On July 24th, cybersecurity firm NETSCOUT announced it had doubled its global Arbor Cloud traffic scrubbing capacity to 33 Tbps. This move comes in response to recent massive traffic surges caused by giant botnets like Aisuru—networks comprising hundreds of thousands of IoT and smart devices that can easily generate Tbps-scale traffic tsunamis. Faced with such magnitudes, many newcomers to network security and operations begin to worry: In the face of attacks reaching tens of Tbps, does the high-defense server deployed by enterprises still offer practical defensive value?

Judging solely by attack peak data can easily lead to misjudgment. Recent attack data shows that while traffic surges are alarming, what actually causes most small and medium-sized business systems to collapse instantly is often not the traffic overwhelming the backbone network, but precise consumption targeting backend business logic. This article compiles several core questions most frequently puzzling junior operations staff, presented in FAQ format to help technical teams understand the new forms of DDoS attacks and the corresponding response strategies.

Traffic attacks have surged to tens of Tbps—Is renting a high-defense server still useful for enterprises?

The key to answering this question lies in clarifying the boundary between traffic scrubbing and business hosting. When botnets like Aisuru launch massive traffic attacks on the backbone network, the server's own NIC and access bandwidth alone cannot directly absorb them. However, the protection logic of modern high-defense servers does not rely on a single machine to withstand all traffic; instead, it uses upstream distributed scrubbing centers to identify and strip malicious traffic at edge nodes.

Recent security reports indicate that the Aisuru botnet now accounts for approximately 33% of global DDoS attack traffic. The essence of such ultra-large traffic is the flooding of meaningless garbage packets, and the role of protective infrastructure is precisely to filter out these Tbps-level dirty traffic before they enter the data center, only allowing cleaned normal business requests to be forwarded to the origin. High-defense solutions like those from rockcloud, with abundant nodes, use front-end traffic scrubbing gateways paired with high-defense servers, enabling the data center to maintain stable operation of the origin server even under massive traffic bombardment.

Why does the backend database and API interface become paralyzed even before bandwidth is fully saturated?

In many newcomers' understanding, DDoS attacks equal saturating bandwidth. However, an application-layer DDoS attack analysis released on July 22nd pointed out that over the past two years, Layer 7 attacks have grown by more than 104%, and attacks targeting API interfaces have surged by 113%.

The essence of this change is a shift in attacker strategy: instead of consuming massive resources to flood Layer 3/4, they use micro-botnets to send legitimate HTTP/HTTPS requests. Attackers deliberately target business endpoints with high computing consumption, such as:

• Global search and complex filtering interfaces on websites
• User login and authentication processes
• Backend PDF report and file export generation interfaces
• Dynamic API responses involving frequent database reads and writes

Because these requests fully comply with normal HTTP protocol formats, basic traffic scrubbing devices can hardly intercept them based solely on packet header characteristics. Even if access bandwidth usage is less than 10%, the backend server's CPU and database connection pool can be exhausted instantly. This explains why there is no traffic alert, yet the business system can no longer respond to normal users.

Facing AI-assisted composite attacks, how should the scrubbing strategy of high-defense servers be adjusted?

The proliferation of AI technology has significantly lowered the barrier for attackers. Current automated tools can not only automatically probe a website's defenses but also adjust request frequency and payload patterns in real-time based on the protection system's response.

If the protection strategy remains limited to simple IP rate limiting or static rules, it is easy to mistakenly block normal users or miss malicious requests. When adjusting protection configurations, operations teams should pay attention to the integration of the following three levels:

• Dynamic behavior analysis: Determine whether requests come from real browsers based on user behavior patterns, rather than simple IP counting
• Interface-level rate limiting: Set fine-grained rate limits independently for APIs that consume computing power, preventing single points from being overwhelmed
• Cache front-end strategy: Staticize non-sensitive dynamic data at edge nodes as much as possible to reduce origin requests

When building the overall architecture, you can leverage the multi-layer scrubbing system provided by rockcloud to perform preliminary filtering of abnormal protocols and high-frequency attacks at the entry point, and then combine with the anti-CC strategy on the origin server to form a collaborative defense.

What are the most common pitfalls for junior operations teams in defense deployment?

For newcomers to security operations, the most common mistake when configuring high-defense products is not choosing the wrong hardware, but mistakenly believing that buying high-defense is a one-time fix. Common deployment blind spots include the following:

First, real IP exposure of the origin server. Although many teams have connected to protection nodes, historical domain resolution records, mail server (SMTP) configurations, or subdomains still expose the real address of the origin server. Attackers can bypass the scrubbing node and directly attack the origin server IP, rendering the protection useless.

Second, using default configurations across the board. Traffic patterns vary greatly across different businesses; the high-concurrency reads of a news site and the frequent write operations of an e-commerce system differ significantly in request patterns. Using the generic template of the protection system often fails to defend against customized Layer 7 attacks.

Finally, a lack of continuous configuration validation and stress testing. Many teams only adjust rules temporarily after suffering an attack, lacking an objective understanding of the business interface's capacity limits. Regularly conducting simulated tests on critical APIs and establishing a clear protection baseline will enable a quick response when an attack occurs.