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Pyherion

Pyherion is the Python-based obfuscation and crypter module within the Veil Framework. It transforms Python payloads by applying various obfuscation techniques — variable renaming, control flow modification, string encoding, and code structure changes. For detection engineers, understanding these transformations is essential for writing detection rules that survive obfuscation.

Working with obfuscated code is one of those areas where defenders benefit enormously from understanding the offensive technique. If you have ever tried to write a YARA rule for a Python-based threat only to have it break after a trivial variable rename, Pyherion shows you exactly why — and how to build more resilient detections.

What Pyherion Does

Pyherion takes a Python script and applies one or more obfuscation transformations:

Variable and Function Renaming

Replaces meaningful names with randomized strings. This breaks simple string-based detection rules that look for specific function or variable names in scripts.

String Encoding

Encodes string literals using base64, hex, or custom encoding schemes. The strings are decoded at runtime, which means static analysis tools that grep for specific strings will miss them.

Control Flow Modification

Restructures the script's control flow — reordering functions, adding dead code, and modifying loop structures. The logical behavior remains identical, but the code structure looks different to signature-based analysis.

Code Wrapping

Encapsulates the payload within multiple layers of encoding and decoding, creating a "wrapper" that must be unwound before the actual payload becomes visible.

Detection Strategies

Obfuscation makes static analysis harder but does not eliminate detection opportunities:

Behavioral Detection

Regardless of obfuscation, the payload's runtime behavior remains the same:

  • Network connections to the same destinations
  • Process creation patterns unchanged
  • Memory allocation behavior identical
  • File system interactions preserved

Behavioral detection rules that focus on what code does rather than what it looks like are resistant to obfuscation.

Script Block Logging

PowerShell's script block logging (Event ID 4104) captures the deobfuscated code at execution time. For Python-based payloads executed through the Python interpreter, equivalent logging can be achieved through interpreter auditing hooks.

Entropy Analysis

Heavily obfuscated scripts have higher entropy (randomness) than normal scripts. Automated entropy analysis of script files can flag anomalous files for manual review.

Execution Environment Anomalies

Pyherion-obfuscated scripts exhibit specific execution characteristics:

  • Multiple decoding operations at the start of execution
  • Import of encoding libraries (base64, codecs)
  • Dynamic code execution (exec, eval)
  • Unusual variable naming patterns (high randomness)

Lab Testing

To test your detection capabilities against obfuscated Python payloads:

  1. Generate a Python payload with Veil-Evasion
  2. Obfuscate it with Pyherion using different settings
  3. Deploy both the original and obfuscated versions to your lab targets
  4. Compare detection results — which rules catch the original but miss the obfuscated version?
  5. Update detection rules to be obfuscation-resistant
  6. Re-test to verify improvement

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