Identifying web clients through TLS fingerprinting can significantly enhance fraud detection by distinguishing between legitimate users and malicious actors. TLS, a web protocol that encrypts communications, begins with a handshake process where clients and servers exchange messages to establish secure connections. During this handshake, unique characteristics of the client's communication, such as the order of cipher suites and other parameters, can be used to generate a TLS fingerprint that reveals information about the client's browser and operating system. This method, alongside other identification techniques like cookies and browser fingerprinting, adds an additional layer of security by flagging bots or spoofed clients. Real-world applications of TLS fingerprinting include threat detection, enforcing security policies, and analyzing client behavior, with tools like JA3 and JA4 providing robust methods for identifying suspicious traffic patterns. As cyber threats evolve, combining TLS fingerprinting with other signals can improve the accuracy of anti-fraud measures and enhance the protection of online platforms against botnets, DDoS attacks, and outdated application vulnerabilities.