Overview of Techniques¶
A secure test environment protects your system, your data, and ensures your Python programs behave reliably, while allowing safe experimentation and testing unknown Python programs.
Common options for creating a secure test environment:
Docker Containers (or Podman) (isolated, reproducible environments)
BSD Jails:When using BSD, the simplest way to isolate programs is by using Jails. FreeBSD Jails enhance security by providing an OS-level virtualisation method that isolates processes, file systems, and network resources into separate, secure environments on a single kernel.
Use a dedicated testing device (laptop or virtual server) and delete the environment once testing is complete, for example by deleting the virtual machine or reinstalling the operating system. A common OS choice for security testing is Kali Linux.
gVisor. This is an User-space kernel / container sandbox. It provides strong isolation for containers by intercepting system calls and running them in user space instead of letting them touch the host kernel directly.
Security: High — much harder for malicious code in a container to escape to the host system compared to standard Docker.
Use case: Running untrusted code in containers, sandboxing microservices, or isolating test environments. gVisor can be seen as a “mini-kernel” inside your container that acts as a safety layer between the app and the host OS.
Firecracker:A Lightweight micro-VM (Virtual Machine). Firecracker is essentially a very small, fast virtual machine, optimized for security and performance, unlike full VMs which are heavier.
Designed to run thousands of isolated micro-VMs efficiently on a single host, originally for serverless platforms like AWS Lambda and Fargate.
Very high — each micro-VM has its own kernel, so even if code is malicious, it’s contained within the VM.
Comparison:
| Method | Purpose | Security Level |
|---|---|---|
| venv / Conda | Dependency management | None (System access is open) |
| PyPy / RestrictedPython | Software-level restriction | Low (Hard to close all escape vectors) |
| Docker /Podman / Containers | OS-level virtualisation | Medium (Better, but shares a kernel) |
| BSDjail | OS-level virtualisation | High |
| gVisor / Firecracker | Micro-VM / Sandboxing | High (Strongest isolation) |
Security Differences Between Docker and Podman
| Feature | Docker | Podman |
|---|---|---|
| Daemon required | ✅ Yes | ❌ No |
| Rootless support | Optional | Native-first |
| Attack surface | Larger (daemon) | Smaller |
| Multi-user systems | Needs care | Safer by default |
Practical Tip¶
If baseline system security hygiene is in place — for example, using separate user privileges for Python installations and avoiding system-wide package installation — then a Python virtual environment (such as venv or conda) is sufficient for routine security validation of Python libraries.
It should be noted, however, that a virtual environment provides dependency isolation rather than a security boundary. Any malicious code executed within the environment will still run with the privileges of the invoking user. For the analysis of untrusted or potentially malicious code, stronger isolation mechanisms — such as containerisation (e.g. Docker) or full virtual machines — are recommended.