S4E just found a high-severity finding from top 10 tcp port service scan
low·Information Scans·Updated Jan 28, 2026

BigCommerce Phishing Detection Scanner

This scanner detects the use of BigCommerce Phishing in digital assets. Phishing involves the impersonation of the legitimate BigCommerce platform for malicious purposes, potentially affecting the security of business transactions and client data. This detection is crucial for maintaining the integrity and trustworthiness of online commerce platforms.

Est. Time~10 seconds
Scan TypeSingle Scan
Targetsurl
CostFree
3.4k
Times Used
continuous scan runs
3.4k
Continuously Checked
assets under CS
0
Vulnerabilities Found
confirmed findings
References
Detail

BigCommerce is a prominent e-commerce platform used by businesses worldwide to manage online sales. It is widely adopted by small to medium-sized businesses seeking a robust online store infrastructure. The platform offers a range of customizable features to help businesses create a seamless shopping experience. It is frequently used by companies for its comprehensive tools and scalability that cater to various e-commerce needs. The software allows users to build their websites with integrated marketing and security features. Thus, ensuring data security is a critical concern for BigCommerce users, warranting routine checks against vulnerabilities.

Phishing on e-commerce platforms like BigCommerce involves mimicking legitimate sites to deceive users into divulging sensitive information. This detection focuses on identifying fake sites misusing the BigCommerce brand without authorization. The method includes checking for elements typical of BigCommerce pages but with discrepancies indicating phishing. Such activities can target customers and compromise personal and financial information. Therefore, the identification of phishing activities is crucial in safeguarding user trust and data security. By detecting these activities early, businesses can mitigate potential damages caused by fraudulent practices.

The detection involves a strategic examination of web pages to identify BigCommerce identifiers not associated with legitimate URLs. Key identifiers include specific HTML elements, status codes, and page titles indicative of BigCommerce without legitimate connection. URLs are checked against known BigCommerce domains to flag discrepancies. By detecting HTTP status codes like '200' within suspicious domains, the process identifies unauthorized BigCommerce replicas. Another technical check includes verifying the absence of authentic BigCommerce links in headers and bodies. Such precision in detection helps ensure high accuracy in identifying phishing risks.

The exploitation of phishing vulnerabilities can lead to severe consequences, including identity theft and unauthorized transactions. Cybercriminals can harvest personal information, leading to potential financial and reputational losses. A breached business environment might result in loss of customer trust and reduced confidence in digital transactions. Additionally, there can be legal implications and financial penalties associated with data breaches. Companies may experience operational disruptions as a result of managing and recovering from such cyber attacks. The ripple effect on customer service and long-term business growth can be significant.

REFERENCES

Solution Advice
  • Regularly monitor your digital assets for discrepancies that might indicate phishing attempts.
  • Educate employees and customers about identifying and reporting phishing attempts associated with your brand.
  • Implement SSL certificates and security markers to validate your legitimate BigCommerce platform pages.
  • Use advanced email filtering to detect and mitigate spoofed BigCommerce communications.
  • Enhance your cybersecurity framework by incorporating multi-factor authentication for sensitive transactions.

Get AI-powered remediation steps tailored to your asset.

Try AI Solutions →

Check your infrastructure.
Right now.

11,000+ scanners. Free to start. No credit card required.