What is Bot Management?

Bot Management: Protecting Your Business from Automated Attacks

Bots are software designed to automate and scale certain tasks that would normally be performed manually by a human. There is a wide range of bot behaviors – some good, like search engine crawlers that catalog websites so that they show up in search results, and some bad, like malicious bots designed to harvest email addresses and account information for nefarious purposes. While bots have been around almost as long as the internet itself, they continue to get more sophisticated and better at emulating human behavior in an effort to evade detection, and effective bot management has become a necessity.

The process of distinguishing bots from humans, sorting good bots from bad, and mitigating malicious bots is what the security industry calls “bot management.” This article will discuss bot management in depth centered around the following themes:

• Impacts of Malicious Bots
• Bot Management and API Security
• Traditional Bot Mitigation Techniques
• Effective Bot Management Solution Requirements
• Bot Management and AI
• Getting Started with Bot Management

Impacts of Malicious Bots

Bots are simply the vehicle for automated attacks, so organizations may not immediately know they have a bot problem. For example, if user accounts are being taken over by bad actors, it may not be immediately apparent that bots are being used to do so at scale. Without a bot management solution in place to detect attacks and identify associated bots, manual investigation is needed to determine if it’s a full-scale bot attack.

It is important to understand the potential targets for attackers and their bots. Web applications are the most obvious, but the proliferation of APIs and the fact that they often provide access to sensitive data make them a compelling target as well. APIs are typically not as visible to security teams since they have no graphical user interface, so they may not be as well protected as traditional web applications.

Ultimately there are broad potential impacts of malicious bots, including direct business impacts such as fraud or sensitive data exposure, as well as indirect impacts such as regulatory implications. Existing regulations such as PCI DSS and HIPAA require systems that process Personal Identifiable Information (PII) to be compliant and protect consumers against fraud and privacy violations, and protecting those systems against bots falls under these and other regulations.

Common risks of malicious bots include:

• Account takeover (ATO) – Using stolen credentials to gain unauthorized access to legitimate user accounts
• Sensitive data exposure – Gathering sensitive data unintentionally exposed by applications and APIs
• Credential stuffing – Using stolen, legitimate credentials to access services
• Flash sales, hype sales, and ticket scalping – Mass purchasing high-demand products quickly for resale, or “jumping the line” to hoard products and deny legitimate customers
• Content scraping/IP theft – Harvesting sensitive data for resale, ransom, or other nefarious purposes
• Gift card/loyalty program abuse – Brute-forcing card object (card number, owner name, PIN, etc.) combinations to find valid gift cards or loyalty program details
• Fake account creation – mass creation of accounts from fake or stolen user identity information
• SIM Swapping – A type of account takeover specific to cell phones that compromises user accounts with unauthorized SIM swaps

Many of these use cases are enabled by business logic abuse, which appear as valid user interactions. These types of abuse are exceedingly difficult to identify because the bot exploits intended app or API functionality. Ultimately, malicious bots can result in decreased application performance and availability, adverse effects on sales and marketing metrics, and infrastructure and personnel cost increases.

Bot Management and API Security

Digital transformation has elicited significant changes in infrastructure over the past decade. Traditional monolithic web and mobile applications have been restructured into microservices that operate primarily through APIs, complemented by the rise of cloud environments like Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP). Businesses have gained dramatically increased flexibility and scalability through these transformations as well as enhanced website performance and reduced downtime. Nonetheless, these developments have also decreased the visibility of the infrastructure for security and IT teams while the potential attack surface has increased.

APIs have become the primary means for applications to interact, both internally and between organizations. Their simplicity, flexibility, and speed facilitate easier data integration and sharing among applications, but also allow attackers to easily orchestrate large-scale automated assaults using networks of malicious bots. Advanced toolkits for bot attacks and the abundance of stolen credentials online have simplified the process for attackers to manipulate business logic and hijack accounts to commit fraud or steal sensitive data. Business logic abuse attacks disguise themselves as legitimate operations, complicating the process of identifying which activities to block.

Traditional Bot Management Techniques

Traditional bot management solutions have been somewhat effective but are not without their drawbacks. Malicious bot identification is more difficult than it has ever been, and sophisticated attackers continually improve their methods to improve their attack success rate. In addition to the detection difficulty of attacks that abuse business logic, so-called “low and slow” attacks that are low volume and spread out over time are also difficult for traditional bot management solutions to detect and prevent.

• IP reputation-based bot management
  • Solutions such as Web Application Firewalls (WAF) and CDNs with bot protection capabilities often leverage IP address reputation for bot defense, examining the history of the IP address and categorizing it as good or bad. However, attackers can easily spread attacks across large numbers of IP addresses with clean reputations, such as hijacked residential IPs, making this solution inadequate.
• JavaScript-based/challenge approach
  • Another bot mitigation technique requires integrating JavaScript or SDKs into web pages, applications, and mobile applications. CAPTCHA systems are widely used but they have several drawbacks. They have a significant impact on user experience and require development and QA effort to implement and test. Critically, JavaScript-based approaches do not directly support APIs, leaving this vital infrastructure unprotected.

Effective Bot Management Solution Requirements

Adversaries continue to increase the sophistication of their attacks, graduating from basic site-scraping bots to sophisticated custom attack platforms. Solutions to match their sophistication can’t rely on IP reputation and JavaScript approaches – what’s needed is a multi-dimensional bot detection and mitigation strategy that is able to protect all applications and APIs and maintain effectiveness as adversaries retool to evade detection.

Effective bot management solutions deliver the following:

• Implement rapidly and support a variety of deployment options to meet customer needs
• Protect applications and APIs without requiring code-level integrations such as CAPTCHAs or infrastructure changes
• Provide coverage for web and mobile applications as well as those for cloud- and microservices-based architectures
• Intelligently identify behavioral anomalies and evolve with attacks
• Agile, responsive, and resilient to adversary re-tooling in real time
• Effective immediately upon deployment without requiring days or weeks of tuning and baselining
• Offer broad mitigation options such as logging, tagging, deception, and blocking

Bot Management and AI

A recent development poised to shake up the bot world both from an attacker’s and a defender’s standpoint is the increased use of machine learning (ML) and artificial intelligence (AI). Large language models (LLM) make it easier and faster to create purpose-built bots and are likely to pose challenges that are as yet unknown. There are already AI models that claim to defeat CAPTCHAs with 100% accuracy, likely kicking off a new cat-and-mouse game as the bot management solutions that rely on JavaScript challenge-based approaches struggle to stay ahead of attackers. The best bot management solutions have relied on ML models to detect bots, whether they’re part of loud, brute force-style attacks or quieter slow-and-low attacks that were previously extremely difficult to detect. If you’re interested in the intersection of AI and enterprise security, we’ve written a blog about GenAI.

How to Get Started

Traditional bot management solutions have proven daunting to implement, especially if they require application modification through JavaScript or mobile SDK integration. However, modern solutions such as Cequence can be deployed via SaaS, dramatically simplifying onboarding and streamlining the number of departments and subject matter experts that are required. Cequence can be deployed in passive mode that enables the customer to see what’s detected and what would be blocked without affecting traffic, with an easy transition to inline when the customer is ready.

Cequence offers a unique approach to bot management that is easy to deploy, provides rapid time to value, and is highly effective. If you’d like to learn more, contact us and let Cequence show you how we can address bots in your unique situation.