# Behind the Code: Identifying Zero-Day Exploits in WordPress
## 3 Methodology  
To systematically identify and assess vulnerabilities in WordPress plugins while adhering to DAST principles, our approach starts with the creation of a sandbox environment \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Study** & **Approach** & **Key Findings** & **Limitations** & **Citation** \\ \hline [PERSON] and [PERSON] (2013) & Signature-Based & Identified zero-day attacks in the real world & Ineffective against unknown threats & [42] \\ \hline [PERSON] et al. (2010) & Signature-Based & Impact of zero-day attacks on SIDS & Ineffective against polymorphic malware & [43] \\ \hline [PERSON] et al. (2020) & Signature-Based & Identified patterns in malware & Struggles with unknown threats & [44] \\ \hline [PERSON] (2000) & Heuristic-Based & Proposed a taxonomy for intrusion detection systems & High false-positive rates & [2] \\ \hline [PERSON] et al. (2019) & Heuristic-Based & Detects unknown malware using heuristics & High false-positive rates & [45] \\ \hline [PERSON] and [PERSON] (2019) & Heuristic-Based & Secure cloud computing using lightweight cryptography & Limited to specific use cases & [46] \\ \hline [PERSON] and [PERSON] (2007) & Anomaly-Based & Overview of anomaly detection techniques & Requires extensive training data & [3] \\ \hline [PERSON] et al. (2018) & Anomaly-Based & Survey of IDS techniques and challenges & High false-positive rates & [34] \\ \hline [PERSON] et al. (2014) & Anomaly-Based & Survey of IDS in wireless sensor networks & Resource constraints & [36] \\ \hline [PERSON] et al. (2012) & Anomaly-Based & Profiles abnormal behavior to detect zero-day attacks & High false-positive rates & [47] \\ \hline [PERSON] et al. (2014) & NIDS/HIDS & Comparison of intrusion detection systems & Limited ability to inspect high bandwidth data & [48] \\ \hline [PERSON] and [PERSON] (2014) & NIDS & Host vs. network-based IDS & Limited by network data volume & [49] \\ \hline [PERSON] et al. (2016) & Anomaly-Based & Analysis of intrusion detection systems in cloud computing environment & High false-positive rates & [50] \\ \hline [PERSON] et al. (2021) & Penetration Testing & Empirical study on vulnerability assessment & Requires extensive manual effort & [51] \\ \hline [PERSON] et al. (2018) & Fuzzing & Survey on fuzzing techniques & Complex defects difficult to analyze & [41] \\ \hline [PERSON] et al. (2023) & ML-Based & Examined ML methodologies for zero-day detection & Limited availability of labeled data & [37] \\ \hline [PERSON] and [PERSON] (2016) & ML-Based & Survey on ML for cybersecurity & Limited by dataset size & [52] \\ \hline [PERSON] et al. (2021) & DL-Based & SVM on MobileNetv2 for malware classification & Requires diverse and extensive datasets & [38] \\ \hline [PERSON] et al. (2023) & DL-Based & GANs for synthetic data generation & Ensuring quality and representativeness of data & [39] \\ \hline [PERSON] et al. (2023) & DL-Based & Deep learning for intrusion detection detection & Computationally intensive & [53] \\ \hline [PERSON] et al. (2021) & Anomaly-Based & Advanced anomaly detection using AI & Requires high computational power & [54] \\ \hline [PERSON] et al. (2019) & Model-Based & A model-based security testing framework & Limited scalability & [55] \\ \hline [PERSON] et al. (2022) & Cryptography-Based & Hierarchical attribute-based encryption for cloud security & High computational cost & [56] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of related studies. equipped with the necessary tools and software, as detailed in Table 2. This controlled environment allows us to dynamically analyze the plugins in real-world conditions, consistent with DAST's focus on runtime testing. Dummy web pages are created using the plugins listed in Table 3, and each plugin undergoes individual testing for XSS vulnerabilities. In line with DAST principles, which involve examining a running application's behavior, varied configuration settings are examined to assess XSS susceptibility.