How does iptables basics differ between distributions?

Iptables is a powerful tool used for managing network traffic on Linux-based systems. However, the basics of iptables can differ slightly between various Linux distributions due to their package management systems, default configurations, and the tools that come pre-installed. Understanding these differences can help system administrators effectively manage firewall settings across different environments.

Some distributions, like Ubuntu and Debian, may use ufw (Uncomplicated Firewall) as a front-end for iptables, which simplifies the command usage for users who may not be familiar with iptables' extensive command line options. Meanwhile, CentOS and Fedora might rely on firewalld, which is a dynamic firewall daemon that provides a different layer of abstraction on top of iptables.

Here are some key differences:

  • Default Configuration: Some distributions have iptables rules pre-defined, while others may start with a default DROP policy.
  • Management Tools: Different distributions might come equipped with different management tools, affecting how iptables rules are managed.
  • Service Commands: The way to start, stop, or reload iptables can vary across distributions.

Below is an example of setting up a simple rule in iptables on a CentOS-based system:

# Allow inbound SSH traffic iptables -A INPUT -p tcp --dport 22 -j ACCEPT # Allow inbound HTTP traffic iptables -A INPUT -p tcp --dport 80 -j ACCEPT # Default policy to drop all other traffic iptables -P INPUT DROP # Save the iptables rules service iptables save

iptables Linux firewall iptables differences Ubuntu iptables CentOS iptables firewall configuration

Related Questions

How do I avoid rehashing overhead with std::set in multithreaded code?

How do I find elements with custom comparators with std::set for embedded targets?

How do I erase elements while iterating with std::set for embedded targets?

How do I provide stable iteration order with std::unordered_map for large datasets?

How do I reserve capacity ahead of time with std::unordered_map for large datasets?

How do I erase elements while iterating with std::unordered_map in multithreaded code?

How do I provide stable iteration order with std::map for embedded targets?

How do I provide stable iteration order with std::map in multithreaded code?

How do I avoid rehashing overhead with std::map in performance-sensitive code?

How do I merge two containers efficiently with std::map for embedded targets?