In today's cybersecurity landscape, organizations are witnessing a significant surge in application-layer (Layer 7) attacks (HTTP DDoS Attacks on API-Based Applications: A Growing Threat). According to recent reports, HTTP DDoS attacks at the application layer increased by 93% year-over-year. Some of these attacks exploit zero-day vulnerabilities, the majority target known vulnerabilities. A report by CISA and NSA highlighted that 11 of the top 15 exploited vulnerabilities in 2023 were initially exploited as zero-days (reference).
This trend underscores the importance for organizations to efficiently manage the detection of known attacks without overwhelming system resources. Signature-based detection, which involves matching incoming traffic against thousands of predefined attack signatures, can be resource-intensive. Implementing signature categorization plays a pivotal role in optimizing detection processes, and ensuring robust security while maintaining optimal system performance.
How Signature Categorization Affects Performance and Security
1. Prioritizing Security Threats
Signature categorization helps to prioritize security threats based on their attack severity and threat type. Instead of treating all attacks equally, categorizing signatures enables security tools like Radware’s Web Application Firewalls (WAFs) to focus on high-priority threats while handling less critical ones more efficiently.
For example:
- Threat type could include high-severity attacks such as SQL Injection, Remote Code Execution (RCE), or Cross-Site Scripting (XSS). These attacks often have a direct, devastating impact on the security of a system and require immediate attention.
- Lower-priority categories might include attacks that are more likely to result in nuisance or information-gathering, such as IP scanning or reconnaissance attacks.
By categorizing signatures and focusing first on high-priority attacks, organizations can allocate resources to monitor and defend against the most serious threats, while less serious attacks can be processed swiftly with minimal impact on system performance. This ensures that security measures do not unnecessarily degrade system performance when handling low-risk threats.
2. Reducing False Positives and System Load
A common challenge in signature-based detection is the generation of false positives, where benign activities are incorrectly flagged as threats. These false positives can overwhelm security systems, increase response times, and strain resources. Signature categorization helps mitigate this by grouping signatures according to their nature or severity, enabling security systems to more accurately filter out low-risk or known false-positive behaviors. A user can decide which signature attacks should be flagged and which can be ignored.
For example, a signature categorized under attack severity “Low” may be deemed a low-priority threat and processed differently. By fine-tuning the response to specific categories, security systems can minimize unnecessary alerts and reduce the computational overhead associated with processing large volumes of traffic.
To further address false positives, Radware’s signature categorization introduces a Confidence Level score associated with each signature. This score reflects the system's assessment of how likely a signature is to correctly identify malicious behaviors without erroneously flagging legitimate traffic. A signature with a high confidence level indicates strong assurance of accuracy, while a lower confidence level suggests the possibility of benign activities being incorrectly flagged. By utilizing these confidence scores, organizations can filter or adjust detection policies to minimize false positives, ensuring that system performance remains high without compromising security.
3. Optimizing Response Actions Based on Threat Categories
With signature categorization, security tools can be tailored to respond differently based on the category of threat. For instance, high-priority attack categories may trigger immediate blocking or deep analysis, while lower-priority categories might only result in logging or sending alerts without blocking the traffic. This dynamic response approach ensures that the system can efficiently handle a variety of threats without applying unnecessarily intensive measures to less critical attacks.
For example:
- SQL Injection (critical): The security system could immediately block the request or trigger an alarm, as these attacks typically have a high potential for data exfiltration or system compromise.
- Directory Indexing (moderate): The system might log the attempt and conduct further analysis to determine if the behavior is part of a larger attack pattern, without immediately blocking the request unless more suspicious activity is detected.
By categorizing threats and tailoring responses based on their severity and nature, security tools can ensure that critical threats receive appropriate blocking or mitigation, while less critical activities are monitored with lighter-weight actions like logging or alerting. While this response strategy is primarily driven by security considerations, it can also incidentally reduce unnecessary processing overhead, helping maintain system efficiency without compromising threat management.
4. Enhancing Performance with Tailored Detection Rules
Signature categorization also allows security systems to implement customized detection rules for specific types of traffic. For example, in a high-traffic environment where performance is critical, the system might apply less stringent detection rules for certain signature categories (such as low-level information-gathering activities) to avoid slowing down legitimate traffic. Conversely, more stringent checks can be applied to more critical categories like data exfiltration or privilege escalation attacks.
The system allows users to include or exclude categories based on their needs. For example, a user might configure the Server OS filter to 'Windows,' causing the system to automatically ignore signatures unrelated to Windows. This reduces CPU utilization and enables faster processing. Hence reducing the CPU utilization and faster processing. This flexibility reduces the overall load on the system, allowing security tools to maintain high throughput while still being effective at detecting and mitigating serious threats.
Radware’s signature categorization feature allows it to filter signatures in various aspects listed below.
- Threat Types – Ex: Application Misconfiguration, SQL Injection, SSI Injection
- Server OS - Windows, Unix/Linux, macOS, any
- Web Server - Apache, Nginx, Node, Microsoft IIS, any
- Framework - Wordpress, Jenkins, Joomla, Drupal, Magento, Shopify, Wix, Sharepoint
- Language - Python, Perl, PHP, JAVA (JSP), Javascript, ASP, HTML
- Database – mysql, sqlite, mongodb, postgres, mssql, oracle
- Confidence level that a signature will not cause to high false positive - Low/Medium/High
- Attack Severity - Low/Medium/High
- Additional filtering:
- Last Modified - YYYY.MM.DD
- CVE Number - CVE-YYYY-XXXXX
5. Monitoring the Signature patterns and changing/optimizing the configuration
Radware’s Signature categorization provides stats to users on the signatures that were filtered/analysed based on the setting that was set. This allows users to understand the system load and accordingly increase/decrease the signature settings.
For example, if certain attack signatures in the "Brute Force Attacks" category are detected regularly, a security team might pre-emptively tighten authentication policies or apply rate-limiting techniques to reduce the chances of a successful attack, without waiting for the system to be overwhelmed.
In this way, categorization also aids in reducing unnecessary security checks for known and recurring low-risk events, helping to preserve system performance while still addressing emerging threats.
Conclusion: A Balanced Approach to Performance and Security
Signature categorization helps achieve a delicate balance between performance and security by organizing attack signatures into manageable, prioritized groups based on their severity and impact. This allows security systems to allocate resources efficiently, ensuring that critical threats are given the attention they need while minimizing the burden of less severe attacks. By applying tailored detection and response actions to specific threat categories, organizations can optimize both the effectiveness of their security measures and the performance of their infrastructure.
Ultimately, signature categorization provides the framework to ensure that security tools remain responsive, accurate, and efficient, without creating performance bottlenecks or unnecessary overhead. It enables a smarter, more agile defense system that adapts to the evolving threat landscape, without sacrificing system performance or user experience. To learn more about Radware’s Web Application Firewall (WAF) solutions and signature protection features, please visit Radware's Official site.