Radhia Cousot

66 papers A* 14A 2B 11Misc 2Journal 17Unranked 19
YearRankTypeTitle / Venue / Authors
2015 J jnl
Found. Trends Program. Lang.
Julien Bertrane, Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, Xavier Rival
2014 A* conf
POPL
Patrick Cousot, Radhia Cousot
2014 conf
CSL-LICS
Patrick Cousot, Radhia Cousot
2013 B conf
FASE
Omer Tripp, Marco Pistoia, Patrick Cousot, Radhia Cousot, Salvatore Guarnieri
2013 B conf
VMCAI
Patrick Cousot, Radhia Cousot, Manuel Fähndrich, Francesco Logozzo
2013 A* ed.
POPL
Roberto Giacobazzi, Radhia Cousot
2012 conf
SPLASH
Francesco Logozzo, Michael Barnett, Manuel Fähndrich, Patrick Cousot, Radhia Cousot
2012 A conf
OOPSLA
Patrick Cousot, Radhia Cousot, Francesco Logozzo, Michael Barnett
2012 A* conf
POPL
Patrick Cousot, Radhia Cousot
2012 J jnl
J. ACM
Patrick Cousot, Radhia Cousot, Laurent Mauborgne
2011 A* conf
POPL
Patrick Cousot, Radhia Cousot, Francesco Logozzo
2011 J jnl
Theor. Comput. Sci.
Patrick Cousot, Radhia Cousot
2011 B conf
VMCAI
Patrick Cousot, Radhia Cousot, Francesco Logozzo
2011 J jnl
ACM SIGSOFT Softw. Eng. Notes
Julien Bertrane, Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, Xavier Rival
2011 B conf
FoSSaCS
Patrick Cousot, Radhia Cousot, Laurent Mauborgne
2010 conf
Essays in Memory of Amir Pnueli
Patrick Cousot, Radhia Cousot, Laurent Mauborgne
2010 ch.
Logics and Languages for Reliability and Security
Patrick Cousot, Radhia Cousot
2010 conf
The Future of Software Engineering
Patrick Cousot, Radhia Cousot, Laurent Mauborgne
2010 B ed.
SAS
Radhia Cousot, Matthieu Martel
2009 J jnl
Theor. Comput. Sci.
Patrick Cousot, Radhia Cousot, Roberto Giacobazzi
2009 J jnl
Softwaretechnik-Trends
Daniel Kästner, Christian Ferdinand, Stephan Wilhelm, Stefana Nenova, Olha Honcharova, Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, Xavier Rival, Élodie-Jane Sims
2009 J jnl
Inf. Comput.
Patrick Cousot, Radhia Cousot
2009 J jnl
Formal Methods Syst. Des.
Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, Xavier Rival
2008 B conf
VMCAI
Radhia Cousot
2007 J jnl
CoRR
Bruno Blanchet, Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, David Monniaux, Xavier Rival
2007 conf
SOS@LICS/ICALP
Patrick Cousot, Radhia Cousot
2007 Misc conf
TASE
Patrick Cousot, Radhia Cousot, Jérôme Feret, Antoine Miné, Laurent Mauborgne, David Monniaux, Xavier Rival
2006 conf
ASIAN
Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, David Monniaux, Xavier Rival
2006 conf
Program Analysis and Compilation
Patrick Cousot, Radhia Cousot
2005 J jnl
Sci. Comput. Program.
Radhia Cousot
2005 A conf
ESOP
Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, David Monniaux, Xavier Rival
2005 B ed.
VMCAI
Radhia Cousot
2004 A* conf
POPL
Patrick Cousot, Radhia Cousot
2004 conf
IFIP Congress Topical Sessions
Patrick Cousot, Radhia Cousot
2003 A* conf
PLDI
Bruno Blanchet, Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, David Monniaux, Xavier Rival
2003 J jnl
Theor. Comput. Sci.
Patrick Cousot, Radhia Cousot
2003 B ed.
SAS
Radhia Cousot
2002 conf
The Essence of Computation
Bruno Blanchet, Patrick Cousot, Radhia Cousot, Jérôme Feret, Laurent Mauborgne, Antoine Miné, David Monniaux, Xavier Rival
2002 B conf
CC
Patrick Cousot, Radhia Cousot
2002 A* conf
CAV
Patrick Cousot, Radhia Cousot
2002 A* conf
POPL
Patrick Cousot, Radhia Cousot
2001 B conf
MFPS
Patrick Cousot, Radhia Cousot
2001 Misc conf
EMSOFT
Patrick Cousot, Radhia Cousot
2000 A* conf
POPL
Patrick Cousot, Radhia Cousot
1999 J jnl
Autom. Softw. Eng.
Patrick Cousot, Radhia Cousot
1997 conf
AMAST
Patrick Cousot, Radhia Cousot
1996 B ed.
SAS
Radhia Cousot, David A. Schmidt
1995 A* conf
CAV
Patrick Cousot, Radhia Cousot
1995 conf
FPCA
Patrick Cousot, Radhia Cousot
1994 conf
ICCL
Patrick Cousot, Radhia Cousot
1993 J jnl
Theor. Comput. Sci.
Patrick Cousot, Radhia Cousot
1993 conf
Formal Methods in Programming and Their Applications
Patrick Cousot, Radhia Cousot
1992 J jnl
J. Log. Comput.
Patrick Cousot, Radhia Cousot
1992 J jnl
J. Log. Program.
Patrick Cousot, Radhia Cousot
1992 conf
PLILP
Patrick Cousot, Radhia Cousot
1992 A* conf
POPL
Patrick Cousot, Radhia Cousot
1991 conf
JTASPEFT/WSA
Patrick Cousot, Radhia Cousot
1991 conf
JTASPEFT/WSA
Patrick Cousot, Radhia Cousot
1989 J jnl
Inf. Comput.
Patrick Cousot, Radhia Cousot
1987 J jnl
Acta Informatica
Patrick Cousot, Radhia Cousot
1980 A* conf
ICALP
Patrick Cousot, Radhia Cousot
1979 A* conf
POPL
Patrick Cousot, Radhia Cousot
1977 A* conf
POPL
Patrick Cousot, Radhia Cousot
1977 conf
Artificial Intelligence and Programming Languages
Patrick Cousot, Radhia Cousot
1977 conf
Language Design for Reliable Software
Patrick Cousot, Radhia Cousot
1977 conf
Formal Description of Programming Concepts
Patrick Cousot, Radhia Cousot
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` |