When botnets industrialize denial of service
DDoS (Distributed Denial of Service) attacks remain one of the major threats on the Internet in 2025. While most companies believe they can protect themselves with traditional solutions, the reality is more complex: today, more than 70% of HTTP DDoS attacks are orchestrated by known botnets.
This industrialization of attacks makes the threat more frequent, more powerful, and above all, more difficult to anticipate.
Botnets and HTTP DDoS attacks:
understanding, anticipating, and protecting yourself
Understanding HTTP DDoS attacks
HTTP DDoS attacks target the application layer (Layer 7) of a website or web application, which is where user interactions occur—such as loading a page, submitting a form, or processing a payment.
The role of botnets in DDoS attacks
A botnet is a network of infected devices (PCs, routers, connected objects, IP cameras, DVRs, etc.) controlled remotely by cybercriminals.
How can you protect yourself from HTTP DDoS attacks?
Implement systems capable of analyzing request behavior to distinguish normal traffic from malicious traffic.
Understanding HTTP DDoS attacks
HTTP DDoS attacks target the application layer (Layer 7) of a website or web application, which is where user interactions occur—such as loading a page, submitting a form, or processing a payment. Unlike network-level DDoS attacks (Layer 3/4), which flood servers with traffic to saturate the bandwidth or disrupt basic connectivity, HTTP DDoS attacks focus on overloading the server’s capacity to handle legitimate application requests.
These attacks aim to:
Send a massive number of HTTP or HTTPS requests to a website, consuming server-side resources such as CPU, RAM, disk I/O, and thread pools, eventually leading to slowdowns or complete outages.
Disrupt backend systems by overwhelming application servers, APIs, or databases, often through repetitive or computationally expensive requests (e.g., search queries, login attempts, or cart updates), pushing the infrastructure beyond its operational limits.
Degrade the user experience by significantly increasing page load times, causing timeouts, or rendering online services inaccessible. This can directly lead to lost revenue, customer frustration, and damage to brand reputation.
In some cases, attackers craft requests that mimic legitimate user behavior, making these attacks harder to detect and mitigate. Sophisticated HTTP DDoS assaults may exploit specific application features or endpoints, causing disproportionate load with minimal traffic volume—a technique known as low and slow DDoS.
Because Layer 7 attacks operate at the same level as genuine user interactions, they are particularly challenging to filter without impacting legitimate traffic, requiring advanced mitigation strategies like behavioral analysis, traffic profiling, and machine learning-based anomaly detection.
The role of botnets in DDoS attacks
A botnet is a network of infected devices (PCs, routers, connected objects, IP cameras, DVRs, etc.) controlled remotely by cybercriminals.
In 2025, these zombie networks will account for the majority of HTTP DDoS attack sources:
Why are botnets so effective?
Massive firepower: Each bot generates requests, multiplied by thousands or even millions of devices.
Multiplication of attack points: Requests come from a variety of IP addresses, making filtering complex.
Ease of access for cybercriminals: Entire botnets are sold or rented on the dark web.
Examples of recent botnets used in HTTP DDoS attacks
Mirai and its variants: Still active, this malware mainly targets poorly protected connected devices.
Meris and Mantis: Designed specifically for volumetric HTTP attacks, with encrypted HTTPS requests.
How can you protect yourself from HTTP DDoS attacks?
1. Behavioral detection
Implement systems capable of analyzing request behavior to distinguish normal traffic from malicious traffic.
2. Use a CDN with built-in DDoS protection
Content Delivery Networks often have application firewalls (WAF) and anti-DDoS protections capable of absorbing this type of traffic.
3. Dynamic IP filtering
Block IP addresses identified as sources of attacks, while taking into account the rapid rotation of IPs used by botnets.
4. Continuous monitoring
Real-time monitoring is essential for detecting the weak signals of an attack in preparation.