Controlling Bot Traffic: Bot Management Explained
Many, if not most of the cybersecurity threats today are performed by malicious bots. For example, hackers can use bots to perform brute force attacks on websites, execute injection attacks to exploit vulnerabilities, post comment spam, and perform DDoS attacks, among others.
These malicious bots, in turn, can cause various kinds of damages to your network and system, which might also affect your customer’s experience in interacting with your business. In turn, this can lead to long-term damage to your reputation and financial losses.
On the other hand, managing bot traffic poses a unique challenge to cybersecurity due to two main reasons:
- First, is that there are good bots owned by legitimate companies like Google, Microsoft, and others that can be beneficial for your business, so you wouldn’t want to accidentally block their activities
- The second is that today’s malicious bots are getting much more sophisticated in impersonating human users. Differentiating between these malicious bots and human users can be a major challenge.
To tackle these two challenges, a proper bot management practice with an appropriate bot management solution is needed in effectively controlling bot traffic.
What Is Bot Management?
In a nutshell, bot management is a strategy to manage bot activities on a website, network, or system. ‘Manage’ is a key emphasis here, since bot management isn’t always about blocking all bot activities.
Bot management mainly involves three core aspects:
- Detecting and identifying the presence of malicious bot activities.
- Detecting legitimate traffic coming from human users and good bots.
- Allowing legitimate traffic to access the website, while managing traffic from malicious bots
There are various ways we can use to manage/mitigate the malicious bot activities, for example:
- Blocking is obviously a cost-effective and efficient approach but must be performed very carefully due to the above reasons. We have to be 100% sure that it is a malicious bot and that there are no other alternative ways to mitigate this traffic before we block the traffic.
- Feeding false information/content is a common and effective approach. This way, we allow the bot to stay active (and waste its resource) but protect our data and valuable information. We can also redirect the bot into a similar page/app with different content.
- Challenge the bot. The idea in this approach is to give a challenge to the bot to prove that it is a human user. CAPTCHA is the common practice here, but lately, it’s no longer effective due to the presence of various CAPTCHA farm services, allowing attackers to employ human users to solve the CAPTCHA before passing the traffic back to the malicious bot.
- Throttling, limiting the speed of fulfilling the bot’s request to slow down its activities, with the hope that the attacker will give up in its attack.
This is a non-exhaustive list, and there are various other methods and techniques we can use to mitigate the bad bot activities.
How Does Bot Management Solutions Detect Bad Bots?
A key differentiator between a great bad management solution and a bad one is how well it can consistently differentiate between malicious bots and good bots/legitimate human traffic.
To do this, there are three main approaches that can be employed:
- Fingerprinting (static) approach: in this approach, the bot detection solution uses analysis tools to identify the traffic’s browser, OS, IP address, and other ‘fingerprints’/signatures to determine whether it is a malicious bot or human users. This method is passive, and can only detect bots with known fingerprints.
- Challenge-based approach: uses active challenges or tests like CAPTCHA to filter bots from human users. The tests should be (very) easy enough for human users to solve, but very hard if not impossible for bots.
- Behavioral-based (dynamic) approach: in this approach, the bot management solution uses various technologies to analyze the activities of the traffic and compare these activities against known patterns to verify its identity. Nowadays AI technologies and machine/deep learning are used to dynamically distinguish between bad bots, good bots, and human users.
Behavioral-based techniques are considered the most advanced approach in mitigating bot activities at the moment. With how newer bots are also using AI technologies to mimic randomized human behaviors and rotate between hundreds if not thousands of IP addresses, using AI in bot detection and management is now a necessity, no longer a luxury.
Why Is Bot Management Important?
Simply put, bot management is important because malicious bots are now the most common source for various cybersecurity threats. The impact of bad bot activities can be long-term and can cause significant damage to reputation and revenue.
Below are some of the most common cybersecurity threats caused by malicious bots:
- Brute force attacks and credential stuffing
A brute force attack is an attempt by automated software (bot) to guess a user credential by trying all possible combinations. Credential stuffing is a type of brute force attack where attackers use bots to try lists of stolen credentials until one is accepted. Credential stuffing and account takeover attacks have a relatively high success rate since we tend to use the same username-password pairs for multiple accounts.
- Content scraping
Attackers can use bots to scan and extract information and sensitive data from sites or databases. This information can include hidden product information, pricing data, hidden files, and so on. Websites in industries that are price-sensitive (i.e. ticketing) are prone to web scraping attacks from bots.
- Information harvesting
Malicious bots can scan websites, social media, and forums to find sensitive and personal information. Hackers can then use this information to launch phishing attacks and other attack vectors.
Bot management is now very important for any businesses that value their digital assets and information. With malicious bots being the source of various cybersecurity threats and attack vectors, there’s simply no reason to take a risk you don’t have to. DataDome can be a cost-efficient and effective solution in protecting your site, network, and system from malicious bot activities while ensuring human traffic and good bots can still access your resources.