A 2023 study on bot attacks shows that businesses lose around 4.3 percent of their annual online revenues because of bot attacks. This translates to around $85.6 million in yearly losses, which is significantly higher than the $33.3 million recorded in 2020. The study also notes that the losses from bots are greater than the average ransom paid to ransomware perpetrators and penalties due to GDPR violations.
Bot attacks are a serious problem but, to be clear, not all bots are bad. Some of them are designed to perform helpful tasks like those used by search engines, social networks, and information aggregators. Dealing with them is like regulating traffic, wherein it is crucial to have an effective way to distinguish the good from the bad to allow the former and block the latter.
Dealing With The Unavoidable
Bots are everywhere, and they appear in different forms – from the famous chatbots like ChatGPT to the web crawlers, botnets, shopping bots, scrapers, and botnets. Anyone who uses computers and the internet likely has encountered them. Businesses with online operations regularly encounter bots, consciously or unwittingly.
Unfortunately, most of the unwitting encounters with bots tend to be associated with threats. These are malicious bots that inflict damage on businesses and their customers. They attack in cunningly ingenious ways, with the potential victims finding it extremely hard to avoid them.
This is why effective bot management is a must. There has to be a way to whitelist useful bots while blacklisting the unwanted or malicious ones. Also, it may be necessary to track bot sources to address the threat at the source.
Generally, companies take the initiative to address the threat from bots. They do this not only to secure their IT assets and business operations but also to mitigate the negative impact of bot attacks on customer experiences. The disruption and inconveniences brought about by DDoS botnets, for example, turn customers away. Worse, cases of fraud aided by bots imperil customer trust or bring about reputational damage.
The Faces of Bad Bots
Bots that are regarded as threats come in different forms. It is a challenge to detect and block them because they are usually disguised with normal or harmless functions. Most of them operate on websites or web apps as the following.
Malicious data collectors – There are useful bots for data collection such as news feed aggregators, but there are also those aimed at stealing information. Web scrapers, for one, are programmed to find valuable data that can be used for criminal ends. Some bots can also scan entire websites and copy them to quickly generate fake sites used in scams, phishing, and other schemes.
DDoS botnet – Distributed denial of service attack perpetrators propagate massive networks of bots referred to as botnets that reside discreetly in various infected devices. These bots can then be instructed to concertedly make malicious requests to sites or apps to exhaust their resources and force them into downtime.
Credential stuffers – Brute force attacks on accounts can be automated with bots that persistently conduct credential stuffing until they manage to take over accounts not secured with multi-factor authentication. Some credential stuffers automate the process of using large amounts of stolen login credentials.
E-commerce attackers – Unscrupulous online business operators may resort to using bots against their competitors. They can deploy bots to perform scalping, exhaust their competitors’ inventories, or overwhelm ordering lines to deprive a store of real customers. Additionally, bots may be used to manipulate the ad impressions of a company, rendering their online advertising campaigns fruitless.
Social media manipulators – Bots have been used to control public opinion by spreading fake news or misinformation and manipulating social media metrics through fake engagement like padded likes and shares, fake followers, and incessant auto-generated comments.
Online fraudsters – Bots are also notably prevalent in consumer fraud cases. They are used to automate phishing attacks and collect personal information to enable identity theft. Additionally, they are frequently used in payment card fraud, particularly in testing large numbers of stolen credit card details to check card validity.
Bad bots are undeniably real and there have been several high-profile cases that demonstrate their potency and adverse impact. The Dyn DDoS and Mirai Botnet attacks in 2016, for example, resulted in significant business losses. Bots have also been notoriously spreading misinformation on Twitter since 2017. Also, the 3ve ad fraud operation in 2018 showed the evil ingenuity of cybercriminals even several years back. They have only become more sophisticated and aggressive as the years go by.
Ensuring Effective Bot Management
Bot management systems make use of different technologies and strategies to catch malicious bots. Some of the commonly employed technologies include web application firewalls, user behavior analysis, and machine learning. Threat identity and bot pattern databases also play a role in the detection and identification phase.
There is no single do-it-all solution for the bot problem. Usually, organisations utilise a combination of different technologies and strategies. The most effective bot management solutions typically integrate static, challenge-based, and behavioral approaches. They address the problem holistically by bringing together multiple solutions that counter the different attacks or vulnerabilities being exploited by bots.
The static approach relies on information gathered about threats to detect and prevent them. It is a passive strategy that only works on known or already identified threats. However, it is still an important approach in dealing with bad bots.
Meanwhile, the challenge-based approach uses tests to determine if an activity is human or bot-generated. The most common method to do this is with CAPTCHA verification or reCAPTCHA, which is a free service from Google. There are also other methods like puzzles and math questions.
On the other hand, the behavioral approach entails the evaluation of activities to observe patterns that may indicate anomalous actions. This usually involves machine learning and loads of data, especially those related to actual users.
It is not easy to find the best bot management solution. However, it is advisable to take into account the crucial features that embody a good balance of static, challenge-based, and behavioral approaches in bot management. These include DDoS protection, web application firewalls for cloud services and gateways, user and entity behavior analysis, and runtime application self-protection (RASP).
Bot management functions, however, may be part of a bigger cybersecurity platform. They may not be packaged as a standalone solution. Organisations that are looking for a good bot management solution may already have it integrated into their broader cybersecurity system. They just need to make sure that they take full advantage of the available functions and add bespoke mechanisms, like reCAPTCHA for customer interaction apps, if necessary.
It is estimated that around 47 percent of all internet traffic is attributable to bots. They are everywhere, inescapable as it may seem. Completely blocking them is not an option given how there are also various bots used to aid business operations. Hence, the effective management of bots is a must. It is reassuring to know, though, that there are many existing solutions in dealing with the problem of bad bots and organisations can also come up with custom solutions using readily available technologies.
