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Hostile Web Bots: Why Modern Bots are Difficult to Detect and Defeat (and How to Do it Anyway)by@reblaze
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Hostile Web Bots: Why Modern Bots are Difficult to Detect and Defeat (and How to Do it Anyway)

by ReblazeSeptember 8th, 2023
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The diverse and creative ways in which hostile bots are used today pose significant challenges to web security. To safeguard modern digital ecosystems, a proactive and multi-faceted approach that combines advanced security solutions and vigilant monitoring is essential.
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In the ever-evolving digital landscape, web security has become an imperative concern. Among the myriad threats lurking in cyberspace, hostile bots are a formidable adversary.


Bots (an abbreviation for “web robots") are software applications programmed to execute tasks autonomously on the internet. While certain bots play a positive role and contribute to diverse online functions like aiding search engine indexing or providing customer support through chatbots, there are hostile bots, created and used with malicious intent. These automated entities, capable of executing a wide array of actions, have escalated from minor annoyances to serious security challenges.


This article explores the current state of hostile bots, their multifaceted applications, the ingenious ways in which threat actors are using them, and how to defeat them.

Understanding the State of Hostile Bots

In the current digital landscape, hostile bots encompass a spectrum of capabilities, ranging from basic data scraping to complex distributed denial of service (DDoS) attacks. Many bots have a high degree of versatility and sophistication; this adaptability allows them to evolve their tactics and evade conventional detection methods, posing significant challenges to web security.


Malicious bots have evolved beyond their rudimentary origins to adopt human-like behaviors. Many can mimic genuine user interactions, making it increasingly difficult to distinguish them from legitimate human traffic. Their evasion tactics, such as IP rotation, browser emulation, and behavior mimicry, challenge traditional security measures and demand innovative countermeasures.

Diverse Attack Vectors

While some bot-driven threats are widely recognized, others remain relatively obscure, making the defense against them an ongoing challenge. Below are some of the most common of these attack vectors.

1. DDoS Attacks

Distributed denial of service assaults are ubiquitous on the modern web. In these incidents, attackers attempt to overwhelm a target website or service with a massive volume of traffic, rendering it inaccessible to legitimate users. Hostile bots are used to wage these attacks, at the scale of the attacker’s choosing. These events can disrupt online services, cause downtime, and result in financial losses.

2. Web Scraping and Data Theft

Hostile bots are often used for web scraping, where they gather information from websites for various purposes, including market research, content theft, and competitive intelligence. While web scraping itself may not always be malicious, it can lead to intellectual property theft and loss of revenue for businesses.

3. Credential Stuffing Attacks

Another common use of hostile bots is in credential stuffing attacks. Hackers attempt to use previously stolen usernames and passwords to gain unauthorized access to various online accounts. Bots automate the process of trying these credentials across multiple platforms, exploiting users who reuse passwords across different sites. The goal is to gain access to sensitive information, financial accounts, or even corporate networks.

4. Impersonation and Fake Accounts

Threat actors deploy hostile bots to create fake accounts on social media platforms, forums, and other online communities. These fake profiles can be used for spreading misinformation, conducting scams, or promoting malicious content. They can also be leveraged for social engineering attacks, exploiting trust and credibility to manipulate users into taking harmful actions.

5. Scraping and Data Theft

Many types of sites are threatened by bots designed to wage custom forms of attack. Data aggregators, apps that quote prices or rates, and certain other types of sites must defend against bots that scrape private data and exploit it in ways that are harmful to the owners of that data. E-commerce websites can be attacked by competitors using bots to scrape pricing information and dynamically adjust their own prices, leading to distorted market dynamics and unfair competition. These subtle manipulations can create an unfair competitive advantage and inflict significant financial damage.

6. API Abuse and Brute-Force Attacks

Hostile bots can exploit weaknesses in Application Programming Interfaces (APIs), gaining unauthorized access, exploiting data leaks, or facilitating further attacks. Brute-force attacks, where bots systematically try various combinations to break into systems or accounts, pose a persistent threat. These attacks can have far-reaching consequences, from data breaches to compromised infrastructure.

7. Inventory Hoarding

Specialized hostile bots can attack e-commerce sites and make inventory unavailable to legitimate customers. For example, they can add products to shopping carts, but never complete the purchases. Another example is travel sites that are attacked by bots that abuse time-to-checkout policies, continually looping and starting to book reservations without ever purchasing tickets. This prevents actual customers from purchasing, and other financial damage can occur as well.

8. Political Influence

Hostile bots have been used to amplify fake news, manipulate public opinion, and spread misinformation during political events and elections. They can create the illusion of widespread support for certain ideas or candidates, impacting democratic processes.

9. Automated Fraudulent Activities

Hostile bots are also used for various forms of fraud, such as ad fraud and fake account creation. Ad fraud involves generating fraudulent ad impressions and clicks to siphon off advertising revenue. Similarly, the creation of fake accounts can deceive users, inflate follower counts, and artificially boost engagement metrics, thereby undermining the authenticity of online interactions.

Defeating Hostile Bots

Why Bots Can Be Difficult to Detect

Bots range from simple simple scripts to advanced AI-driven agents. The most sophisticated ones can be very difficult to recognize. Advanced hostile bots can mimic human behavior by simulating mouse movements, keyboard input, and browsing patterns. Further, threat actors have developed ways to bypass CAPTCHAs and other security measures designed to distinguish between humans and bots.


To make matters worse, underground markets have arisen that include the sale of botnet services. Even non-technical threat actors can now rent and deploy advanced hostile bots to wage their attacks. As a result, while older and simpler bots are still common on the web today, there is a rising percentage of advanced threats that are more difficult to defend against.

Effective & Efficient Bot Detection

An effective bot management solution must be able to block highly sophisticated bots that can evade conventional identification techniques. As mentioned earlier, modern hostile bots are often programmed to mimic human behavior, making their detection challenging. However, with advanced algorithms and detection mechanisms, an effective bot management system can accurately distinguish between genuine users and malicious bots.


Efficiency plays a crucial role in bot management, particularly in handling large traffic volumes in real time. The detection of sophisticated bots may necessitate significant computational capabilities, all while ensuring that the performance of the protected system remains uncompromised. An efficient bot management solution must be capable of consistently mitigating and detecting bot traffic while maintaining high performance levels.


This can be done through a multi-step bot detection process, filtering traffic through multiple stages. The process should start with rapid and computationally economical techniques like signature profiling, threat intelligence feed verification, and environmental profiling. These initial steps quickly eliminate a significant portion of easily identifiable bots. Another key technique is rate limiting, which is important for blocking bots that are submitting requests (such as login attempts) that otherwise appear to be legitimate.


Subsequent stages, such as dynamic filtering, demand more resources but have the capacity to detect and block more sophisticated bots. The most resource-intensive analysis, which encompasses biometric behavioral assessment, is solely employed on traffic that has successfully traversed all preceding stages. This strategic approach facilitates precise identification of even the most intricate bots, while keeping latency to a minimum.

Manipulating Bots and Deceiving Threat Actors

While the primary focus of a bot management solution revolves around achieving effective and efficient detection, advanced systems can surpass mere bot mitigation, and actively mislead threat actors.


For example, the solution can return custom responses to specific bot activities. Threat actors will use the http response status codes from a web application or API to orchestrate their activities; a solution can confuse their actions by returning unexpected or deceptive codes.


Another example: imagine an e-commerce establishment besieged by competitor-driven price-scraping bots. Instead of simply blocking these bots, a strategy that rivals might notice and strive to overcome, the targeted store can manipulate the bots' encounters by presenting them with fabricated information. By adopting this approach, the affected store disrupts the rivals' endeavors to pilfer and exploit sensitive data. As a result, rather than reacting in a passive manner to the presence of bots, the victimized entity in effect takes charge and directs the bots' behaviors, ultimately thwarting their harmful motives.


Other examples could be given. By assuming control over bot activities, victims can frustrate the efforts of malevolent bot operators, safeguard their data and intellectual assets, and gain valuable insights into potential risks. This proactive engagement level significantly contributes to shielding websites and online services against the deleterious effects of bot assaults.

Conclusion

The diverse and creative ways in which hostile bots are used today pose significant challenges to web security. From credential stuffing attacks to political influence campaigns, the impact of these automated threats can be far-reaching and damaging. As technology continues to advance, threat actors will likely find new and innovative ways to exploit vulnerabilities.


To safeguard modern digital ecosystems, a proactive and multi-faceted approach that combines advanced security solutions and vigilant monitoring is essential. By staying informed about the tactics employed by hostile bots and implementing effective countermeasures, we can collectively defend against these evolving threats and ensure a safer online experience for all.