CDN edge nodes are facing security threats, such as CC attacks and API abuse, which are common tactics used by attackers. These two types of attacks not only disrupt website access but can also lead to data leakage and service downtime. Therefore, it is crucial to implement effective security hardening at CDN edge nodes to protect against these attacks.
Preventing CC attacks requires understanding their nature. CC attacks use a large number of requests that simulate normal user behavior to rapidly deplete server resources, causing slow system responses or even system crashes. Compared to traditional DDoS attacks, CC attacks are more targeted and covert. Because their requests appear legitimate, they are difficult to filter directly through traffic scrubbing. Therefore, security strategies for CDN edge nodes should not rely solely on traffic filtering but should also incorporate intelligent identification and behavioral analysis.
One effective strategy is to utilize request rate limiting. By limiting the number of requests from the same IP address or user session per unit time, it can effectively curb abnormal access rates. For example, edge nodes can configure a rule to allow a specific IP address to initiate a maximum of 100 requests per second, automatically rejecting or delaying requests exceeding this limit. This not only reduces the impact of attack traffic on the origin server but also improves overall network response efficiency. During actual configuration, rate limiting policies can be flexibly adjusted based on different access paths and interfaces to ensure smooth business operations.
Second, deploying a captcha mechanism can also effectively defend against CC attacks. By displaying a pop-up image or sliding captcha for frequent visitors, the system verifies the visitor's authenticity and prevents malicious bots from continuously initiating requests. The captcha mechanism should be triggered intelligently to avoid causing excessive inconvenience to legitimate users. In conjunction with a behavioral analysis system, a captcha challenge can be automatically initiated when an IP address or device exhibits abnormal behavior, thereby increasing the operational cost for attackers.
Third, API abuse is another major challenge facing current internet application security. With the prevalence of microservices architectures and open platforms, APIs have become the core of business interactions, but they have also become targets for attack. Attackers may leverage automated tools to maliciously call APIs to steal data or consume resources. To this end, edge nodes must implement strict authentication and access control for API access. Common methods include API key management, OAuth authorization mechanisms, and IP whitelisting. By verifying the legitimacy of the request source, most invalid or malicious calls can be blocked.
Fourth, request behavior monitoring should also be implemented to combat API abuse. Edge nodes should monitor API call frequency, abnormal request patterns, and access parameter anomalies in real time. When anomalies are detected, dynamic blocking, rate limiting, or alerting can be implemented. For example, if a user requests a large number of sensitive interfaces in a short period of time, their access should be immediately restricted and the security team notified for further investigation. This dynamic protection approach is more flexible and efficient than relying solely on static rules.
Fifth, combining log auditing and machine learning technologies to conduct in-depth analysis of edge node access logs is also a key way to improve protection capabilities. By analyzing historical data and building models of normal access behavior, legitimate and abnormal traffic can be more accurately distinguished, enabling precise defense. Furthermore, log auditing can help quickly locate the source of attacks and, in conjunction with source tracing mechanisms, implement targeted blocking. With the advancement of AI technology, more and more CDN vendors are introducing intelligent detection algorithms to continuously improve the automation and accuracy of defenses.
Overall, CDN edge node security reinforcement should be a multi-layered, multi-faceted system. Rate limiting and verification codes serve as the first line of defense, blocking the vast majority of simple and frequent malicious requests. Authentication and access control ensure the security of API calls. Behavior monitoring and dynamic response mechanisms provide flexible and real-time defense adjustments. Log auditing and intelligent analysis improve the accuracy and efficiency of overall defense. Only by effectively combining these strategies can we ensure service stability and business security in complex and volatile network environments.
The following is a simple Nginx rate limit configuration example, which can be applied to CDN edge nodes to limit the request rate of a single IP:
http {
limit_req_zone $binary_remote_addr zone=one:10m rate=10r/s;
server {
location /api/ {
limit_req zone=one burst=20 nodelay;
proxy_pass http://backend_api;
}
}
}
As network attack methods continue to escalate in 2025, CDN edge node security must also evolve. Employing multiple strategies to coordinate resistance is key to defending against CC attacks and API abuse. Develop a comprehensive edge node security plan based on your business characteristics and security requirements to ensure unimpeded user experience and business continuity. Security is never a one-time task; it's a process of continuous optimization and response.
