh Raghavan, Guifei Jing, Xianfeng Song, Zheng Duan
2024 B conf
SMC
Jiale Lai, Jiake Tian, Yi Zou, Xianfeng Song, Fangming Liu, Dacheng Li
2023 conf
ICONIP (14)
Xianfeng Song, Yi Zou, Zheng Shi, Yanfeng Yang, Dacheng Li
2023 J jnl
Remote. Sens.
Yan He, Chen Wang, Jinghao Hu, Huihui Mao, Zheng Duan, Cixiao Qu, Runkui Li, Mingyu Wang, Xianfeng Song
2021 J jnl
ISPRS Int. J. Geo Inf.
Junli Liu, Miaomiao Pan, Xianfeng Song, Jing Wang, Kemin Zhu, Runkui Li, Xiaoping Rui, Weifeng Wang, Jinghao Hu, Venkatesh Raghavan
2021 J jnl
Sensors
Guangyuan Zhang, Stefan Poslad, Xiaoping Rui, Guangxia Yu, Yonglei Fan, Xianfeng Song, Runkui Li
2020 conf
CCTA
Mohammad Ali Abooshahab, Morten Hovd, Edmund Brekke, Xianfeng Song
2020 J jnl
Remote. Sens.
Guangyuan Zhang, Xiaoping Rui, Stefan Poslad, Xianfeng Song, Yonglei Fan, Bang Wu
2020 J jnl
Signal Image Video Process.
Yonglei Fan, Xiaoping Rui, Stefan Poslad, Guangyuan Zhang, Tian Yu, Xijie Xu, Xianfeng Song
2019 J jnl
Sensors
Guangyuan Zhang, Xiaoping Rui, Stefan Poslad, Xianfeng Song, Yonglei Fan, Zixiang Ma
2017 J jnl
Comput. Environ. Urban Syst.
Jing Wang, Chaoliang Wang, Xianfeng Song, Venkatesh Raghavan
2017 conf
AIM
Xianfeng Song, Lars Duggen, Benny Lassen, Charles Mangeot
2015 J jnl
Remote. Sens.
Hongyuan Huo, Zhuoya Ni, Caixia Gao, Enyu Zhao, Yuze Zhang, Yi Lian, Huili Zhang, Shiyue Zhang, Xiaoguang Jiang, Xianfeng Song, Ping Zhou, Tiejun Cui
2015 J jnl
Int. J. Geogr. Inf. Sci.
Jing Wang, Xiaoping Rui, Xianfeng Song, Xiangshuang Tan, Chaoliang Wang, Venkatesh Raghavan
2014 C conf
IGARSS
Hongyuan Huo, Xiaoguang Jiang, Xianfeng Song, Zhuoya Ni, Liang Liu
2014 J jnl
Remote. Sens.
Hongyuan Huo, Xiaoguang Jiang, Xianfeng Song, Zhao-Liang Li, Zhuoya Ni, Caixia Gao
2013 J jnl
Cogn. Sci.
Thomas N. Wisdom, Xianfeng Song, Robert L. Goldstone
2012 C conf
IGARSS
Runkui Li, Yasuyuki Kono, Junzhi Liu, Ming Peng, Venkatesh Raghavan, Xianfeng Song
2011 C conf
IGARSS
Jing Wang, Xiaoping Rui, Xianfeng Song, Chaoliang Wang, Lingli Tang, Chuanrong Li, Venkatesh Raghavan
2010 conf
Geoinformatics
Chaoliang Wang, Xianfeng Song, Fangzhou Xu
2010 conf
Geoinformatics
Xianfeng Song, Chaoliang Wang, Masakazu Kagawa, Venkatesh Raghavan
2010 C conf
IGARSS
Xianfeng Song, Xiaoguang Jiang, Xiaoping Rui
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` |