Our unique Python protection ensures that Python3 files are secured to harden them against reverse engineering.
Python is a versatile and popular programming language; however, its interpreted nature exposes it to risks of reverse engineering. Typically, Python projects are distributed as source files, which grant direct access to valuable intellectual property and sensitive data. Even when these files are compiled to .pyc files or transformed into C using Cython, they remain susceptible to reverse engineering through disassembly and decompilation, posing significant security challenges.
Protecting Python code is essential not only to safeguard intellectual property but also to secure the significant investments made in research and development. Effective protection prevents unauthorized access and manipulation, ensuring that proprietary technology remains confidential and maintains its competitive advantage.
Our unique Python protection ensures that Python3 files are secured to harden them against reverse engineering. Our protection is two-fold with the advanced Python file protection working hand-in-hand for the protection with the Python interpreter.
Our solution protects Python code from unauthorised access, preventing disassembly and decompilation. Unlike standard .pyc files, we dynamically transform the interpreter’s instruction sets, assigning unique opcode mappings to every code object, including functions and lambdas. These mappings are further obfuscated, creating a constantly shifting target that makes reverse engineering significantly more difficult, ensuring proprietary algorithms remain secure.
Due to our unique approach the interpreter has to be modified as well to be able to execute the protected and obfuscated Python files. Our solution extends security to the Python interpreter itself through integration with Emproof Nyx. This ensures a comprehensive defense against reverse engineering, tampering, debugging attempts and unauthorized access.
Emproof Nyx protects software from reverse engineering threats.
The source code is protected and no longer visible. Pure Python files – and even compiled .pyc files – can typically be easily reverse engineered, our solution ensures that the source code remains secure and inaccessible.
All strings in the code are replaced with encoded versions, which are decoded at runtime. This prevents sensitive information from being exposed in the compiled files.
Our protections are meticulously designed to ensure that they impose the least possible overhead.
Our python protection is easy to integrate into any workflow. Our tool only needs the source code files as input and wraps everything into a ready to ship package for customers. Think of us as the last step in your CI/CD pipeline.
Execution of the protected python also works without hassle as the packages contain all necessary files and do not have to install extra dependencies to ensure that the protected files are working.
The protected interpreter is able to work with unprotected python3 files as well, which means that included modules and libraries do not have to be protected if not wanted.
Our solution has significant benefits over other strategies that are often deployed to protect python code.
This method involves applying obfuscation techniques directly to the Python source code. While it can make the code less readable, all information remains within the script, and the transformations are reversible. Attackers can deobfuscate the code using readily available tools, making this approach insufficient against even unexperienced reverse engineers.
Encrypting Python scripts requires them to be decrypted before execution. This decryption step exposes the code in memory, allowing attackers to set breakpoints and dump the decrypted code at runtime. As a result, encryption alone does not provide robust protection against reverse engineering or code extraction.
This technique replaces standard opcodes with substituted ones in a static manner. However, it is vulnerable to known-plaintext attacks and statistical analysis. Since the opcode mapping is consistent across the application, attackers can analyze patterns and infer the original opcodes, compromising the obfuscation.
Protect your Python code and keep your intellectual property safe.