恶意机器人报告（英文版）_28页_1mb

2020 Bad Bot Report Summary

Core Content

The 2020 Bad Bot Report by Imperva provides a comprehensive analysis of the evolving threat landscape involving bad bots. It outlines the increasing sophistication and prevalence of these automated threats across various industries, emphasizing their impact on website security, business operations, and customer experience.

Main Points

1. Bad Bot Activity Trends

• Bad bot traffic reached its highest level in the report's history, accounting for 24.1% of all website traffic in 2019, up from 18.1% the previous year.
• Human traffic increased by 1.1% to 62.8%, while good bot traffic dropped to 13.1%, down from 25.1% the prior year.
• The U.S. remains the top source of bad bot traffic at 45.9%, followed by the Netherlands, Canada, China, and Germany.

2. Rebranding of Bad Bots

• Bad bots are increasingly being marketed as "business intelligence" services, offering data scraping, competitive insights, and other tools that appear legitimate.
• This trend has made it harder to distinguish between good and bad bots, especially as bad bots adopt Chrome-like user agents to mimic real users.
• The use of "hypebots" and "sneaker bots" is on the rise, allowing malicious actors to gain unfair advantages in the marketplace.

3. Types of Bad Bot Activities

• Price Scraping: Competitors steal pricing data, leading to loss of market share and SEO issues.
• Content Scraping: Unauthorized use of proprietary content, damaging brand value and SEO rankings.
• Account Takeover (Credential Stuffing): Stolen credentials are used to access user accounts, leading to financial fraud, unauthorized purchases, and chargebacks.
• Credit Card Fraud: Bots test stolen credit card numbers to find valid ones, often targeting nonprofit organizations.
• Denial of Service (DoS): Bad bots cause site slowdowns and downtime, impacting customer experience and business revenue.
• Denial of Inventory: Bots hold inventory in shopping carts, preventing real customers from accessing products.
• Social Media Influence: Bots are used to spread propaganda and influence election outcomes by manipulating social media accounts.

4. Bad Bot Sophistication Levels

• Simple bots (26.3%) are the easiest to detect, using single IP addresses and no browser simulation.
• Moderate bots (53.6%) are more advanced, using headless browsers to execute JavaScript.
• Sophisticated bots (20.1%) mimic human behavior, including mouse movements and clicks, and are harder to detect.
• Advanced Persistent Bots (APBs) (73.7%) are the most dangerous, using anonymous proxies, rotating IPs, and stealth techniques to evade detection.

5. Industry-Specific Bot Problems

• Financial Services (47.7%) face the highest proportion of bad bot traffic, primarily due to credential stuffing and data scraping.
• Education (45.7%) is targeted for research paper access, class availability, and account takeover.
• Marketplaces (39.8%) and E-commerce (18.6%) suffer from price and content scraping, as well as account and credit card fraud.
• Ticketing (25.8%) and Airlines (30.5%) are heavily impacted by credential stuffing and inventory manipulation.
• Nonprofits (32.7%) are particularly vulnerable to credit card testing and fraudulent donations, which result in chargebacks and reputational damage.

6. Bad Bot Identity and Behavior

• Over 55.4% of bad bots claim to be Google Chrome, followed by Firefox (13.3%) and Safari (7.9%).
• A significant portion of bad bots (70%) originate from data centers, a slight decrease from 73.6% in 2018.
• The use of Amazon ISP by bad bots has also decreased, from 23.5% in 2018 to 11.6% in 2019.
• Many bad bots are using old browser versions, such as Internet Explorer 5, which was the most commonly claimed browser in 2019.

7. Impact on Businesses

• Bad bots increase infrastructure costs, cause skewed analytics, and lead to revenue loss.
• They are used for fraud, spam, and competitive intelligence, and are becoming more legitimized as part of the business ecosystem.
• The arms race between bot operators and security measures continues as new evasion techniques are developed.

Key Recommendations

• Detect and block bad bot activity using advanced bot detection tools.
• Monitor traffic patterns to identify anomalies such as spikes in login attempts or unexplained site slowdowns.
• Implement user agent analysis to differentiate between legitimate and malicious bots.
• Enhance authentication mechanisms to prevent credential stuffing and account takeover.
• Invest in infrastructure resilience to handle the high volume of bot traffic without affecting real users.

Conclusion

The 2020 Bad Bot Report highlights the growing threat of bad bots, their increasing sophistication, and their impact across all industries. As these bots continue to evolve and rebrand as legitimate tools, businesses must remain vigilant and adopt robust security measures to protect their digital assets and user experience.