This paper examines injection vulnerabilities in web applications, which remain a critical security threat according to OWASP Top 10:2021. The study evaluates traditional detection methods like Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST), while exploring emerging approaches such as Interactive Application Security Testing (IAST) and AI-driven solutions. Key findings demonstrate how integrating signature-based detection (SBD) and anomaly-based detection (ABD) within IAST frameworks improves accuracy in identifying zero-day attacks and complex injection vectors. The research emphasizes proactive security measures including strict input validation, parameterized queries, and contextual output encoding. Notably, tools like SonarQube, Semgrep, OWASP ZAP, and Arachni are analyzed for their effectiveness in DevOps environments. The study concludes that a hybrid approach combining automated testing, developer education, and AI-enhanced solutions offers the most robust defense against evolving web application threats.