[March 2026 Web Attack Trend Analysis]

1. Weekly Web Attack Trend Analysis

By analyzing weekly web attack trends, it is possible to identify specific periods when attacks are most
concentrated. These insights can be used to establish proactive prevention and response strategies in
anticipation of high-risk periods.

The graph below visualizes the number of web attacks detected by AIWAAP on a weekly basis throughout
February 2026.



Based on an analysis of data detected by AIWAAP throughout February 2026, an average of over 300,000
web attacks were identified per day. This is comparable to the previous month, indicating that threats
targeting web servers remain persistent.

In addition, attack frequency was higher on weekends (Saturday and Sunday) than on weekdays, suggesting
a strategic attempt to exploit periods of lower web server activity outside of business hours. Elevated attack
activity was also observed at the beginning and end of the week, particularly on Mondays and Fridays.
Notably, on Friday, February 27, a large number of new attacks were detected following the application of
updated detection patterns as part of a regular pattern update.

In particular, February 27 recorded the highest concentration of web attacks during the entire period.
Among the attack types detected on that day, SQL Injection accounted for the largest share.

SQL Injection is a representative attack method that manipulates databases to gain unauthorized system
access or exfiltrate sensitive information. Attackers commonly use this technique to bypass authentication
mechanisms or to probe database structures. Due to these characteristics, it poses a significant risk to the
protection of sensitive corporate data.

Within AIWAAP, SQL Injection is also classified as a high-risk threat with numerous detection patterns in
place. These findings highlight the need for continuous monitoring and more refined response strategies
for major web attack types, including SQL Injection, and provide a critical basis for establishing future
detection and blocking policies.

2. Web Attack Trends by Attack Type

By analyzing web attack trends by attack type based on detection logs, it is possible to systematically
identify which types of attacks were most prevalent over the course of a month. This analysis goes beyond
simple statistics and serves as a key foundation for establishing security policies and refining an
organization’s response framework.

An analysis of detection logs collected by AIWAAP in February 2026 revealed a wide range of web attack
types. Among them, certain attack types showed clear patterns—either occurring in concentrated periods
or accounting for a significant portion of the total attack volume. In particular, traditional yet still highly
threatening attack types such as SQL Injection and Application Vulnerabilities ranked among the most
frequent, and these are typically executed repeatedly using automated attack tools or botnets.

The chart below visualizes the distribution of web attack types detected by AIWAAP throughout February 2026.



According to statistics on web attack types detected by AIWAAP in February 2026, SQL Injection accounted
for the largest share at 36.94% of total detections. This was followed by App Weakness (14.63%), System
File Access (13.69%), Default Page (8.83%), and Bad User-Agent (8.09%). These findings highlight the
need for more precise 대응 and proactive prevention measures for specific attack types.

SQL Injection, in particular, is one of the most critical threats, consistently ranking among the top in the
OWASP Top 10. Its techniques continue to evolve in increasingly sophisticated ways. This attack typically
occurs when user-supplied input is directly included and executed within SQL queries. Attackers exploit this
to bypass authentication, explore database structures, and exfiltrate sensitive data.

Systems that rely on dynamic queries or lack proper input validation are especially vulnerable to this type of attack.

The second most prevalent category, App Weakness, targets inherent security flaws in applications, such as
insufficient authentication, session management vulnerabilities, and misconfigurations. Notably, there has
been an increase in cases detected as authentication bypass attempts and API abuse, particularly in
cloud-based SaaS systems and API-driven services. This trend may also influence the development of future
cloud security policies.

The third most common category, System File Access (12.55%), refers to attempts by attackers to exploit
web application vulnerabilities to gain unauthorized access to internal system files and directories or to
manipulate arbitrary files. Such attacks may result from server misconfigurations, inadequate access controls,
or failures in directory path validation. If successful, they can lead to privilege escalation or the installation
of backdoors.

The fourth most common category, Default Page (8.83%), targets pages that retain default configurations
after installation or system message pages. These pages may expose information about the system’s
software and configuration during the reconnaissance phase, which can then be leveraged for follow-up
attacks. While generally considered passive, this type of attack is often conducted at scale using automated
scanners, making early detection and response essential.

The fifth most common category, Bad User-Agent (8.09%), involves the use of malicious or abnormal
User-Agent strings to probe systems or mimic automated scanners and crawlers. During the reconnaissance
phase, abnormal User-Agent values can reveal the tools being used by attackers and their intent
(e.g., vulnerability scanning, crawling, scraping), providing clues for subsequent attacks. This type of traffic
often combines evasion techniques, such as impersonating legitimate browsers or using known malicious
strings, with characteristics of large-scale automation. As a result, it should not be considered purely passive,
and early detection and blocking are critical due to the high volume typically generated by automated scanners.

---

The Web Attack Trend Report provides the latest web vulnerability analyses, industry-specific attack patterns,
and key CVE-based vulnerability information, all based on processed data from the AI/ML-powered threat intelligence platform AILabs.

Subscribe to receive the full monthly Web Attack Trend Report!

[ Subscribe → ]