AI Models Excelling in Web Application Security Challenges: A Performance and Cost Analysis

In a recent evaluation, a cybersecurity expert developed a framework to assess the performance of leading AI models in solving Capture The Flag (CTF) challenges for web applications. The models evaluated included GPT-5, Claude Sonnet 4.5, Gemini 2.5 Pro, and Grok. The assessment consisted of 32 challenges, with each model allowed 2 attempts and 50 turns per challenge. According to the findings, GPT-5 and Claude Sonnet 4.5 both successfully resolved 29 out of 32 challenges. However, GPT-5 achieved this with a 63% lower cost compared to Sonnet 4.5. Additionally, GPT-5 Mini demonstrated a notable performance-to-price ratio, resolving 26 out of 32 challenges at an 84% lower cost than Sonnet 4.5. These results highlight the growing capability of AI models in addressing cybersecurity challenges. The ability to solve CTF challenges suggests that these models can effectively identify and exploit vulnerabilities in web applications. This has significant implications for both offensive and defensive cybersecurity practices. From an offensive perspective, AI models could be used to automate the discovery and exploitation of vulnerabilities, potentially increasing the frequency and sophistication of attacks. On the defensive side, these tools can assist security professionals in identifying and mitigating vulnerabilities more efficiently. The cost efficiency of models like GPT-5 and GPT-5 Mini is particularly noteworthy. Lower costs could democratize access to advanced cybersecurity tools, making them available to smaller organizations and individual researchers. This could lead to a more level playing field in cybersecurity, where advanced capabilities are not limited to well-funded entities. However, it is crucial to recognize that while AI models can be powerful tools, they are not a substitute for human expertise. Human judgment remains essential for understanding context, making ethical decisions, and applying nuanced reasoning to complex security scenarios. The rapid evolution of AI capabilities underscores the importance of continuous learning and adaptation in the cybersecurity field. For a more detailed analysis and comprehensive results, refer to the original article.