pyobfus: the Python obfuscator

Obfuscate Python before you ship it—and still debug what you shipped.

简体中文 · Product · Documentation · PyPI

pyobfus is a local-first, AST-based Python obfuscator for Python 3.9–3.14. It handles complete projects, keeps generated output portable, and can reverse-map protected production tracebacks for developers and AI coding agents. Community is Apache-2.0, has no file or line limits, and requires no trial.

What's new in v0.6.1: fixes two bugs where the build succeeded but the output failed when run. Directory builds broke from pkg import f as g (NameError), and single-file builds renamed parameters without updating keyword calls (TypeError, or arguments silently bound wrong). Parameter names are now kept by default; --no-preserve-param-names restores the old behavior with a warning. Rebuild, keep the new mapping, and rerun your tests; see the changelog.

Why pyobfus

Quick start

pip install pyobfus

# Check compatibility, preview, then build
pyobfus --check src/
pyobfus src/ -o dist/ --dry-run --json
pyobfus src/ -o dist/ --save-mapping mapping.json --verify-syntax
# --verify-syntax only compiles the output; run your own tests against dist/

# Restore names when a production traceback arrives
pyobfus --unmap --trace error.log --mapping mapping.json

For framework presets, configuration discovery, packaging and verification, start at the task-oriented documentation.

Minimal example

Input:

def greet(name):
    message = f"Hello, {name}!"
    return message

print(greet("world"))

Run pyobfus input.py -o output.py. Representative Community output:

def I0(I1):
    I2 = f"Hello, {I1}!"
    return I2

print(I0("world"))

Both print Hello, world!. Generated identifiers can differ with input and configuration; verify the exact output with your own tests. Keep a mapping when you need to restore names from a shipped traceback.

Parameter names are preserved by default in every preset. Explicit --no-preserve-param-names or YAML preserve_param_names: false keeps legacy renaming with a warning: keyword calls may raise TypeError or silently bind incorrectly. Rebuild from original source and keep the new mapping with the new artifact; mapping numbers can change and old mappings cannot decode rebuilt output. Cross-file directory builds (the default) still preserve parameters; legacy --no-cross-file directory builds follow the option.

Features at a glance

Community includes name mangling with import rewriting across a project (directories also rename function locals; parameters and methods remain unchanged there; single files also rename methods and preserve parameters by default, see the guide), string and numeric transforms, framework-aware presets, config-aware pre-flight scanning, SARIF, structured dry-run, reverse traceback mapping, syntax verification, provenance, reproducible output and verifiable build reports.

Professional adds four kinds of commercial value:

• Protection strength: AES encryption, control-flow flattening, dead-code injection, anti-debugging, Selective Opacity and sealing.
• Protected assets: import strings, embedded data, Runtime String Vault and protected tracebacks.
• Distribution control: device, expiry, run-count, platform and application-supplied-key policies.
• Accountability: forensic watermarking and buyer-specific builds.

The durable classification rule is documented in the Community / Pro boundary policy.

🔌 Companion MCP server: pyobfus-mcp

Install the MCP server with no API key and no source upload:

uvx pyobfus-mcp
# or: pip install pyobfus-mcp

It exposes structured tools for scanning, configuration, protection, verification, preset explanation, tier recommendations and traceback mapping. See the MCP package guide and its registration in the official MCP Registry.

Agent and editor integrations

• pyobfus-review and pyobfus-protect skills separate read-only review from build-producing work. See skills.
• The VS Code extension provides inline risk diagnostics and traceback reversal; it is also on Open VSX.
• zhurong2020/pyobfus-action@v1 runs scans or verified builds in GitHub Actions with SARIF support.
• The stable JSON CLI includes reason codes and an ai_hint next action.
• Agent-readable project facts are published in llms.txt, while contributor instructions live in AGENTS.md.

All Agent guidance is public and human-auditable. pyobfus does not serve hidden instructions or different facts based on User-Agent.

Configuration

Generate a starting configuration or use a named preset:

pyobfus --init src/
pyobfus src/ -o dist/ --preset django
pyobfus --list-presets

Community presets include safe, balanced, aggressive, fastapi, django, flask, pydantic, click, sqlalchemy and ml. See the documentation home and pyobfus --help for current options. Optional max_files and max_total_loc values are user-selected safety limits at every tier.

How do I debug an obfuscated crash with an AI assistant?

Build with --save-mapping mapping.json, keep that file private, then run:

pyobfus --unmap --trace error.log --mapping mapping.json

The restored identifiers can be read by you or an AI assistant without giving the customer your mapping or original source. --trace-marker can also stamp generated files with the exact recovery command.

Purchase Professional Edition

Professional Edition is $45 USD, one time—not a subscription. A five-day trial requires no registration or card:

pyobfus-trial start

The trial is an honor-system convenience control, not a security boundary. Visit the product and purchase page for current payment methods, refund terms and purchase steps. After purchase, use the license activation guide.

Runtime-backed Pro artifacts depend on the separately redistributable, pure-Python pyobfus-runtime package. Target machines do not need the complete proprietary builder or a licence key.

Security and limitations

Obfuscation raises the cost of inspection; it does not make client-side Python irreversible. Runtime-decrypted material can be observed by a determined attacker. Keep credentials and authorization decisions behind environment, secret-manager or server boundaries.

• Threat model
• Support matrix
• Release provenance
• Security policy

Comparison and deployment guides

• Comparison overview
• vs PyArmor
• vs Nuitka
• PyInstaller cookbook
• Compiled-packaging cookbook
• Integration testing

Architecture and development

The product line separates the Apache-2.0 Core, proprietary Pro builder, redistributable runtime, MCP package, editor extension and GitHub Action. See:

• Project structure
• Contributing guide
• Developer instructions
• Changelog

Community and citation

Use GitHub Issues for bugs and Discussions for questions and ideas. Citation metadata is in CITATION.cff, with archival DOI 10.5281/zenodo.20846053.

Core is Apache-2.0; Professional implementation is proprietary. See LICENSE-NOTICE.md.