Carmine Serio

29 papers C 7Journal 18Unranked 4
YearRankTypeTitle / Venue / Authors
2024 C conf
IGARSS
Pamela Pasquariello, Guido Masiello, Carmine Serio, Giuliano Liuzzi, Rocco Giosa, Marco D'Emilio, Italia De Feis, Sara Venafra
2023 J jnl
IEEE Trans. Geosci. Remote. Sens.
Elisabetta Ricciardelli, Francesco Di Paola, Domenico Cimini, Salvatore Larosa, Pietro Mastro, Guido Masiello, Carmine Serio, Tim Hultberg, Thomas August, Filomena Romano
2023 C conf
IGARSS
Elisabetta Ricciardelli, Francesco Di Paola, Domenico Cimini, Salvatore Larosa, Guido Masiello, Pietro Mastro, Carmine Serio, Tim Hultberg, Thomas August, Filomena Romano
2022 J jnl
IEEE Geosci. Remote. Sens. Lett.
Francesco Falabella, Carmine Serio, Guido Masiello, Qing Zhao, Antonio Pepe
2022 J jnl
Remote. Sens.
Pietro Mastro, Guido Masiello, Carmine Serio, Antonio Pepe
2022 J jnl
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
Pietro Mastro, Guido Masiello, Carmine Serio, Domenico Cimini, Elisabetta Ricciardelli, Francesco Di Paola, Tim Hultberg, Thomas August, Filomena Romano
2021 C conf
IGARSS
Guido Masiello, Carmine Serio, Sara Venafra, Angela Cersosimo, Pietro Mastro, Francesco Falabella, Pamela Pasquariello
2021 C conf
IGARSS
Francesco Falabella, Angela Perrone, Tony Alfredo Stabile, Antonio Pepe, Carmine Serio
2020 C conf
IGARSS
Francesco Falabella, Carmine Serio, Giovanni Zeni, Antonio Pepe
2020 J jnl
Sensors
Carmine Serio, Guido Masiello, Pietro Mastro, David C. Tobin
2020 J jnl
Sensors
Francesco Falabella, Carmine Serio, Giovanni Zeni, Antonio Pepe
2020 J jnl
Remote. Sens.
Angela Cersosimo, Carmine Serio, Guido Masiello
2020 J jnl
Remote. Sens.
Pietro Mastro, Carmine Serio, Guido Masiello, Antonio Pepe
2019 J jnl
Sensors
Guido Masiello, Carmine Serio, Sara Venafra, Laurent Poutier, Frank-M. Göttsche
2018 J jnl
Remote. Sens.
Guido Masiello, Carmine Serio, Sara Venafra, Giuliano Liuzzi, Laurent Poutier, Frank-M. Göttsche
2017 conf
MultiTemp
R. Q. Iannone, Fabrizio Niro, Philippe Goryl, Steffen Dransfeld, Bianca Hoersch, Kerstin Stelzer, Grit Kirches, M. Paperin, Carsten Brockmann, Luis Gómez-Chova, Gonzalo Mateo-Garcia, Rene Preusker, Jürgen Fischer, Umberto Amato, Carmine Serio, Ute Gangkofner, Béatrice Berthelot, Marian-Daniel Iordache, Luc Bertels, Erwin Wolters, Wouter Dierckx, Iskander Benhadj, Else Swinnen
2016 J jnl
Int. J. Appl. Earth Obs. Geoinformation
Pietro Milillo, Daniele Perissin, Jacqueline T. Salzer, Paul Lundgren, Teodosio Lacava, Giovanni Milillo, Carmine Serio
2016 conf
SAR
Pietro Milillo, Deodato Tapete, Francesca Cigna, Daniele Perissin, Jacqueline T. Salzer, Paul Lundgren, Eric J. Fielding, Roland Burgmann, Filippo Biondi, Giovanni Milillo, Carmine Serio
2015 C conf
IGARSS
Pietro Milillo, Daniele Perissin, Paul Lundgren, Carmine Serio
2013 J jnl
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
Umberto Amato, Anestis Antoniadis, Maria Francesca Carfora, Paolo Colandrea, Vincenzo Cuomo, Monica Franzese, Stefano Pignatti, Carmine Serio
2012 C conf
IGARSS
Valerio Tramutoli, Sedat Inan, Norbert Jakowski, Sergey Pulinets, Alexey Romanov, Carolina Filizzola, Irk Shagimuratov, Nicola Pergola, Nicola Genzano, Carmine Serio, Mariano Lisi, Rosita Corrado, Caterina Livia Sara Grimaldi, Mariapia Faruolo, Rosa Maria Petracca Altieri, Semih Ergintav, Ziyadin Çakir, Erhan Alparslan, Selime Gurol, Mohammed Mainul Hoque, Klaus-Dieter Missling, Volker Wilken, Claudia Borries, Yuri Kalilnin, Konstantin Tsybulia, E. Ginzburg, Anatoly Pokhunkov, Liubov Pustivalova, Alexander Romanov, Igor V. Cherny, Sergei Trusov, Anna Adjalova, Denis Ermolaev, Sergey Bobrovsky, Rossana Paciello, Irina Coviello, Alfredo Falconieri, Irina Zakharenkova, Yuri Cherniak, Alexander Radievsky, Vincenzo Lapenna, Marianna Balasco, Sabatino Piscitelli, Teodosio Lacava, Giuseppe Mazzeo
2010 J jnl
Remote. Sens.
Giuseppe Grieco, Guido Masiello, Carmine Serio
2005 J jnl
Environ. Model. Softw.
Annamaria Carissimo, Italia De Feis, Carmine Serio
2003 conf
ISCAS (5)
Antonio Luchetta, Carmine Serio, M. Viggiano
2003 J jnl
Environ. Model. Softw.
Umberto Amato, Guido Masiello, Carmine Serio, M. Viggiano
2002 J jnl
Environ. Model. Softw.
Umberto Amato, Guido Masiello, Carmine Serio, M. Viggiano
2000 J jnl
Environ. Model. Softw.
Umberto Amato, Claudia Angelini, Carmine Serio
1999 J jnl
IEEE Trans. Geosci. Remote. Sens.
Umberto Amato, Vincenzo Cuomo, Italia De Feis, Filomena Romano, Carmine Serio, Hirokazu Kobayashi
1993 conf
Fractals in the Natural and Applied Sciences
Carmine Serio
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` |