A Python library for parsing and manipulating YARA rules using Abstract Syntax Trees
Project description
yaraast
A Python library for parsing and manipulating YARA rules using Abstract Syntax Trees.
Features
- 100% YARA Parsing Success: Parses all production YARA files (273,683+ rules tested)
- YARA-L 2.0 Support: Full support for Google Chronicle detection rules (891/891 files)
- YARA-X Support: Compatible with YARA-X syntax and features
- Automatic Dialect Detection: Context-aware detection distinguishes YARA, YARA-L, and YARA-X
- Advanced Features:
- Hex nibble wildcards (
4?,?5,??) - Regex modifiers (
/i,/m,/s,/g) - VirusTotal LiveHunt module support
- Wildcard string sets (
$a*,any of ($prefix*)) - Negative integers in metadata
- Extended
of...inoperator with ranges (N of ($a*) in (start..end)) - PE exports with regex patterns (
pe.exports(/pattern/)) - Comment-aware hex string parsing
- Streaming parser for large files (100MB+ threshold)
- ClamAV syntax detection
- Hex nibble wildcards (
Installation
pip install yaraast
Quick Start
from yaraast import Parser
from yaraast.unified_parser import UnifiedParser
# Parse YARA rules with automatic dialect detection
yara_code = """
rule example {
meta:
author = "Security Team"
version = 1
strings:
$hex = { 4D 5A 90 00 }
$str = "malware" wide
condition:
$hex at 0 and $str
}
"""
# Option 1: Direct parser (when you know it's standard YARA)
parser = Parser(yara_code)
ast = parser.parse()
# Option 2: Unified parser with auto-detection (recommended)
ast = UnifiedParser.parse_string(yara_code)
# Access rule components
rule = ast.rules[0]
print(f"Rule: {rule.name}")
print(f"Strings: {len(rule.strings)}")
print(f"Condition: {rule.condition}")
Advanced Usage
Automatic Dialect Detection
The UnifiedParser automatically detects YARA, YARA-L, and YARA-X dialects:
from yaraast.unified_parser import UnifiedParser
# Parse file with automatic detection
ast = UnifiedParser.parse_file("rules.yar")
# Or parse string
ast = UnifiedParser.parse_string(yara_code)
# Force specific dialect if needed
from yaraast.dialects import YaraDialect
ast = UnifiedParser.parse_file("rules.yar", dialect=YaraDialect.YARA)
Streaming Parser for Large Files
For very large YARA files (100MB+), use streaming mode:
from yaraast.unified_parser import UnifiedParser
# Automatically uses streaming for files > 100MB
ast = UnifiedParser.parse_file("large_ruleset.yar")
# Force streaming for smaller files
ast = UnifiedParser.parse_file("rules.yar", force_streaming=True)
# Custom threshold (in MB)
ast = UnifiedParser.parse_file("rules.yar", streaming_threshold_mb=50)
Lenient Parsing Mode
For files with mixed YARA/ClamAV syntax:
from yaraast import Parser
# Enable lenient mode to skip invalid patterns
parser = Parser(yara_code, lenient=True)
ast = parser.parse()
# Check for skipped patterns
if parser.errors:
print(f"Skipped {len(parser.errors)} invalid patterns")
Working with YARA-L
from yaraast.yaral import YaraLParser
yaral_code = """
rule detect_suspicious_activity {
meta:
author = "Threat Intel"
events:
$e.metadata.event_type = "NETWORK_CONNECTION"
$e.target.port = 443
condition:
$e
}
"""
parser = YaraLParser(yaral_code)
ast = parser.parse()
VirusTotal Module Support
Full support for VirusTotal LiveHunt and Retrohunt rules:
from yaraast import Parser
# Parse rules using VirusTotal module
vt_rule = """
import "vt"
rule vt_livehunt_example {
meta:
description = "Detect files based on VT intelligence"
condition:
vt.metadata.new_file and
vt.metadata.analysis_stats.malicious > 5 and
vt.metadata.file_type == vt.FileType.PE_EXE
}
"""
parser = Parser(vt_rule)
ast = parser.parse()
# Access VT module usage
print(f"Uses VT module: {'vt' in [imp.module for imp in ast.imports]}")
Supported VT module features:
vt.metadata.*- File metadata and analysis statisticsvt.behaviour.*- Behavioral analysis datavt.net.*- Network activity indicators- All VirusTotal Intelligence operators and functions
Visitor Pattern
from yaraast import Parser
from yaraast.visitor import BaseVisitor
class RuleCollector(BaseVisitor):
def __init__(self):
self.rule_names = []
def visit_rule(self, node):
self.rule_names.append(node.name)
super().visit_rule(node)
ast = Parser(yara_code).parse()
collector = RuleCollector()
collector.visit(ast)
print(f"Found rules: {collector.rule_names}")
Language Support
YARA Features
- ✅ All YARA syntax and operators
- ✅ Hex strings with wildcards and jumps
- ✅ Regular expressions with modifiers
- ✅ String modifiers (ascii, wide, nocase, fullword, xor, base64)
- ✅ All condition operators and expressions
- ✅ Module imports (pe, elf, math, hash, vt, etc.)
- ✅ PE exports with regex patterns (
pe.exports(/pattern/)) - ✅ Extended
of...inranges (N of ($a*) in (start..end)) - ✅ Private and global rules
- ✅ Include directives
- ✅ Comments inside hex strings
YARA-L 2.0 Features
- ✅ Event matching and correlation
- ✅ Outcome sections
- ✅ Time windows and aggregations
- ✅ Match sections
- ✅ Complex boolean expressions
- ✅ Chronicle-specific functions
YARA-X Features
- ✅ New syntax elements
- ✅ Enhanced type system
- ✅ Compatibility mode
Testing
Verified with production rulesets:
- ClamAV: 223,261 rules
- YARA Master Collection: 31,463 rules
- Community Rules: 11,331 rules
- Google Chronicle: 891 YARA-L rules
Performance
- Parses 273,683+ rules across 14 files
- 337 comprehensive tests (100% passing)
- Handles files up to 91MB
- Streaming mode for files > 100MB
- ~1,800 rules/second on large files (30MB+)
Requirements
- Python >= 3.13
- click >= 8.1.0
- rich >= 13.0.0
- attrs >= 23.0.0
- PyYAML >= 6.0.0
Optional Dependencies
# LSP support
pip install yaraast[lsp]
# libyara integration
pip install yaraast[libyara]
# Performance optimization
pip install yaraast[performance]
# Visualization
pip install yaraast[visualization]
# All features
pip install yaraast[all]
CLI Usage
# Parse YARA file
yaraast parse rules.yar
# Validate syntax
yaraast validate rules.yar
# Pretty-print with formatting
yaraast format rules.yar
# Start LSP server
yaraast lsp
License
MIT License - see LICENSE file for details
Author
Marc Rivero (mriverolopez@gmail.com)
Links
- PyPI: https://pypi.org/project/yaraast/
- GitHub: https://github.com/mriverolopez/yaraast
- Documentation: https://yaraast.readthedocs.io/
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