AI has become a hot topic in the last few years, not least for security professionals. ChatGPT may be the first thing many people think of when they think about AI, but if you’re trying to keep your organization secure, AI-driven bots are an emerging concern. Although bot attacks have been an issue for decades, they are becoming more challenging to prevent, detect, and stop.
Part of the reason for this is the combination of malicious bots with AI and machine learning. This has enabled bots to evade traditional mitigation tactics, often slipping by firewalls and other tools undetected. However, security tools that also use AI to improve their detection capabilities can help you keep ahead of malicious actors.
What are AI-Driven Bots?
A bot is automated software that is used to perform various tasks. They perform scans and web crawls, and they are ideal for simple, highly repetitive tasks. Bots are also highly effective tools for cyberattacks. They often run on compromised devices, in particular poorly secured IoT devices.
While there are many bots that perform positive and necessary functions, the bad bots pose a significant threat to organizations. DDoS attacks, for example, are attacks on networks caused by malicious bots to deprive a company of legitimate traffic or to shut down an application or website.
This threat is worsened by the growth of AI. Bad bots are becoming more intelligent and adaptable, which allows them to evade detection by firewalls and other security tools. Bots that incorporate AI are able to learn from their environments and adapt, which results in less predictable activity patterns or mimicry. An AI-driven bot is much more capable of imitating typical activity when attempting to access a network than a traditional bot.
Threats Posed by AI-Driven Bots
Bot threats are nothing new. They are behind several common attacks, including:
- Credential stuffing. When a data breach occurs and user credentials are leaked, attackers will often use these leaked credentials to attempt to infiltrate other websites or applications. This is done through credential stuffing attacks, in which a bot attempts to log in until one of the username and password combinations works.
- DDoS. In a DDoS attack, bots spam an application or website with requests. Eventually, host resources are overwhelmed, which prevents authorized user access.
- Web scraping. Although not all web scraping is necessarily bad, it can be a problem for your company. If your organization has trade secrets or other sensitive information built into your website, web scraping can pull them and transmit them to the public or your competition.
- Form spam. If your website or application has fillable forms, you are at risk for a form spam attack. In this attack, bots can misuse your forms to do things like transmit malicious code and overwhelm host resources.
Although these attacks could be prevented with firewalls and other anti-malware tools, AI enables attacks to be performed more quickly and effectively. AI can be used for vulnerability scanning, exploitation, defense evasion, and other malicious purposes. This makes it more difficult for your security solutions to block the attacks. In some cases, the bots are in and out before they are detected.
Mitigating AI Bot Attacks
You still need your security tools and solutions to defeat AI-powered bots. Robust security solutions that can close the gaps that these bots exploit are essential, but it helps if you can implement solutions that also harness the power of AI. Defensive use of AI can help your security teams quickly identify and address potential attack traffic.
An example of this is an AI-powered web application firewall (WAF). When you use a WAF that can leverage AI and machine learning, it is able to detect the subtleties of bot activity patterns, even when these bots are using AI to closely mimic normal traffic. The WAF can then block the bot traffic before it reaches your network. It can also adapt rules for blocking to reflect the bots’ activity.
Other mitigation strategies include:
- Account takeover protection. Using machine learning and context cues, this solution can keep bots from attempting to log in to user accounts.
- Runtime Application Self-Protection (RASP). By monitoring application activity, RASP stops processes if they do not reflect typical human user behavior. Using defensive AI, this tool can become more finely attuned to sophisticated bots attempting to pass for legitimate users.
- Input validation. Validating submissions to your forms can prevent injection attacks via malicious code in the forms. By leveraging AI to help detect anomalous inputs, you can improve the accuracy of your filters.
- Challenges. The most common example of a challenge is a CAPTCHA. Many bots are unable to complete challenges successfully.
When you’re looking for the best security solutions to mitigate the bot threat, make sure that you opt for a multi-layered solution. It’s important for your tools to intercept and block bots on both a network and an application level; also, they need to be able to do this without blocking your customers. Fortunately, there are solutions designed to keep your systems both safe and accessible.
Even when bots use AI to become more evasive and difficult to detect, you have options. Especially if you are able to use multi-layered solutions that are built with AI, you have a great deal of flexibility and adaptability to leverage against AI bot attacks.
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