Bad bots have always been the enemies of the internet, and one the most significant threats for online businesses but, as of 2026, the risks are growing far beyond what we’ve known. While some automated programs are useful (search engine crawlers, for example), others can disrupt operations, damage revenue, and compromise security.
Not all bots are equal: some are genuinely helpful, but distinguishing them requires specific tools and, for digital business to remain on course, harmful bots need to be identified and controlled. Meanwhile, legitimate, human users need a smooth experience.
Recognizing harmful bots
Malicious bots can take many forms and pursue various objectives, with some designed to scrape content, steal intellectual property, or copy pricing information, others aim to execute account takeovers or generate fake accounts. Scalping bots target inventory in e-commerce, buying large quantities of products to resell at higher prices, while Layer 7 DDoS bots can overwhelm servers, causing downtime and financial losses.
Recognizing the patterns of those bots is key; they often mimic human activity with automated mouse movements, randomized clicks, and other evasion techniques to bypass traditional security measures. Analysis of traffic behavior and advanced detection tools are necessary to reliably distinguish them from real users, or the real users will also be caught in the crossfire.
Differentiating between good and bad bots
Search engine crawlers, indexing bots, and other helpful automated agents improve website visibility and facilitate essential functions. The challenge lies in separating these good bots from malicious actors. Blocking helpful bots can harm SEO rankings and reduce discoverability but, at one and the same time, allowing malicious bots to operate unchecked can drain resources and compromise security; this is why effective differentiation requires continuous monitoring and a clear understanding of each bot’s purpose.
Stopping bots that compromise security and reputation
Businesses should prioritize blocking bots that directly threaten security or reputational integrity. Bots that attempt credential stuffing, launch DDoS attacks, or create fraudulent accounts can have long-term consequences. For example, fake accounts can distort analytics, skew advertising metrics, and reduce trust in platforms that rely on user-generated content. Similarly, bots scraping proprietary content undermine the value of intellectual property.
Datadome’s bot management
Datadome emphasizes the importance of bot management in distinguishing between beneficial and harmful automated traffic; the platform allows businesses to automatically detect and mitigate malicious activity while letting legitimate bots continue operating.
Datadome’s bot management system is designed to handle sophisticated threats that mimic human behavior using machine learning techniques – a key feature, since malicious bots often employ nonlinear mouse movements and randomized clicks to evade detection, and scalable attacks can involve hundreds or thousands of simultaneous bot actions. Finding them without the right tools is like trying to catch a fish with a lasso.
By using bot management, companies can protect against account takeover attempts, scraping, DDoS attacks, fake account creation, and inventory scalping. The platform supports real-time feedback loops, which enable the system to adapt to threats and minimize the risk of allowing harmful bots onto a site.
Focusing on bots that affect revenue and user experience
Bots that impact revenue or degrade user experience should be prioritized. In e-commerce, scalping bots can remove high-demand items from shelves before legitimate customers have a chance to purchase them. Bots involved in ad fraud can consume advertising budgets without producing actual conversions. These activities distort performance metrics and make it harder for teams to understand genuine customer behavior.
Even when revenue isn’t directly affected, bots that slow down site performance or create fake accounts reduce trust and credibility. They can increase infrastructure costs, strain customer support, and infringe on legitimate user journeys. Controlling these types of bots preserves financial stability and confidence among users and customers.
Why automation is helpful
As bot activity grows in scale and sophistication, manual- or rule-based approaches aren’t realistic solutions. After all, modern bots adapt quickly, rotate identities, and mimic real user behavior closely enough to bypass static controls even if those static controls seem to be working effectively in the beginning. Trying to manage these threats with individual rules, IP blocklists, and isolated defenses creates gaps for attackers, often at speed and volume that internal teams simply can’t manage.
Rather than relying on single indicators, more advanced bot management solutions analyze traffic holistically, assessing behavior patterns, device signals, and interaction consistency in real time (aka, as the threats evolve). Harmful bots are mitigated instantly; legitimate users and approved automated agents can continue uninterrupted, reducing false positives, which can damage user experience and revenue as much as bot attacks themselves.
Solutions like Datadome’s take that operational burden away from businesses and their tech teams, already stretched thin before we take into account this new threat. Detection models evolve as new attack patterns emerge, removing the need for constant manual tuning, while the visibility into bot activity also helps teams understand where risks are concentrated and how threats are changing each and every day.
