In 2024, automated internet traffic surpassed human activity for the first time in a decade. According to the 2025 Imperva Bad Bot Report, bots now account for 51% of all web traffic and malicious "bad bots" make up 37% of that total, up from 32% in 2023, marking six consecutive years of growth.

This shift changes how organizations must think about online risk. When a brand faces a sudden surge in comments, mentions, or traffic, there is a growing probability that a portion of that activity isn't human at all.

Bot network attacks are no longer fringe cybersecurity incidents. They are now a primary force shaping online narratives, distorting data, and influencing reputation at scale.

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What a Bot Network Attack Actually Looks Like

Modern bot attacks are rarely obvious. Gone are the days of easily identifiable spam floods. Today's bot networks are coordinated, adaptive, and often indistinguishable from real users.

They typically manifest in several ways: coordinated harassment campaigns that flood social media replies; disinformation amplification that creates the illusion of consensus; distributed denial-of-service (DDoS) attacks that overwhelm infrastructure; credential stuffing and account takeover attempts; and click fraud that distorts marketing performance.

The scale of these networks can be staggering. On March 20, 2026, German, U.S., and Canadian cybercrime authorities announced the dismantling of two of the world's largest botnets, Aisuru and Kimwolf. Aisuru consisted of several million compromised devices, including routers and webcams. Kimwolf, a related network, involved several million infected Android TV boxes. Both were responsible for record-breaking distributed denial-of-service attacks, according to the U.S. Department of Justice. Infected devices were rented out to other criminals, who then used them to extort victims, some of whom suffered losses of tens of thousands of dollars per incident.

These attacks have become more difficult to detect because they are powered by AI. The 2025 Imperva Bad Bot Report found that advanced bots use residential proxies to route malicious traffic through legitimate-looking IP addresses, making them far harder to identify. APIs have become a primary target, accounting for 44% of advanced bot attacks — a figure that underscores how deeply embedded these threats are in modern digital infrastructure.

The implication is clear: bot networks are no longer just noise. They are engineered systems designed to influence, disrupt, and exploit.

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Why Bot Attacks Are Accelerating

The escalation of bot-driven attacks is not accidental. It is structural.

The biggest driver is artificial intelligence. Generative AI tools have lowered the barrier to entry, allowing what even low-skilled actors to deploy bot networks at scale. The 2025 Imperva Bad Bot Report notes that AI is allowing "less sophisticated actors to launch a higher volume of bot attacks with increased frequency." 

Critically, these systems are no longer static. Attackers use AI to analyze failed attempts and refine evasion techniques in real time, according to the same Imperva report. This marks a shift from traditional automation to adaptive adversarial systems.

Bot creation has also been commoditized. Entire ecosystems now exist where botnets can be rented or deployed as a service with what the industry calls Bots-as-a-Service (BaaS) enabling coordinated campaigns at unprecedented scale.

The Aisuru and Kimwolf takedown illustrates this model directly: the operators didn't run attacks themselves. They sold access to their networks of compromised devices to other criminals, functioning as a criminal infrastructure provider.

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The Real Business Impact

For executives, the implications extend far beyond cybersecurity.

First, there is the financial cost. Ad fraud alone — a subset of bot-driven fraud — cost businesses an estimated $84 billion globally in 2023 and is projected to reach $172 billion by 2028. Broadening the scope to include account takeover, scraping, and API abuse, global losses from bot attacks exceed $100 billion annually. In the Aisuru and Kimwolf cases, individual victims reported losses of tens of thousands of dollars from extortion alone and that figure does not account for infrastructure damage, downtime, or reputational fallout

Second, there is the issue of data integrity. Bots skew analytics, inflate engagement metrics, and distort customer insights. Organizations relying on corrupted data to make decisions face a risk that is harder to quantify than direct fraud losses, but often more damaging over time.

Third,  and perhaps most underappreciated, is reputational risk.

Bot networks can manufacture outrage, simulate public sentiment, and trigger media narratives. A coordinated attack can make a fringe issue appear mainstream, influencing journalists, stakeholders, and even investors. In this context, bot attacks are not just technical incidents. They are reputation events.

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