Rainer Konietschke

23 papers A* 6A 3B 1C 1Journal 4Unranked 7
YearRankTypeTitle / Venue / Authors
2013 ch.
Frontiers of Intelligent Autonomous Systems
Stefan Jörg, Rainer Konietschke, Julian Klodmann
2013 A conf
IROS
Bastian Deutschmann, Rainer Konietschke, Alin Albu-Schäffer
2012 conf
CURAC
Martin Lohmann, Rainer Konietschke
2012 conf
HAVE
Verena Nitsch, Berthold Färber, Anja Hellings, Stefan Jörg, Andreas Tobergte, Rainer Konietschke
2012 conf
IAS (2)
Stefan Jörg, Rainer Konietschke, Julian Klodmann
2011 A* conf
ICRA
Rainer Konietschke, Tim Bodenmüller, Christian Rink, Andrea Schwier, Berthold Bäuml, Gerd Hirzinger
2011 A conf
IROS
Julian Klodmann, Rainer Konietschke, Alin Albu-Schäffer, Gerhard Hirzinger
2010 B conf
RO-MAN
Rainer Konietschke, Andreas Tobergte, Carsten Preusche, Paolo Tripicchio, Emanuele Ruffaldi, Sabine Webel, Uli Bockholt
2010 J jnl
Int. J. Comput. Assist. Radiol. Surg.
Ulrich Hagn, Rainer Konietschke, Andreas Tobergte, Mathias Nickl, Stefan Jörg, Bernhard Kübler, Georg Passig, Martin Gröger, Florian A. Fröhlich, Ulrich Seibold, Luc Le Tien, Alin Albu-Schäffer, Alexander Nothhelfer, Franz Hacker, Markus Grebenstein, Gerd Hirzinger
2010 J jnl
Presence Teleoperators Virtual Environ.
Andreas Tobergte, Georg Passig, Bernhard Kübler, Ulrich Seibold, Ulrich Hagn, Florian A. Fröhlich, Rainer Konietschke, Stefan Jörg, Mathias Nickl, Sophie Thielmann, Robert Haslinger, Martin Gröger, Alexander Nothhelfer, Luc Le Tien, Robin Gruber, Alin Albu-Schäffer, Gerd Hirzinger
2010 conf
CURAC
Andrea Schwier, Rainer Konietschke, Tim Bodenmüller, Tobias Ende, Simon Kielhöfer, Gerd Hirzinger
2009 A* conf
ICRA
Rainer Konietschke, Gerd Hirzinger
2009 C conf
MMSP
Robert Bauernschmitt, Eva U. Braun, Martin Buss, Florian A. Fröhlich, Sandra Hirche, Gerhard Hirzinger, Julius Kammerl, Alois C. Knoll, Rainer Konietschke, Bernhard Kübler, Rüdiger Lange, Hermann Georg Mayer, Markus Rank, Gerhard Schillhuber, Christoph Staub, Eckehard G. Steinbach, Andreas Tobergte, Heinz Ulbrich, Iason Vittorias, Chen Zhao
2009 A* conf
ICRA
Andreas Tobergte, Rainer Konietschke, Gerd Hirzinger
2009 A* conf
ICRA
Christoph Borst, Thomas Wimböck, Florian Schmidt, Matthias Fuchs, Bernhard Brunner, Franziska Zacharias, Paolo Robuffo Giordano, Rainer Konietschke, Wolfgang Sepp, Stefan Fuchs, Christian Rink, Alin Albu-Schäffer, Gerd Hirzinger
2009 A* conf
ICRA
Rainer Konietschke, Ulrich Hagn, Mathias Nickl, Stefan Jörg, Andreas Tobergte, Georg Passig, Ulrich Seibold, Luc Le Tien, Bernhard Kübler, Martin Gröger, Florian A. Fröhlich, Christian Rink, Alin Albu-Schäffer, Markus Grebenstein, Tobias Ortmaier, Gerd Hirzinger
2008 J jnl
IEEE Robotics Autom. Mag.
Ulrich Hagn, Tobias Ortmaier, Rainer Konietschke, Bernhard Kübler, Ulrich Seibold, Andreas Tobergte, Mathias Nickl, Stefan Jörg, Gerd Hirzinger
2008 J jnl
Ind. Robot
Ulrich Hagn, Mathias Nickl, Stefan Jörg, Georg Passig, Thomas Bahls, Alexander Nothhelfer, Franz Hacker, Luc Le Tien, Alin Albu-Schäffer, Rainer Konietschke, Markus Grebenstein, Rebecca Schedl-Warpup, Robert Haslinger, Mirko Frommberger, Gerd Hirzinger
2006 A* conf
ICRA
Tobias Ortmaier, Holger Weiss, Ulrich Hagn, Markus Grebenstein, Matthias Nickel, Alin Albu-Schäffer, Christian Ott, Stefan Jörg, Rainer Konietschke, Luc Le Tien, Gerd Hirzinger
2006 conf
Humanoids
Christian Ott, Oliver Eiberger, Werner Friedl, Berthold Bäuml, Ulrich Hillenbrand, Christoph Borst, Alin Albu-Schäffer, Bernhard Brunner, Heiko Hirschmüller, Simon Kielhöfer, Rainer Konietschke, Michael Suppa, Thomas Wimböck, Franziska Zacharias, Gerhard Hirzinger
2006 conf
ARK
Rainer Konietschke, Gerd Hirzinger, Y. Yan
2006 A conf
IROS
Rainer Konietschke, Tobias Ortmaier, Ulrich Hagn, Gerd Hirzinger, Silvia Frumento
2003 conf
CARS
Rainer Konietschke, Tobias Ortmaier, Holger Weiss, Robert Engelke, Gerd Hirzinger
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` |