How Do Bad Bots Attack Websites?
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Introduction to What Is a Bot?
Bad bots attack websites every day, resulting in financial losses, data breaches, and system disruptions in various industries. These automated scripts are designed to replicate human behavior while performing harmful tasks on a large scale. Whether it’s data theft or fraud, bad bots represent a category of automated software.
But what is a bot? In summary, a bot is a program or script that carries out tasks automatically, and while some bots are useful, malicious bots are designed for exploitation. Understanding how bad bots attack websites is essential for organizations—especially in sensitive fields such as finance, healthcare, and e-commerce, which require safeguarding their digital assets and customer information data.
In this article, we will explore the most common strategies that bad bots use to attack websites, the particular harm they inflict, and the vital protections organizations need to deploy.
Why Do Bad Bots Target Websites?
Before exploring the tactics, it’s crucial to grasp the reasons behind bad bots attacking websites. In contrast to good bots that index content or track site performance, malicious bots exist solely for exploitation. Their primary motives include:
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Financial gain via fraud or theft
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Data extraction and intellectual property theft
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System disruption for competitive or malicious purposes
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Unauthorized access to user accounts and services
How do bots work in this context?
They automate repetitive tasks, often at a large scale, allowing attackers to evade manual security measures and conduct intricate campaigns swiftly and discreetly. Websites that hold high-value information, like financial institutions or e-commerce platforms, are particularly susceptible. Let’s examine four common techniques that bad bots employ to infiltrate and attack websites.
How Bad Bots Attack Websites Through Credit Card Fraud
A common method used by malicious bots to target websites involves credit card fraud, especially through a technique referred to as card cracking.
1. What is Card Cracking?
Card cracking involves bad bots testing stolen credit card numbers (known as PANs) across payment gateways to determine valid combinations of security data like CVV, ZIP code, and expiration date.
2. Steps in a Bot-Based Credit Card Fraud Attack:
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Acquire stolen PANs (e.g., via phishing or underground markets).
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Automate form submissions on payment sites to guess the missing security details.
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Distribute attacks across dozens of websites to avoid detection.
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Verify and use valid card combinations for unauthorized purchases.
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Such bot-driven attacks can process thousands of credit cards daily with alarming speed and efficiency.
3. How to Stop Credit Card Fraud Bots:
| Defense Method | Description |
|---|---|
|
Device Fingerprinting |
Identifies recurring devices and browsers, even across sessions. |
|
Browser Validation |
Ensures the browser behavior matches a real human interaction. |
|
Behavioral Analytics |
Detects anomalies like repetitive purchase attempts or fast keystrokes. |
|
Reputation Analysis |
Flags known bot signatures and IPs using blacklists and behavior patterns. |
|
Progressive Challenges |
Uses cookie tests, JavaScript challenges, or CAPTCHAs based on suspicious activities. |
Moreover, implementing multi-factor authentication (MFA) along with encrypting credit card APIs and applying stringent authorization measures can significantly lessen the risk of fraud.
How Bad Bots Attack Websites Through Account Takeover (ATO)
Another major way bad bots attack websites is through account takeover or credential stuffing. This tactic involves trying thousands of stolen usernames and passwords across different services.
How It Works
Bad bots rely on the fact that many users reuse passwords. Attackers automate login attempts using large credential databases until they find a match.
1. ATO Attack Process:
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The bot accesses multiple accounts using stolen credentials.
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It mimics different IP addresses to evade detection.
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Successful logins are flagged and exploited for personal or financial information.
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Accounts may be resold or utilized for phishing campaigns.
2. ATO Prevention Measures:
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Device Fingerprinting and CAPTCHA: Prevent repeated, rapid login attempts from the same device.
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IP Blacklisting: Block IPs exhibiting abnormal login activity.
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Rate-limiting non-residential IPs: Throttle login attempts from data centers or proxy servers.
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Headless Browser Detection: Blocks browsers operating without a GUI, commonly used by bots.
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Avoid Using Email as Username: Decrease the chances of credential reuse across websites.
Track login behaviors and initiate enhanced authentication steps upon identifying anomalies to more effectively detect malicious bots.
How Bad Bots Attack Websites Using DDoS Attacks
Distributed Denial of Service (DDoS) is a well-known method where bad bots attack websites to overwhelm servers with traffic, making the site unusable for legitimate users.
1. What Is a Bot-Based DDoS Attack?
These attacks specifically target the application layer of the OSI model, bombarding the website with high volumes of legitimate-looking requests. This consumes server resources and renders services unavailable.
2. Symptoms of a Bot-Driven DDoS Attack
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Increase in requests per second (RPS)
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Delayed site response or total outages
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Uncommon traffic sources or patterns
3. DDoS Mitigation Strategies
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Always-On and On-Demand Mitigation Systems
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Traffic Filtering Rules
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Rate Limiting for High RPS IPs
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Geo-blocking or IP Reputation Services
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Cloud-Based Load Balancing and Caching
Proactive DDoS protection is crucial for maintaining uptime and preventing revenue loss during peak attack periods. How does AI detect bad bots in this case?
AI systems examine past traffic trends to identify irregularities in request rates, source behaviors, and payloads in real time.
How Bad Bots Attack Websites Through Content Scraping
Content scraping is a stealthier way bad bots attack websites. These bots scan websites to collect information like pricing, interest rates, product details, and proprietary research.
1. Impacts of Scraping:
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Loss of Competitive Edge: Malicious bots have the ability to extract your proprietary content- like loan rates and financial tools- granting competitors the opportunity to imitate and profit from your efforts.
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SEO Penalties: If your content is duplicated elsewhere, search engines might penalize your site, which can negatively affect your visibility and search rankings.
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Performance Degradation: Large amounts of bot traffic overtax your server resources, leading to site slowdowns or outages that annoy genuine users.
2. Identifying Malicious Scraping
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Fake HTTP Headers: While legitimate bots reveal their identities, malicious ones frequently disguise themselves with deceptive user-agent strings.
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Ignoring Robots.txt: Ethical crawlers adhere to robots.txt rules, while malicious bots circumvent these restrictions to access all areas of your site.
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Unusual Crawling Patterns: Legitimate bots crawl at regular intervals, while malicious bots often bombard your site in erratic, high-volume bursts, indicating abusive behavior.
3. Content Scraping Defenses
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User-Agent Analysis: Block or challenge suspicious requests that feature forged or unusual headers.
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Rate Limiting and Throttling: Limit repeated access attempts from the same IP to decrease scraping speed and deter abuse.
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Bot Detection AI: AI can identify malicious bots by recognizing unusual behaviors such as rapid clicking, non-human scrolling patterns, or a lack of mouse movement—demonstrating how AI identifies harmful bots.
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Robots.txt and Honeytraps: Guide ethical bots using robots.txt and establish hidden fields or fake links (honey traps) to capture scrapers in action.
Why Financial Services Are Prime Targets Due to Bad Bot attacks on websites
Websites in the financial industry are prime targets because they harbor vast amounts of personal and financial data. According to a recent analysis, only 37% of traffic to these sites comes from real users, while more than 30% is driven by malicious bots.
Financial services experience attacks through all four methods previously mentioned: credit card fraud, account takeover (ATO), Distributed Denial of Service (DDoS), and data scraping, which leads to:
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Unauthorized financial transactions
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Identity theft and subsequent regulatory penalties
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Service outages and customer dissatisfaction
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Loss of competitive intelligence and market credibility
How to Stay Protected Against Bad Bots
Understanding how bots function and how they attack websites is crucial for proactive protection. As attacks become more sophisticated, defenses like IP blocking or CAPTCHA are insufficient. A comprehensive strategy combines multiple security layers: Behavioral analytics, Device and browser fingerprinting, Progressive challenges, Machine learning-based detection, API security, and strict authentication.
Websites in sectors like finance, healthcare, and e-commerce must continuously adapt their defenses to counter malicious bots. Inaction is costly—bots will keep evolving.
How Prophaze Defends Against Bad Bots
Organizations need adaptive, intelligent defenses to combat the growing menace of malicious bots. Prophaze offers an AI-powered Web Application Firewall (WAF) that safeguards against critical threats such as credit card fraud, account takeovers, DDoS attacks, and content scraping. By leveraging behavioral analysis, real-time bot detection, and automated threat mitigation, Prophaze empowers organizations to identify and block malicious bots before they can cause damage. It’s a proactive, future-ready solution for the evolving landscape of bad bot attacks.
