Protecting Python Applications The Simpler Way
All software ought to be protected, not just applications made with one of the usual suspects: C or Java. In recent years, Python has become an increasingly attractive choice for software developers, not least with the language’s commitment to simplicity and clarity, but also the sheer range of solid, up-to-date resources for AI or machine learning applications. The newfound popularity of the language becomes plain when one sees its ranking in the TIOBE Index, following hot on the heels of the two traditional favorites.
But simple and clear also means: an appealing target for would-be attackers. And Python does make it unnecessarily easy for them to access the code. If it is not available in plaintext form from the outset, but precompiled with Cython, skilled attackers would still have no major problems with getting back to the original code by using common hacking tools. Especially in innovation-heavy areas like AI, that code can represent a substantial intellectual and commercial asset, making it perfect prey for unscrupulous hackers.
Wibu-Systems believes that only solid encryption can truly protect sensitive code from these threats. That is why Python support has been added to the popular CodeMeter Protection Suite. The traditional approach would be to transform Python code into a native application with tools like Cython and to then protect that application with CodeMeter’s powerful encryption. But there is a second, revolutionary approach: Encrypting the Python code itself in its original form. With CodeMeter’s technology, the code is only decrypted when it is actually needed and remains encrypted at all other times, so that it could not simply be extracted from working memory. CodeMeter can also encrypt different parts of the code with separate licenses or cryptographic keys to allow smart modular protections for the finished application.
Our masterclass will show you how to protect your applications automatically in their Python form and which packages you will need to get your software out into world.
Here are the main highlights:
- Two options for protecting Python application:
- Transformed into native applications
- Protected as Python code
- Use cases:
- Protecting entire applications
- Adding modular protections (Features-on-Demand)
- Requirements and tips & tricks
Join our webinar to see how you can protect the know-how that you have built into your Python applications from reverse engineering and how you can use CodeMeter to monetize this investment into your products.