Zero-Trust architecture is a security approach built on the principle of “never trust, always verify.” Unlike traditional perimeter-based security, it treats every access request as suspicious, whether you are inside or outside the network. In my nearly 20 years of experience, I’ve repeatedly seen how significant the risks posed by not only external threats but also internal vulnerabilities can be. Many times, I’ve witnessed how quickly a malicious actor or a misconfigured service can spread, even within an internal network we considered secure.
In this post, I will share three practical steps I’ve taken when integrating Zero-Trust architecture into my own systems or client projects, along with the experiences I gained during this process. These steps are tangible applications that truly work in the field, rather than a theoretical framework. My goal is to make this seemingly complex topic more concrete and actionable.
1. Strengthening Authentication and Authorization (IAM)
At the core of Zero-Trust is the continuous verification of the identity of every user and device. In older systems, it was common for a user to be granted full privileges upon entry. However, this means that if an account is compromised, the entire network is put at risk. I saw this error in an old Active Directory integration; when a service account was compromised, it gained access to almost the entire production environment.
Therefore, the first step has always been to strengthen the Identity and Access Management (IAM) infrastructure. Multi-factor authentication (MFA) and role-based access control (RBAC) are critical here. In the backend of my side projects or in a production ERP, I centralized authentication processes using standards like OpenID Connect (OIDC) and OAuth2. This allows each application to communicate with a central Identity Provider (IdP) instead of writing its own authentication mechanism.
On the RBAC side, it’s essential to ensure that each user has only the minimum privileges necessary for their job. For example, a production operator should only be able to see and complete the production orders for their own shift, while the accounting department should only be able to access financial reports. In my experience, you need to understand the “workflow” very well when making this distinction. When I say that software architecture is often not software but organizational flow, this is exactly what I mean. Otherwise, even if you write very strict RBAC, users will constantly look for “bypass” methods because they can’t do their jobs.
# A simple RBAC check example in a FastAPI application
from fastapi import Depends, HTTPException, status
from typing import Set
# In a real application, this is read from a JWT token coming from an IdP
def get_current_user_roles() -> Set[str]:
# This part parses the JWT token and returns the user's roles
# For example, {"admin", "operator"}
return {"operator"} # Default role for demo purposes
def role_required(required_roles: Set[str]):
def role_checker(user_roles: Set[str] = Depends(get_current_user_roles)):
if not required_roles.intersection(user_roles):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="You do not have permission to access this operation."
)
return True
return role_checker
# Usage example
@app.get("/production-orders", dependencies=[Depends(role_required({"operator", "manager"}))])
async def get_production_orders():
return {"message": "Listing production orders."}Code snippets like this are used every day in the production ERP I developed. The get_current_user_roles function reads the roles claim inside the JWT token and authorizes accordingly. If a user doesn’t have the required roles, they receive a 403 Forbidden error. This can be applied not only at the application level but also at the API Gateway layer.
2. Segmenting the Network with Micro-Segmentation
In traditional networks, there was a distinction between the “secure zone” (LAN) and the “insecure zone” (WAN). It was assumed that a device entering the internal network could access everything. This allows an attacker to spread across the entire system through “lateral movement” in the event of a breach. I experienced this problem many times because of VLAN tagging chaos. Due to a faulty VLAN configuration, I saw an accounting department computer able to access the PLCs on the production line; this was a nightmare scenario.
In Zero-Trust, however, the network is divided into the smallest, most isolated pieces possible. Each piece is protected within itself by firewall rules. This is called micro-segmentation. In my approach, I first divide all the resources on the network (servers, databases, IoT devices, user devices) into groups. Then, I define firewall policies that allow the minimum communication between these groups.
For example, in a production ERP:
- Database servers: Only allow TCP 5432 (PostgreSQL) traffic coming from application servers.
- Application servers: Only allow traffic coming from web servers and specific management IPs, and can also connect to database servers.
- Web servers: Only allow inbound HTTP/HTTPS traffic and outbound traffic to application servers.
- Operator screens: Can only access production line applications and specific management servers.
I apply this segmentation both at the network layer (VLANs, ACLs) and at the host layer (iptables, firewalld).
# A simple iptables rule on the PostgreSQL server that only allows
# traffic coming from a specific application server IP.
# You must carefully check the existing rules before adding this one!
sudo iptables -A INPUT -p tcp --dport 5432 -s 192.168.1.100 -j ACCEPT
sudo iptables -A INPUT -p tcp --dport 5432 -j DROPIn this example, no one except the application server at IP address 192.168.1.100 can access the PostgreSQL port. This is one of the most basic micro-segmentation steps. In complex scenarios, NFTables or the ACLs of hardware network devices are used. In particular, in work I did for a bank’s internal platform, I saw that each application was isolated within its own virtual network and could only communicate through specific APIs. Although this led to routing flap problems in an environment with around 2,500 virtual machines, when designed correctly it provides a major gain in terms of security. my notes on VLAN segmentation
3. Ensuring Continuous Verification and Device Security (Device Posture)
Zero-Trust focuses not only on the question “who are you?” but also on “where are you coming from and what is your state?” Before or during a device’s access to the network, its security posture (device posture) must be continuously checked. This includes checks such as whether the device has an up-to-date operating system, whether antivirus software is running, and whether certain security patches are installed.
In my practice, this step usually happens through a ZTNA (Zero-Trust Network Access) solution or a specially developed agent. For example, when a user’s laptop tries to connect to the company network, it is checked whether the device’s disk encryption is enabled and whether the latest security update is older than 30 days. If these conditions aren’t met, the device is granted access only to patch servers or a quarantine network.
I use a similar mechanism for access to my own side product’s management interface. If my device doesn’t meet a certain security policy (for example, if the VPN isn’t connected or it isn’t coming from a specific IP range), access is blocked.
# Using auditd on Linux servers to monitor file integrity.
# Added to the /etc/audit/rules.d/audit.rules file.
# This rule logs every change to the /etc/passwd file.
-w /etc/passwd -p wa -k identity_changes
# Restart the auditd service
sudo systemctl restart auditd
# View the logs (for example, after a change to the passwd file)
# sudo journalctl -u auditd | grep identity_changesThe use of auditd in this example lets me continuously monitor the integrity of critical files on the device. If there is an unauthorized change to the passwd file, an alarm is triggered immediately. This is just one of the practical steps I take to maintain the device’s secure posture. In more complex scenarios, enterprise EDR solutions perform these checks in much greater detail. Similarly, using fail2ban, I continuously monitor failed login attempts on my servers and automatically ban IP addresses when I catch certain patterns. improving server security with Fail2ban
The Challenges of Zero-Trust and My Approach
The transition to a Zero-Trust architecture holds serious challenges, especially for large and complex enterprise structures. One of the biggest challenges is integration with existing legacy systems. Since many old applications weren’t designed in accordance with Zero-Trust principles, adapting them can sometimes be as hard as rewriting the application. For example, on a bank’s internal platform, converting an old COBOL application’s Active Directory integration to OAuth2 required an effort that took months.
Another challenge is user experience (UX). Continuous authentication and strict access controls can be annoying for users at first. Complaints like “Is it asking for a password again?” and “Why can’t I access this application?” are inevitable. My approach to this is to make the transition gradual and to clearly explain to users why these changes are being made. I generally apply Zero-Trust principles starting with the systems that hold the most critical and sensitive data.
In addition, there’s also the cost dimension of Zero-Trust. New tools, additional licenses, and training can require a significant investment at the start. For me, the return on this investment stays far below the cost and reputational loss that a potential cyberattack would create. Last year, in a client project, we calculated the cost of a potential data breach at 2.5 million USD. The 250,000 USD investment made in the Zero-Trust infrastructure eliminated a large part of this risk.
Real-World Applications and My Expectations
Zero-Trust architecture is now a topic that needs to be on the agenda of not just large enterprise companies, but also SMBs and even my own small projects. Especially with the spread of remote work and the increase in cloud-based services, traditional network boundaries have blurred. There is no longer a world where everyone is connected to the office network.
When applying Zero-Trust principles in my own systems (such as the backend of my side products running on a VPS), I generally prefer lighter, open-source tools. For example, JWT-based access control with Nginx, continuous monitoring with fail2ban, and micro-segmentation with iptables. On a large TR e-commerce site, however, I saw this architecture implemented with more comprehensive ZTNA solutions and SIEM integrations.
In the coming period, I think AI’s role in Zero-Trust architecture will increase even further. In areas like anomaly detection, behavior analysis, and automatic policy updates, AI will make Zero-Trust smarter and more proactive. For example, if a user tries to access a resource they normally don’t access at 3:00 at night, AI can detect this behavior as an anomaly and automatically block access or send an additional authentication request. In my own AI application architecture, I’m working on similar anomaly detection algorithms using models like Gemini Flash and Groq.
Zero-Trust is not a product but a philosophy and a continuously evolving process. It doesn’t end with a one-time setup; it requires continuous monitoring, policy updates, and adaptation. For me, this will continue to be one of the most exciting and challenging areas as a security architect. I believe that in the future we’ll see more companies turning to this approach, and the impact of cybersecurity incidents decreasing as a result.