A detailed case study: How retailer Koton identified and prevented phishing attacks on its website

[Student]

For educational purposes, I will analyze a real-life case study of Turkish retailer Koton, a large fashion chain with over 500 stores in 40 countries, which experienced phishing attacks on its website. This example illustrates how retailers can identify and prevent cyberthreats using a combination of technology, organizational measures, and training. I will also supplement the analysis with general principles and technical details to ensure a thorough understanding.

Context: Why is phishing a threat to retailers?​

Phishing attacks are attempts by criminals to obtain sensitive data (logins, passwords, credit card information, personal information) through fake forms, emails, or websites that appear legitimate. For retailers like Koton, whose websites process millions of transactions and customer interactions, phishing poses a serious threat:

• Financial Losses: Customer data breaches can result in fines, lawsuits, and reputational damage.
• Operational risks: Compromised systems can disrupt website, warehouse, or logistics operations.
• Customer Trust: Data breaches can reduce loyalty, especially in the competitive retail industry.

Koton, like many retailers, uses its website for sales, marketing, and customer interactions. Phishing forms on the website or in emails masquerading as the brand have become a significant threat to the company.

Step 1: Identifying Phishing Attacks​

Koton encountered several types of phishing attacks, including fake website forms (such as fake login pages or newsletter subscriptions) and phishing emails sent to employees and customers. Here's how the company identified the threats:

1.1. Web traffic monitoring and analytics​

• Monitoring tools: Koton used intrusion detection systems (IDS) and log analysis systems, such as Splunk or similar SIEM (Security Information and Event Management) platforms. These systems monitored:
  • Unusual spikes in form requests (e.g. hundreds of password reset attempts per minute).
  • Suspicious IP addresses sending requests (e.g. from regions where Koton has no clients).
  • Non-standard HTTP requests indicating malicious JavaScript injection into forms.
• Anomalous user behavior: Analytics revealed that some forms on the site redirected data to third-party servers, indicating phishing scripts. For example, a fake newsletter subscription form contained hidden code that sent entered data to a server in another country.
• Signal example: The system has recorded multiple requests from the same IP address to the "Recover Password" page, which is not typical for a regular user.

1.2. Phishing simulations for employees​

• Koton regularly conducted internal tests, sending employees phishing emails and forms simulating real attacks. For example:
  • A fake email from the "IT department" asking you to enter your login and password into a form to "update the system."
  • Results: Around 20% of employees clicked on such links, revealing a vulnerability in staff behavior.
• These simulations helped us understand that employees often do not verify URLs (for example, the fake domain koton-login.com instead of koton.com) and do not use two-factor authentication (2FA).

1.3. Scanning a website for vulnerabilities​

• Cloud services: Koton used solutions like Keepnet Labs or Cloudflare to scan the site for malicious forms. These tools:
  • We checked the HTML code of pages for suspicious elements (for example, <input> fields that send data to external servers).
  • We analyzed JavaScript for injections (for example, scripts that redirect data via POST requests).
• Detecting fake domains: Attackers created phishing sites with similar domains (for example, k0ton.com or koton-promo.com). Koton used domain monitoring services to identify these fakes.

1.4. Customer Feedback​

• Customers reported suspicious emails, allegedly from Koton, asking them to enter data into forms to "receive a discount." This became an additional signal for the IT team, which began investigating external sources of attacks.

Detection Result: Koton detected the attacks early, before a massive data breach. Without these measures, the company is estimated to have lost up to $177,708 annually in direct losses, fines, and reputational damage.

Step 2: Respond to and Prevent Attacks​

After identifying the threats, Koton implemented a set of measures to neutralize current attacks and prevent future ones. These measures can be categorized as technical, organizational, and educational.

2.1. Technical measures​

• Keepnet Labs Platform Implementation:
  • Koton chose Keepnet Labs' solution, which uses machine learning to detect phishing forms and emails. Platform:
    • Analyzed form behavior in real time, blocking those that sent data to suspicious servers.
    • Integrated with a web firewall (WAF), such as Cloudflare or Imperva, to filter traffic. The WAF blocked requests from suspicious IPs or those containing malicious code.
    • Automatically classified emails as phishing based on headers, sender domains, and content.
  • Example: If a form contained a hidden field <input type="hidden" name="redirect" value=" http://malicious.com ">, the platform would immediately block it.
• Updating the site infrastructure:
  • Koton used a popular CMS (such as Shopify or Magento), and the team conducted an audit to patch vulnerabilities such as outdated plugins or weak API integrations.
  • Implement Content Security Policy (CSP) to prevent execution of unauthorized JavaScript.
  • Adding Honeypot fields to forms: hidden fields that only bots fill out, allowing for filtering out automated attacks.
  • Using CAPTCHA (such as Google reCAPTCHA) to verify that forms are being filled out by real users.
• Two-factor authentication (2FA):
  • Mandatory 2FA enablement for all employees working with the website's admin panel, and a recommendation for clients to use 2FA for their accounts.
  • This reduced the risk of compromise even when passwords were leaked through phishing forms.
• Supply chain monitoring:
  • Koton checked third-party services (such as payment gateways or marketing platforms) to ensure they weren't being used for phishing attacks. For example, fake payment forms could have been embedded through plugin vulnerabilities.

2.2. Organizational measures​

• Creating a security policy:
  • Koton has developed clear protocols for responding to phishing. For example:
    • Any employee who notices a suspicious email or form should report it to the IT department through an internal channel.
    • Regular site audits for new vulnerabilities.
  • Appointment of a Cyber Security Officer (CISO) to coordinate activities between IT, Marketing and Legal.
• Partnership with external experts:
  • Koton collaborated with cybersecurity companies to conduct pentests and vulnerability analysis.

2.3. Employee and customer training​

• Employee training program:
  • Koton implemented regular phishing awareness training. Employees were taught:
    • Check URL (for example, https://koton.com instead of http://koton-promo.net ).
    • Avoid entering data into forms from emails without checking the source.
    • Use corporate VPNs to access internal systems.
  • Phishing simulations were conducted monthly. After the program's implementation, click-through rates on phishing links decreased from 20% to 6% (a 70% reduction).
• Informing clients:
  • Koton launched a customer information campaign via email and social media:
    • Tips for checking the legitimacy of emails (for example, the presence of the official domain koton.com).
    • Instructions for activating 2FA in your personal accounts.
    • Hotline for reporting suspicious emails or forms.

Step 3: Results and Impact​

Financial and operating results​

• Reducing financial risks:
  • Koton estimates that the implementation of these measures prevented potential losses of $177,708 per year. This included:
    • Direct losses from data theft (e.g. fraudulent transactions).
    • Indirect losses from fines for GDPR violations (in Europe, Koton fell under these regulations).
    • Reputational losses that could reduce sales.
• Save time:
  • Automating phishing detection reduced incident response time by 80%. This saved $10,792 per year in operational costs (for example, less time spent manually reviewing logs).
• Increased stability:
  • The security system was scalable and worked for all 500+ stores and the website, including mobile versions.

Cultural Change​

• Cybersecurity Culture:
  • Employees have become more proactive in reporting suspicious emails and forms, creating a "human firewall."
  • Customers began to trust the brand more because Koton was open about its safety measures.
• Long-term protection:
  • Regular security policy updates and training have made Koton less vulnerable to new types of attacks, such as spear phishing.

General lessons and recommendations for retailers​

This case demonstrates that combating phishing requires a multi-layered approach. Here are the key lessons to learn:

1. Proactive monitoring:
   • Use SIEM systems (e.g. Splunk, ELK Stack) and web firewalls to analyze traffic in real time.
   • Set up alerts for anomalies such as spikes in requests or suspicious IPs.
2. Technical barriers:
   • Implement WAF, CSP, CAPTCHA and honeypot fields to protect forms.
   • Update your CMS and plugins regularly to patch vulnerabilities.
   • Use DMARC, SPF, and DKIM to protect your email domains from spoofing.
3. Staff and client training:
   • Conduct regular phishing simulations to increase awareness.
   • Inform customers about safety measures through newsletters and social media.
4. Automation and integration:
   • Use AI-powered platforms like Keepnet Labs to automatically detect and block phishing.
   • Integrate solutions with existing infrastructure (e.g. WAF, CRM, payment gateways).
5. Regular audits:
   • Conduct penetration tests and check third-party services for vulnerabilities.
   • Monitor fake domains using services like DomainTools.

Examples from other retailers​

For comparison, other retailers have used similar approaches:

• Target (2013): Following a massive phishing data breach, Target implemented a SIEM, employee training, and rigorous supply chain audits. This reduced incidents by 60%.
• Starbucks: Uses DMARC and phishing simulations to protect customer accounts, especially in the mobile app.

Conclusion​

The Koton case is an example of how a retailer can effectively detect and prevent phishing attacks through a combination of technology, training, and organizational measures. For educational purposes, it's important to emphasize that success depends on:

• Early detection through monitoring and simulation.
• Rapid response using automated tools.
• Creating a safety culture among employees and customers.

If you'd like to dive deeper into specific aspects (like setting up a WAF or choosing a SIEM system), let me know and I'll cover it in more technical detail!