Top Python Security Tools

Python's elegant syntax and powerful libraries have made it the language of choice for web development, data science, machine learning, and more. From startups to tech giants, teams rely on Python to build innovative products quickly. But this popularity comes with a security price tag. Common vulnerabilities like injection flaws, insecure dependencies in requirements.txt, and exposed secrets can turn a powerful application into an open door for attackers.

Securing your Python code is crucial, but it needs to be done without slowing down the development process. You need tools that can find real flaws, integrate smoothly into your CI/CD pipeline, and give developers clear, actionable feedback. The market is filled with options, from simple open-source scanners to comprehensive security platforms. How do you choose the right one for your project?

This guide is designed to provide clarity. We will offer an honest, detailed comparison of the top Python security tools for 2026. By analyzing their features, strengths, and ideal use cases, we'll help you find the perfect solution to keep your Python applications secure and your development team productive.

How We Evaluated the Python Security Tools

We assessed each tool based on the criteria that matter most for modern development and security teams:

• Developer Experience: How easily does the tool fit into a developer's daily workflow and provide feedback?
• Comprehensiveness: Does the tool cover static code analysis (SAST), dependency scanning (SCA), and secret detection?
• Accuracy and Actionability: How effective is the tool at finding real vulnerabilities while minimizing false positives and providing clear fix guidance?
• Integration and Speed: How well does it integrate into CI/CD pipelines, and how quickly does it provide feedback?
• Scalability and Pricing: Can the tool support a growing organization, and is its pricing model transparent?

The 6 Best Python Security Tools

Here is our analysis of the best tools available for securing your Python codebase.

1. Aikido Security

Aikido Security is a developer-first security platform that unifies all aspects of application security into a single, cohesive experience. For Python developers, it consolidates findings from nine different security scanners—covering custom code, dependencies (from requirements.txt or Poetry), secrets, and cloud infrastructure—and intelligently triages them to show only what's truly important. Its core mission is to eliminate noise and empower developers with AI-driven fixes directly within their workflow.

Key Features & Strengths:

• Unified Security Platform: Combines SAST, SCA, secret detection, and IaC scanning into one dashboard. This provides a complete view of your Python project's risk without the need to manage alerts from multiple tools.
• Intelligent Triaging: Automatically identifies which vulnerabilities in your code or dependencies are actually reachable and exploitable. This allows developers to focus on the critical issues and ignore the noise.
• AI-Powered Autofixes: Delivers automated code suggestions to resolve vulnerabilities directly within pull requests. For Python, this can include updating packages in requirements.txt or patching vulnerable code, dramatically speeding up remediation.
• Seamless Developer Integration: Natively integrates with GitHub, GitLab, and other CI/CD tools in minutes. Security feedback is delivered as comments in pull requests, making it a frictionless part of the development process.
• Enterprise-Ready with Simple Pricing: Built to handle the demands of large organizations, Aikido offers robust performance with a straightforward, flat-rate pricing model that simplifies budgeting.

Ideal Use Cases / Target Users:

Aikido is the best overall solution for any organization, from startups to enterprises, that wants to make security an intrinsic part of its Python development process. It is perfect for development teams taking ownership of security and for security leaders who need a scalable, efficient platform.

Pros and Cons:

• Pros: Exceptionally easy to set up, consolidates the functionality of multiple tools, drastically reduces false positive alerts, and offers a generous free-forever tier.
• Cons: As a comprehensive platform, it replaces many point solutions, which might be a change for teams accustomed to a multi-vendor security stack.

Pricing / Licensing:

Aikido offers a free-forever tier with unlimited users and repositories. Paid plans unlock advanced capabilities with simple, flat-rate pricing.

Recommendation Summary:

Aikido Security is the top choice for organizations seeking to integrate comprehensive and efficient security into their Python development. Its developer-centric design and intelligent automation make it the premier solution for shipping secure applications at speed and scale.

2. Bandit

Bandit is a free and open-source tool designed to find common security issues in Python code. It works by parsing each file, building an abstract syntax tree (AST) from it, and running appropriate plugins against the AST nodes. It is a lightweight and focused static analysis tool created by the Python Code Quality Authority (PyCQA).

Key Features & Strengths:

• Focused on Python Security: Specifically designed to identify common security vulnerabilities in Python code, such as issues with pickle, yaml.load, and risky function calls.
• Fast and Lightweight: As a command-line tool, it runs very quickly, making it ideal for pre-commit hooks and fast CI/CD pipeline checks.
• Highly Configurable: You can easily specify which tests to run or ignore, and you can define confidence and severity levels to filter out noise.
• Extensible: Allows you to write your own custom plugins to check for security issues specific to your codebase or framework (like Django or Flask).

Learn more about the role of Bandit among leading security tools in our roundup of top open-source dependency scanners.

Ideal Use Cases / Target Users:

Bandit is an excellent starting point for any Python developer or team looking to add a basic layer of static security analysis to their projects. It's perfect for running in a CI/CD pipeline to catch low-hanging fruit.

Pros and Cons:

• Pros: Free and open-source, very fast, easy to set up, and highly configurable.
• Cons: It is not a comprehensive security solution. It only performs SAST and won't find vulnerabilities in your dependencies or detect leaked secrets. It may not find complex, multi-step vulnerabilities.

Pricing / Licensing:

Bandit is free and open-source (Apache License 2.0).

Recommendation Summary:

Bandit is an essential, foundational tool for any Python project. Its speed and simplicity make it a no-brainer for catching common security mistakes early in the development process.

3. Dependabot

Dependabot is a native GitHub feature that helps you keep your dependencies up to date. It automatically scans your Python project's dependency files (like requirements.txt or Pipfile.lock) for known vulnerabilities and can be configured to automatically create pull requests to upgrade them to a secure version.

Key Features & Strengths:

• Native GitHub Integration: As a built-in GitHub feature, it is incredibly easy to enable and use across all your repositories.
• Automated Pull Requests: Saves developers time by automatically generating pull requests to upgrade vulnerable dependencies, complete with release notes and compatibility scores.
• Vulnerability Alerts: Provides security alerts directly in your repository when new vulnerabilities are discovered in your project's dependencies.
• Broad Language Support: While we're focused on Python, it supports a wide range of other languages and package managers as well.

Ideal Use Cases / Target Users:

Dependabot is an essential, foundational tool for any team developing Python projects on GitHub. It's the first line of defense against open-source vulnerabilities and requires almost no effort to set up.

Pros and Cons:

• Pros: Free, seamlessly integrated into GitHub, and highly effective at automating dependency updates.
• Cons: It only covers open-source dependencies (SCA). It does not scan for vulnerabilities in your custom code or detect leaked secrets. It is also limited to the GitHub ecosystem.

Pricing / Licensing:

Dependabot is free for all public and private repositories on GitHub.

Recommendation Summary:

Dependabot is a non-negotiable tool for basic dependency security on GitHub. It’s a simple, powerful, and free way to manage the risk from your open-source Python packages.

4. Semgrep

Semgrep is a fast, open-source static analysis tool that is gaining popularity for its flexibility and developer-friendly approach. It uses a simple, intuitive rule syntax that makes it easy for developers and security engineers to write custom checks for their Python codebase.

Key Features & Strengths:

• Lightweight and Fast: Semgrep is designed to run quickly in CI/CD pipelines, providing near-instant feedback on every commit.
• Customizable Rules: It’s easy to write custom rules tailored to your organization’s specific coding patterns, frameworks (like Django or Flask), and security requirements. The rule syntax feels like writing Python code itself.
• Community and Registry: Benefits from a large community that contributes rules to a public registry, covering thousands of checks for security, correctness, and performance in Python and other languages.
• Strong Python Support: Has excellent support for Python and its popular frameworks, making it easy to find framework-specific vulnerabilities.

Ideal Use Cases / Target Users:

Semgrep is great for teams that want a fast, customizable static analysis tool for their Python projects. It’s loved by security engineers who want to write their own checks and developers who appreciate its speed and precision.

Pros and Cons:

• Pros: Extremely fast, highly customizable, free and open-source core, and a strong community.
• Cons: While powerful for custom checks, it may not have the same depth of analysis for complex bugs as some enterprise tools. It needs to be combined with an SCA tool for dependency scanning.

Pricing / Licensing:

Semgrep is open-source and free. Semgrep, Inc. offers a paid commercial platform with features like a centralized dashboard and enterprise support.

Recommendation Summary:

Semgrep is a fantastic choice for teams that value speed and customizability in their static analysis. Its developer-friendly nature makes it a powerful addition to any modern Python security toolchain.

5. Snyk

Snyk is a popular developer-focused security platform that helps teams find and fix vulnerabilities in their code, open-source dependencies, and container images. It is particularly strong in the Python ecosystem.

Key Features & Strengths:

• Developer-First Approach: Integrates seamlessly into IDEs, command lines, and CI/CD tools, providing fast feedback where developers work.
• Strong SCA for Python: Snyk's open-source scanning is highly regarded for its accuracy and comprehensive vulnerability database for packages on PyPI.
• Actionable Remediation Advice: Provides clear explanations and one-click fixes for many types of vulnerabilities, such as automatically creating pull requests to upgrade dependencies.
• Snyk Code (SAST): Offers static analysis to find vulnerabilities in your custom Python code.

Ideal Use Cases / Target Users:

Snyk is ideal for development teams who want to take an active role in security. It’s a great fit for organizations of all sizes that are looking for a user-friendly platform to embed security into their daily workflows.

Pros and Cons:

• Pros: Excellent developer experience, fast scan times, and actionable fix advice. The free tier is generous.
• Cons: Can become expensive at scale. The unification of its various products into a single platform can sometimes feel disjointed. Can still produce a significant number of alerts.

Pricing / licensing:

Snyk offers a free tier that is popular with individual developers. Paid plans are priced based on the number of developers and the features required.

Recommendation Summary:

Snyk is a very popular and effective tool for empowering developers to own security. Its ease of use and focus on fast, actionable feedback make it a strong choice for securing Python projects.

6. PyUp Safety

PyUp Safety is a command-line tool from PyUp that checks your installed Python dependencies for known security vulnerabilities. It is a dedicated Software Composition Analysis (SCA) tool focused purely on the Python ecosystem.

Key Features & Strengths:

• Focused Dependency Scanning: Scans your requirements.txt file or local environment against a curated database of Python package vulnerabilities.
• Simple and Fast: As a command-line tool, it's very easy to install and run, providing quick feedback on the security of your dependencies.
• CI/CD Integration: Can be easily added to any CI/CD pipeline to act as a security gate, failing builds if vulnerable packages are detected.
• Multiple Input Sources: Can check dependencies from requirements.txt files, Pipfile.lock, Poetry lock files, or the local environment.

Ideal Use Cases / Target Users:

Safety is great for developers and DevOps teams who need a simple, fast, and dedicated tool for checking Python dependencies for vulnerabilities. It's a great open-source alternative for SCA.

Pros and Cons:

• Pros: Free for local use, very simple to use, and focuses on doing one thing well.
• Cons: It only performs dependency scanning (SCA). The vulnerability database used by the free version is updated less frequently than the commercial version.

Pricing / Licensing:

Safety is free to use from the command line, but the underlying vulnerability database is only updated monthly. Paid plans from PyUp offer an always-up-to-date database and additional features like CI/CD integration.

Recommendation Summary:

Safety is a simple and effective tool for checking your Python dependencies. For teams needing a dedicated SCA tool that's easy to integrate into CI, it's a solid choice.

Making the Right Choice

Securing your Python applications requires a layered defense. Foundational open-source tools like Bandit for static analysis and PyUp Safety for dependency checking are essential starting points. For those on GitHub, Dependabot is a must-use for automated dependency management.

However, managing a collection of separate tools often leads to alert fatigue, integration headaches, and a fragmented view of risk. A unified platform that solves these challenges provides a clear advantage. Aikido Security stands out by consolidating the functionality of these point solutions into a single, cohesive platform—and by going a step further with its AI-driven approach to penetration testing and robust vulnerability management capabilities.

By integrating security seamlessly into your CI/CD pipeline, triaging alerts to show only what's reachable, and providing AI-powered fixes, Aikido eliminates the friction that holds DevSecOps back. For any organization looking to build a fast, efficient, and secure Python development process, Aikido provides the best balance of comprehensive coverage, developer experience, and enterprise-grade power.