How to Prevent Botnet Attacks & Detect Them Early

Somewhere right now, a home router, a security camera, or a cheap smart TV is being used to attack a website, and its owner has absolutely no idea. 

That’s how botnets work: millions of compromised devices, executing commands from someone who doesn’t own any of them.

Botnets power some of the most damaging attacks organizations face: DDoS floods, credential stuffing, payment fraud, and spam campaigns at scale. One well-armed fleet can take a site down or drain customer accounts in minutes. 

The good news is that botnet attacks are preventable if you know what to look for and act before the attack lands.

This guide covers how to detect botnet activity, close the infection vectors attackers rely on, and stop botnet traffic before it reaches your application. 

Key takeaways

• A botnet attack uses a network of malware-infected devices, controlled remotely, to run coordinated attacks at scale
• Botnet attack types include DDoS, credential stuffing, click fraud, spam, crypto-mining, and data theft, each with a different business cost
• Detection relies on traffic anomalies and device signals that legitimate users don’t produce
• Prevention is layered: patch devices, secure IoT hardware, segment your network, apply rate limiting, and continuous monitoring

What is a botnet attack?

A botnet attack is a coordinated, malicious action carried out by a network of malware-infected devices under remote control. The network is the botnet. The attack is what it does.

Three actors make botnet attacks work:

• Bot herder: the threat actor who controls the botnet
• C2 (command and control) server: the infrastructure that sends instructions to infected devices
• Zombie devices: the compromised hardware (laptops, servers, smartphones, IoT cameras) that execute the commands

Bot and botnet are often used interchangeably, but they’re not the same thing. A bot is software. A botnet is a fleet of hardware—infected devices that collectively carry out attacks at scale.

The infection itself isn’t the attack. A device recruited into a botnet can sit dormant for months. The attack happens when the bot herder activates the network: flooding a server, running credential stuffing campaigns, or generating fraudulent ad clicks.

How do botnets work?

Botnets follow a three-stage lifecycle: infect, connect, execute.

Stage 1: Recruitment

The bot herder spreads malware via phishing emails, drive-by downloads, unpatched software vulnerabilities, or weak IoT credentials. Once a device is infected, it’s recruited into the botnet. The device owner rarely knows it happened.

Stage 2: C2 communication

Infected devices connect to the C2 server to await instructions. In older centralized models, all traffic routes through a single server, which are easier to take down and easier to trace. 

Modern botnets use peer-to-peer (P2P) C2 structures, where each device can relay commands to others. There’s no single point of failure for law enforcement or defenders to target.

Stage 3: Command execution

The bot herder sends a command, and every zombie device acts simultaneously. That coordinated scale is what makes botnets effective for DDoS and large-scale fraud.

With botnets-for-hire, the barrier to launching a major attack has dropped to almost nothing. Threat actors can now rent access to an existing botnet—sometimes called a DDoS booter or botnet booter—without building one themselves. 

What are the main types of botnet attacks?

Most botnet attacks fall into six categories, each with a different business impact.

DDoS (distributed denial of service)

The botnet floods a target—server, website, or API—with more traffic than it can handle. The service goes down for legitimate users. For e-commerce sites, downtime during peak periods can mean thousands of dollars lost per minute. 

Learn more about DDoS protection and Layer 7 DDoS protection.

Spam and phishing distribution

Compromised devices send billions of spam emails, usually to spread more malware, harvest credentials, or run phishing scams. Some botnets send tens of billions of messages per day.

Credential stuffing and account takeover

Stolen username and password pairs are tested against login pages at high volume. Botnets automate the guessing. Even a 1–2% success rate across millions of credentials translates into thousands of compromised accounts. 

For e-commerce and financial services teams, the cost is direct: fraud losses, customer churn, and the long-term trust damage that follows. 

See our guides on credential stuffing and preventing account takeover attacks.

Crypto-mining

Infected devices donate their processing power to mine cryptocurrency for the attacker. Victims see higher electricity bills and degraded device performance. The attacker collects the revenue without investing in hardware.

Click fraud

Botnets generate fake ad clicks or impressions, draining advertiser budgets. The traffic looks real in analytics, but it isn’t.

Data theft

Some botnets are purpose-built to extract sensitive information like banking credentials, credit card numbers, or session tokens. For e-commerce teams, this is directly tied to carding and card cracking protection.

How do you detect a botnet infection?

Catch a botnet early by watching for traffic anomalies and device behaviors that legitimate users don’t produce.

Device-side signals

If one of your own devices has been recruited into a botnet, you’ll typically see:

• Unexplained CPU or memory spikes, even when the device is idle
• Unknown outbound connections to unfamiliar IPs or domains
• Persistent slowdowns with no obvious cause
• Processes running in the background that shouldn’t be there

Anti-malware tools that do both static and dynamic analysis help here. Static scans check for known malware signatures and links to known C2 servers. Dynamic analysis watches for IRC traffic on unusual ports, simultaneous identical DNS requests, and unexpected SMTP activity—all signals of botnet participation.

Network and web-side signals

If your site or API is being targeted by a botnet, watch for:

• Traffic spikes that don’t correlate with any campaign or product event
• Unusual geographic patterns, like high volume from regions you don’t serve
• Repeated failed login attempts across many accounts in a short time window (a textbook signal of credential stuffing)
• Sessions with zero mouse movement, zero scroll events, or interaction timing that no human could produce
• Scripted navigation following the same path, repeatedly, at identical intervals

The challenge is that modern bots adapt. A WAF running on signatures catches known threats but misses adaptive bots that rotate IPs, spoof fingerprints, and mimic human behavior. By the time signature-based tools flag something, the damage may already be done.

Real-time, intent-based bot detection closes that gap, classifying every request not based on what a bot looks like on a blocklist, but on how it behaves. That’s what catches the ones that signatures miss.

How to prevent botnet attacks: 7 strategies

Prevention is layered. Close the infection vectors, then block botnet traffic before it reaches your application.

1. Patch and update every device

Most botnet infections start with an unpatched vulnerability. Smominru spread by exploiting EternalBlue—a vulnerability Microsoft had patched, but millions of devices had never applied the fix. Regular patching across operating systems, applications, and firmware closes the doors malware needs to get in.

Set up automatic updates where possible. For endpoints that can’t auto-patch, maintain a schedule and stick to it.

2. Secure IoT devices and change default credentials

IoT is the largest botnet recruitment pool. Cameras, routers, smart sensors, industrial controllers all ship with weak or identical default credentials, and most never get changed.

For any IoT device on your network:

• Change default usernames and passwords immediately on deployment
• Disable remote access features you don’t use
• Keep firmware updated
• Audit your device inventory regularly

3. Segment networks and filter outbound traffic

Even if a device gets infected, network segmentation limits the damage. If zombie devices can’t reach the C2 server, they can’t receive commands or participate in an attack.

Segment your network so that IoT devices, employee workstations, and servers operate in separate zones. Apply firewall rules that block unexpected outbound connections, particularly to unusual IPs or on non-standard ports. Many botnet C2 callbacks follow recognizable patterns once you know what to watch for.

4. Protect email and endpoints

Most device infections still start with a human click, such as a phishing email, a malicious attachment, or a fake software download. Email security filters and endpoint detection tools interrupt the delivery chain before malware lands on a device.

Look for tools that catch Trojan-type malware, which disguises itself as legitimate files. This is how the majority of passive botnet recruitment works, and why this layer matters even if you have strong perimeter defenses.

5. Apply rate limiting and a WAF on web apps and APIs

Rate limiting throttles high-volume automated traffic before it overwhelms your infrastructure. A WAF adds signature-based filtering at the edge.

That said, a WAF alone won’t stop sophisticated botnet traffic. WAFs operate on known patterns. Botnets adapt. For bot mitigation at scale, behavioral detection needs to work alongside your WAF, not replace it. They solve different problems.

6. Monitor traffic and set alerts for anomalies

You can’t stop what you can’t see. Continuous traffic monitoring across your web apps, APIs, and network gives you the baseline needed to spot anomalies before they become incidents.

Set alerts for:

• Sudden spikes in traffic to login pages, pricing pages, or checkout flows
• Geographic shifts in your traffic mix
• Spikes in failed authentication attempts
• Unusual crawl patterns on pages bots shouldn’t be targeting

Logs are useful but reactive. By the time you’re reading them, the attack has often already run. The goal is detection at the edge, in real time.

7. Train users against phishing

Most botnet infections still trace back to a human clicking something they shouldn’t. Regular phishing awareness training, simulated phishing exercises, and clear reporting procedures reduce that risk meaningfully. 

It’s not the most technically interesting control, but it’s often where the infection chain starts, and where it’s cheapest to break.

How do organizations stop botnet attacks at scale?

Manual rules and static defenses can’t keep pace with botnets that rotate IPs, adapt their fingerprints, and launch low-and-slow attacks across millions of unique addresses.

Defense in depth at the organizational level means combining device hardening, network segmentation, and a real-time detection layer that sits in front of your web traffic. The detection layer is where scale matters most.

Per-rule maintenance fails against evolving botnets. The moment you write a rule for a specific IP range or User-Agent pattern, a well-run botnet has already rotated past it. What works instead is a system that classifies every request based on intent—not just whether it matches a known bad pattern, but whether it behaves like a human or a machine executing a script.

That’s the difference between signature-based anti-bot solutions and intent-based bot management: one chases the bot after the pattern is identified. The other classifies in real time, before damage occurs.

Protect your business from botnet attacks with DataDome 

Botnet prevention comes down to a layered checklist: patch every device, change default credentials on IoT hardware, segment your network, filter outbound traffic, protect email, apply rate limiting, monitor continuously, and train your team against phishing. 

None of these steps alone is sufficient. Together, they make botnet recruitment and execution significantly harder.

DataDome’s 2025 Global Bot Security Report tested nearly 17,000 websites and found that only 2.8% were fully protected against simple bot attacks. 

The gap between the sophistication of modern botnets and the defenses most organizations have in place is real, and it’s widening.

Botnets are cheaper to rent, harder to spot, and increasingly powered by AI that mimics human behavior convincingly enough to evade signature-based tools. Peer-to-peer C2 structures make takedowns less effective. And as DataDome’s threat research into the Kimwolf botnet shows, residential proxy networks mean individual IPs often look clean—even when the traffic behind them is entirely fraudulent.

Real-time detection isn’t an advanced security feature anymore. It’s the baseline.

DataDome stops 20,000+ attacks every second by classifying every request based on intent in under 2 milliseconds. That’s what stopped a 2.45 billion-request DDoS campaign that spanned 1.2 million unique IPs across 16,000+ autonomous systems—an attack where no single IP ever tripped a rate limit. 

Test your website’s defenses against botnet attacks with our free Vulnerability Scan, or book a demo to see DataDome’s protection in action.