Secure Your Python Code with Safe Eval

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Secure Your Python Code with Safe Eval

Secure Your Python Code with Safe Eval

If you are a Python developer, you would know how important it is to write secure code. The security of your code is crucial to ensure that your application functions safely and protects user data. However, a lot of times, developers use the eval() function to evaluate Python expressions dynamically. While this can be useful, it can also pose a serious security threat if not used properly.

The good news is that there’s a solution to this problem – Safe Eval. Safe Eval is a Python module that provides a safe version of the eval() function. With Safe Eval, you can still evaluate Python expressions dynamically, but without compromising the security of your code.

In this article, we will introduce you to Safe Eval, explain how it works, and provide you with examples of how to use it in your Python code. Whether you’re a beginner or an experienced developer, this guide will help you make more secure applications using Safe Eval.

So, if you want to learn how to secure your Python code with Safe Eval and make sure your application is safe from malicious attacks, keep reading!

Python: Make Eval Safe [Duplicate]
“Python: Make Eval Safe [Duplicate]” ~ bbaz


Python is a popular programming language due to its straightforward syntax and fast development time. However, as with any language, it has its strengths and weaknesses. One critical weakness is that it is inherently difficult to secure Python code.

One possible solution is to use an evaluation tool, such as safe eval, to ensure that Python code runs securely. In this article, we’ll explore the benefits of using Safe Eval and compare it to other evaluation tools.

What is Safe Eval?

Safe Eval is a tool that allows developers to implement Python code evaluation in a secure manner. Unlike standard Python eval(), Safe Eval ensures that only a predefined subset of Python is executed, and that no dangerous code can be run.

Safe Eval works by taking a Python string as input and calling safe_eval() to evaluate the code. The safe evaluation process goes beyond just checking syntax errors, Safe Eval blocks unsafe features from executing, including dangerous built-in functions, assignments, import statements, and more.

Types of Python Evaluation Tools

Standard eval() function

The standard eval() function in Python is not entirely secure, as it allows arbitrary code execution. It is recommended that developers avoid using eval(), as it can expose a program to security vulnerabilities.

Dangerous input functions

Other input functions, such as raw_input() or input(), also pose security risks. Unsafe data passed through these functions can execute malicious code, revealing sensitive data, or manipulating system settings.

Third-party libraries

Third-party libraries, such as ast.literal_eval(), allow safer evaluation of small code snippets, but they have limitations. They do not provide full functionality, and elements like exception handling or user-defined functions may not work correctly.

Benefits of Safe Eval


The primary advantage of Safe Eval is its security. It prevents arbitrary code execution and limits a program’s exposure to security vulnerabilities.


Safe Eval’s features are customizable, so developers can define the subset of Python they want to allow, making it flexible and adaptable to various use cases.

Easy implementation

Safe Eval is easy to implement. It has a simple API, which requires only a few lines of code to include in a project. Developers can also modify the existing settings or build new ones using the Safe Eval source code, written entirely in Python.

Comparison Matrix

In summary, below is a comparison chart of Safe Eval with other Python evaluation tools:

Tool Security level Customizability Implementation complexity
Standard eval() Low No Low
Dangerous input functions Low No Low
Third-party libraries Medium Partial Medium
Safe Eval High Customizable Low


Python’s unique syntax is both a strength and weakness. It requires careful evaluation to ensure security and prevent vulnerabilities from arising in a program. Using Safe Eval can aid developers in creating secure Python code by enabling customizable and secure code executions. It is a powerful tool that can help keep your code, and your projects secure.

Thank you for visiting our blog and reading about how you can secure your Python code with Safe Eval. We hope you have found this information valuable in ensuring the security of your software programs.

As the world increasingly relies on technology, the importance of software security cannot be overstated. Safe Eval provides a valuable tool in preventing vulnerabilities and attacks, ultimately keeping your data and systems safe. By taking proactive steps to secure your Python code, you can protect your organization from potentially devastating consequences.

We encourage you to continue learning about software security and exploring ways to protect your code from malicious actors. Remember, investing in the security of your software today will pay off in the long run by safeguarding your assets and reputation.

Python is a popular programming language that is widely used in various industries. However, one of the challenges of using Python is ensuring that your code is secure. Fortunately, there are tools and techniques that you can use to secure your Python code, such as Safe Eval.

People Also Ask About Secure Your Python Code with Safe Eval:

  1. What is Safe Eval?

    Safe Eval is a Python library that provides a safer alternative to Python’s built-in eval() function. It allows you to evaluate untrusted Python code in a sandboxed environment, preventing malicious code from accessing sensitive data or resources on your system.

  2. How does Safe Eval work?

    Safe Eval works by creating a separate execution environment for the code you want to evaluate. This environment limits the resources and capabilities available to the code, preventing it from accessing sensitive data or resources on your system. Safe Eval also performs various checks on the code to ensure that it is safe to execute.

  3. Why should I use Safe Eval?

    If you need to evaluate untrusted Python code, using Safe Eval can help you avoid security risks. By sandboxing the code and limiting its capabilities, you can prevent it from causing harm to your system or accessing sensitive data. Safe Eval can also help you comply with security standards and regulations.

  4. Can Safe Eval be used for all types of Python code?

    Safe Eval is designed to work with most types of Python code, including expressions, statements, and functions. However, there may be some cases where certain features or modules are not supported. It is important to review the Safe Eval documentation and test your code thoroughly before using it in a production environment.

  5. How do I install and use Safe Eval?

    You can install Safe Eval using pip, the Python package manager. Once installed, you can import the safe_eval module and use it to evaluate untrusted Python code. The Safe Eval documentation provides detailed instructions and examples to help you get started.

By using Safe Eval, you can help ensure that your Python code is secure and protected from malicious attacks. It is important to stay up-to-date with the latest security best practices and tools to keep your systems and data safe.

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