A Thirty-Day Dataset of Malicious HTTP Requests Blocked by OWASP ModSecurity on a Production Web Server

We present a real-world dataset capturing thirty consecutive days of malicious HTTP traffic filtered and blocked by the OWASP ModSecurity Web Application Firewall (WAF) on a live production server. Each entry corresponds to a request that triggered one or more rules in the OWASP Core Rule Set (CRS), resulting in its inclusion in the audit log due to suspected exploitation attempts. The dataset includes attack categories such as SQL injection, cross-site scripting (XSS), local file inclusion, scanner probes, and various malformed or evasive input forms. The data has been carefully anonymized to protect sensitive information while preserving critical structural tags, including request method, URI, triggered rule IDs, request headers, and user-agent strings. This dataset provides a real-world resource for cybersecurity researchers, particularly those developing or evaluating intrusion detection systems (IDSs), WAF rule tuning strategies, anomaly detection algorithms, and adversarial machine learning models. The dataset also allows performance testing of threat prevention pipelines. By making this dataset publicly available, we aim to support reproducible research in web security, encourage benchmarking of detection techniques under real-world conditions, and contribute insight into the nature of contemporary web-based threats observed in an uncontrolled environment.

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Publication Details

Journal
Data
Published
2025-11-11
DOI
https://doi.org/10.3390/data10110186
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

A Thirty-Day Dataset of Malicious HTTP Requests Blocked by OWASP ModSecurity on a Production Web Server

Bertalan Forstner, Geza Lucz
Data
Network Security and Intrusion Detection
article

A Thirty-Day Dataset of Malicious HTTP Requests Blocked by OWASP ModSecurity on a Production Web Server

Bertalan Forstner, Geza Lucz
article en

Abstract

We present a real-world dataset capturing thirty consecutive days of malicious HTTP traffic filtered and blocked by the OWASP ModSecurity Web Application Firewall (WAF) on a live production server. Each entry corresponds to a request that triggered one or more rules in the OWASP Core Rule Set (CRS), resulting in its inclusion in the audit log due to suspected exploitation attempts. The dataset includes attack categories such as SQL injection, cross-site scripting (XSS), local file inclusion, scanner probes, and various malformed or evasive input forms. The data has been carefully anonymized to protect sensitive information while preserving critical structural tags, including request method, URI, triggered rule IDs, request headers, and user-agent strings. This dataset provides a real-world resource for cybersecurity researchers, particularly those developing or evaluating intrusion detection systems (IDSs), WAF rule tuning strategies, anomaly detection algorithms, and adversarial machine learning models. The dataset also allows performance testing of threat prevention pipelines. By making this dataset publicly available, we aim to support reproducible research in web security, encourage benchmarking of detection techniques under real-world conditions, and contribute insight into the nature of contemporary web-based threats observed in an uncontrolled environment.

DataVol. 10(11)
Budapest University of Technology and Economics (HU)
Openalex Percentile: Top 61%
Network Security and Intrusion Detection
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