A sophisticated method to bypass Web Application Firewall (WAF) protections using HTTP Parameter Pollution techniques combined with JavaScript injection.
The research, conducted by Bruno Mendes across 17 different WAF configurations from major vendors including AWS, Google Cloud, Azure, and Cloudflare, revealed alarming vulnerabilities in the current web security infrastructure.
The technique exploits fundamental parsing differences between WAF engines and web application frameworks, particularly ASP.NET’s parameter handling behavior, to execute Cross-Site Scripting (XSS) attacks that evade traditional security detection mechanisms.
Key Takeaways
1. Splitting XSS payloads across multiple HTTP parameters defeats WAF detection.
2. Only 3 out of 17 major WAF configurations blocked sophisticated parameter pollution attacks.
3. AI hackbot achieved 100% bypass success, finding simple exploits in seconds.
Exploiting ASP.NET Parameter Concatenation
The breakthrough technique leverages ASP.NET’s specific behavior when processing duplicate HTTP parameters.
When ASP.NET encounters multiple parameters with the same name through its HttpUtility.ParseQueryString() method, it concatenates their values using commas.
This behavior creates an opportunity for sophisticated bypasses when combined with JavaScript’s comma operator syntax.
The researchers at Ethiack demonstrated how a seemingly benign query string like /?q=1’&q=alert(1)&q=’2 gets processed by ASP.NET into the concatenated form 1′,alert(1),’2.
When this payload is inserted into a JavaScript context, such as userInput = ‘USER_CONTROLLED_DATA’;, it becomes valid JavaScript code: userInput = ‘1’,alert(1),’2′;.
The comma operator in JavaScript evaluates each expression sequentially, effectively executing the malicious alert(1) function while maintaining syntactic validity.
Traditional WAFs struggle to detect this technique because they typically analyze individual parameters rather than understanding how web frameworks parse and concatenate multiple parameter values.
Bruno Mendes tested three increasingly sophisticated payloads, ranging from simple injection attempts like q=’;alert(1),’ to complex parameter pollution payloads using newlines and variable assignments such as q=1’%0aasd=window&q=def=”al”+”ert”&q=asd[def](1)+’.
WAF Vulnerabilities Discovered
The testing results exposed significant gaps in current WAF protection mechanisms.
Only three out of 17 tested configurations successfully blocked all manually crafted payloads: Google Cloud Armor with ModSecurity rules, Azure WAF with Microsoft’s Default Rule Set 2.1, and all open-appsec configurations.
Notably, multiple AWS WAF rule sets, including AWS Managed Rules, Cyber Security Cloud rule set, and F5 rule set, were completely bypassed by every payload tested.
The bypass success rates increased dramatically with payload complexity, escalating from 17.6% for simple payloads to 70.6% for sophisticated parameter pollution techniques.
Even more concerning, the researchers’ automated “hackbot” achieved a 100% detection evasion rate, successfully finding bypasses for previously resilient WAF configurations.
For instance, the hackbot discovered that Azure WAF could be bypassed using a simple payload test\\’;alert(1);// that exploits parsing discrepancies in escaped character handling.
The research highlighted a critical security paradox: organizations investing in expensive WAF solutions may remain vulnerable to both sophisticated parameter pollution attacks and surprisingly simple bypass techniques.
The findings demonstrate that signature-based WAFs are particularly susceptible to these attacks, while machine learning-based solutions show better detection capabilities but still contain exploitable vulnerabilities.
This research underscores the fundamental limitation that WAFs cannot fully simulate application parsing behavior, creating differential vulnerabilities that skilled attackers can exploit.
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