What is a Botnet?

A botnet is a group of internet-connected devices infected with malware so a single operator can steer them remotely. Each device, often called a bot or zombie computer, may appear to work normally while it follows commands from a command-and-control channel.

How botnets are built and controlled

Infection usually starts with phishing, malicious downloads, exposed services, or unpatched software. Some families spread like worms across local networks. Once the bot client runs, it calls out to a controller and waits for jobs.

Early botnets used centralized servers or IRC channels. Many modern families use layered infrastructure: fast-flux DNS, bulletproof hosting, or peer-to-peer overlays so there is no single switch to flip. Law enforcement and security vendors publish takedown notices and technical briefs when large nets are disrupted; CISA and other national CSIRTs routinely warn about botnet-sized threats to critical services.

Command-and-control channels also evolved toward redundancy. Some families poll social posts, paste sites, or domain generation algorithms so defenders cannot permanently unplug one hostname. For advertisers the practical takeaway is simpler: the same distributed design that helps operators survive takedowns also helps them spray clicks or impressions across many unrelated IP addresses.

Scale is the point. A lone bot is easy to block. Tens or hundreds of thousands of hosts spread across ISPs and countries create noise that hides each individual node. Operators rent or sell access to these networks for spam, DDoS, credential stuffing, and ad-related abuse.

Common tasks assigned to botnets

• Denial of service: Coordinated traffic floods can slow or knock sites offline during sales, launches, or political events.
• Spam and phishing: Many small senders beat reputation filters that would block one large mail source.
• Ad fraud and invalid clicks: Infected PCs and phones can load pages, fire trackers, or click ads so criminals earn publisher or affiliate payouts while advertisers pay for useless activity.
• Proxying and anonymization: Some nets route other criminals’ traffic through victims’ home IPs, which also complicates fraud detection.
• Secondary payloads: Bots can drop ransomware modules, miners, or stealers depending on the campaign.

The Mirai source code leak in 2016 showed how weak default passwords on cameras and routers could fuel massive DDoS networks. That case is a reference point in vendor and government guidance on IoT hardening, not an abstract story.

Consumer routers, DVRs, and cheap gadgets still enlarge the pool of plausible residential IPs that malware can weaponize. When those devices browse or fetch ads, traffic can resemble normal households even though the session is scripted. That overlap is why ad fraud teams stress behavior and device consistency, not IP reputation alone.

Why botnets matter for advertisers

Pay-per-click and pay-per-acquisition models assume humans (or at least genuine commercial intent) sit behind clicks and conversions. Botnets break that assumption at scale. According to ClickPatrol’s 2025 PPC study, non-human activity remains a double-digit problem across many accounts when measured with modern detection.

Macro estimates from Juniper Research put global digital advertising spend lost to fraud at roughly $68 billion in 2022 in their published forecast, with large economies carrying outsized shares of modeled losses (Juniper Research, February 2022). Botnets are one delivery mechanism inside that total, especially where criminals sell clicks or impressions as a service.

CHEQ reported 17.9% invalid traffic in its 2024 State of Fake Traffic analysis, compared with 11.3% the year before across sampled enterprise data (CHEQ, 2024). Distributed bot traffic contributes to invalid buckets when it simulates human journeys at scale.

When botnets drive clicks, you pay the platform, competitors may gain relative impression share, and your algorithms learn from poisoned signals. Smart bidding and lookalike models treat fraudulent engagement as success, which pushes spend toward more of the same bad traffic.

A concrete example: say you pay EUR 11 per click in a software vertical. One thousand bot-driven clicks in a month are EUR 11,000 of media spend that never had a serious evaluation stage. If even a fraction of those clicks convert on a shallow micro goal (newsletter signup on a disposable domain), automated bidding can interpret the segment as efficient and raise bids, compounding the damage.

Affiliate and lead programs face a related risk: scripted form posts from distributed IPs resemble “many users” until you validate phone numbers and downstream sales. That pattern ties to junk leads and wasted sales effort, not just higher CPC.

Publishers can be hurt from the other side. If a site unknowingly attracts botnet-driven visits, advertisers see poor post-click behavior and exclude the domain. Display ad fraud material explains how invalid impressions flow through programmatic pipes.

Detection and mitigation

Enterprise security teams focus on egress monitoring, endpoint detection, patching, and network segmentation. Marketing and growth teams should pair those efforts with traffic quality review on paid and owned properties.

• Network and ASN signals: Sudden surges from hosting providers or known bulletproof ranges warrant review. Residential proxy botnets deliberately blur this line, so ASN alone is not enough.
• Behavior: Impossible session depth, identical timing patterns, or zero scroll with perfect click paths suggest automation. Compare to suspicious behavior definitions used in fraud products.
• Velocity: Many submissions or clicks from disparate IPs within the same second often indicates coordination.
• Outcome checks: If paid clicks do not produce plausible site engagement or pipeline, assume measurement or traffic quality issues before you scale bids.

Read botnet detection and types of bots for wider technical context. How fraud is detected in ClickPatrol’s methodology summary aligns with multi-signal scoring rather than static IP lists.

Platform-level refunds for “invalid clicks” help but rarely cover everything. Advertisers often combine native controls with dedicated filtering so botnet traffic never enters optimization loops. Blocking bot traffic from Google Ads walks through practical steps.

Understanding proxies and VPNs helps analysts interpret geo mismatches. Botnets increasingly tunnel through consumer connections, so geography that once flagged datacenters is now only one input.

For a tour of how these tactics combine with domain abuse and invalid traffic schemes in paid media, read ad fraud techniques in 2025. Pair that with ASN-level reviews when you investigate sudden spikes from unfamiliar networks.

Abisola

Meet Abisola! As the content manager at ClickPatrol, she’s the go-to expert on all things fake traffic. From bot clicks to ad fraud, Abisola knows how to spot, stop, and educate others about the sneaky tactics that inflate numbers but don’t bring real results.

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