How to Block Bots Bypassing Geolocation via Proxy

Bots Using Proxies to Bypass Geolocation Restrictions: Detection and Protection

Bots that use proxies to bypass geolocation restrictions pose a serious threat to web applications. Effectively combating them requires a multi-layered approach that combines behavioral analysis, machine learning, and specialized proxy detection tools.

Table of Contents

• Understanding the Problem
• Main Methods for Detecting Proxy Bots
• Integrated Protection Solutions
• Technical Implementation with fail2ban
• Performance and Security Optimization
• Deployment Recommendations

Understanding the Problem

Your observation about the absence of GEO variables in bots is a key indicator of automated scripts. As experts from Imperva note, modern bots use sophisticated masking techniques, including IP rotation and emulation of real user behavior.

The main challenge is that simple IP blocking is ineffective against proxy bots that constantly change traffic sources. This leads to firewall bloat and creates a false sense of security, as bots easily bypass such restrictions.

Main Methods for Detecting Proxy Bots

Behavioral Analysis

Modern protection systems use behavioral analysis to identify anomalies in user actions. As Indusface points out, this allows identification of deviations from normal behavior patterns that are characteristic of bots.

Key behavioral markers:

• Absence of natural pauses between requests
• Mechanical interaction patterns with the interface
• Missing session variables such as GEO
• Unnatural action sequences

Proxy and VPN Detection

Specialized services can detect proxy connections with high accuracy. According to IP2Location, IP geolocation tools can identify and block IP addresses from known VPN and anonymizer providers.

Detection methods:

• TTL (Time To Live) packet analysis
• Checking open proxy ports
• Comparing geolocation data with IP reputation
• Using databases of known proxy servers

Integrated Protection Solutions

Comprehensive Bot Protection Platforms

Modern solutions offer a multi-layered approach to detecting malicious bots, combining client polling, behavioral analysis, machine learning, and connection characteristics analysis Imperva.

Popular platforms:

• Cloudflare: Uses machine learning, behavioral analysis, and global threat intelligence
• HUMAN Security: Provides AI and behavioral analysis to block malicious bots
• Kasada: Unique approach with client-side verification and behavioral analysis
• Feedzai: Combines advanced AI, behavioral analytics, and real-time monitoring

API Security and Validation

For protecting search forms as in your case, multi-factor validation is important. As noted by IPinfo, many API providers already use a matrix of validation checks to ensure legitimate access to endpoints.

Technical Implementation with fail2ban

Configuring Rules for Proxy Bots

Your approach using fail2ban is viable but requires optimization. Here are effective strategies:

1. Hybrid approach with behavioral triggers:

[Definition]
# Block based on missing GEO variable + frequent requests
failregex = .*MISSING_GEO.* .*\.(GET|POST).*search.*
ignoreregex = 

2. Using time windows:

findtime = 300  # 5 minutes
bantime = 3600  # 1 hour
maxretry = 3    # 3 failed attempts

Firewall Optimization

To prevent firewall bloat:

1. Use IP address aggregation by proxy provider subnets
2. Implement dynamic cleanup of old rules
3. Configure threshold values for automatic cleanup

Performance and Security Optimization

Balancing Protection and Convenience

Effective protection should minimize impact on real users. As Security Boulevard recommends, your system should reduce reliance on CAPTCHA by using behavioral analysis instead.

Machine Learning for Adaptive Protection

Implement adaptive machine learning models that continuously learn from new traffic patterns. As noted by GlobalDots, this allows identification of anomalies characteristic of bot behavior.

Deployment Recommendations

Phase 1: Monitoring and Analysis

First, implement passive monitoring to collect data on bot behavior:

• Log all requests with missing GEO variables
• Analyze request frequency patterns
• Collect data on used headers and browser fingerprints

Phase 2: Gradual Protection Implementation

1. Start with simple blocking rules based on missing GEO
2. Add behavioral triggers
3. Implement specialized proxy detection
4. Optimize firewall rules

Phase 3: Continuous Improvement

Regularly update proxy databases and rule settings based on analysis of new threats.

Sources

1. Bypass Bot Detection (2025): 5 Best Methods - ZenRows
2. Proxies as a Service: How to Identify Proxy Providers via Bots as a Service - DataDome
3. How to Bypass Cloudflare in 2025: The 9 Best Methods - ZenRows
4. What are Bots and Bot Traffic? How to Detect, Stop & Prevent Bot Attacks? - Certara
5. Using machine learning to detect bot attacks that leverage residential proxies - Cloudflare Blog
6. Advanced Bot Protection | Stop Advanced Bots - Imperva
7. Bot Protection - Top 7 Tools for 2024 - Trusted Accounts
8. Bot Protection - Detect & Stop Bad Bots - HUMAN Security
9. 9 Bot Detection Tools for 2025: Selection Criteria & Key Questions to Ask - Security Boulevard
10. Top 9 Bot Detection Software & Tools - SEON

Conclusion

To effectively combat proxy bots that bypass geolocation, we recommend:

1. Using a combined approach that combines behavioral analysis and proxy detection
2. Implementing multi-layered protection with gradually enhanced security measures
3. Optimizing fail2ban rules to prevent firewall bloat
4. Considering implementation of specialized bot protection platforms for comprehensive protection
5. Continuously updating databases and detection algorithms based on analysis of new threats

Your observation about the absence of GEO variables in bots is a valuable indicator that can be used as part of a comprehensive protection strategy. Start with basic rules and gradually enhance the system as you collect more data about attacker behavior.