Honeypot Injection for Web Application Attack Detection
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Solution Overview
Problem
Current web application firewalls have high total cost of ownership due to the need for continuous tuning, are ineffective in distinguishing between benign and malicious traffic, introduce friction for valid users, and have high false positive rates, and are limited in preventing manual, targeted attacks by skilled attackers.
Innovation Solution
A network security system that includes an attack mitigation apparatus which injects a honeypot into the source code of web application resources, allowing for behavioral analysis and client scoring to identify suspicious clients, and uses deceptive responses to prevent reverse engineering of the security policy, thereby reducing friction for valid users and enhancing attack detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If web application firewalls use attack signatures and policy engines to detect malicious behavior, then automated attacks and common vulnerabilities can be prevented, but false positive rates increase and manual targeted attacks by skilled attackers can bypass the system
Solution Approach 1:
The patent introduces honeypots as intermediary elements embedded within web application resources. These honeypots act as mediators that selectively engage with malicious clients without affecting benign users. When a client interacts with the honeypot, it triggers a conviction mechanism that marks the client as malicious, thereby improving detection accuracy without increasing false positives among legitimate users.
Solution Approach 2:
The patent applies different security treatments to different parts of the system: honeypots are injected into specific web application resources that are likely to be targeted, while benign resources remain unchanged. This localized approach ensures that security measures are applied precisely where needed, improving detection of targeted attacks without introducing unnecessary friction for legitimate users accessing other parts of the application.
2Reliability
If web application firewalls apply the same security rules to all users, then consistent security policy is maintained, but friction is introduced for valid users and performance is reduced
Solution Approach 1:
The patent segments users into different categories: benign users who never interact with honeypots and malicious users who do. This segmentation allows the system to apply different security treatments: benign users experience no friction and fast processing, while malicious users are identified through honeypot engagement and subjected to security actions. This resolves the contradiction by maintaining security policy consistency through the conviction mechanism while eliminating unnecessary friction for legitimate users.
3Adaptability or versatility
If web application firewalls continuously tune security policies to adapt to rapid web application updates, then effectiveness against new attacks is improved, but total cost of ownership increases due to requiring experienced administrators
Solution Approach 1:
The patent implements a self-adjusting security system where honeypots automatically engage with malicious clients and trigger conviction markings without requiring administrator intervention. The system autonomously adapts to new attack patterns by deploying honeypots into updated web application resources and automatically identifying malicious behavior through honeypot engagement, thereby maintaining high adaptability while eliminating the need for continuous manual tuning by experienced administrators.
4Reliability
If web application firewalls block suspicious traffic to prevent attacks, then security is improved, but skilled attackers can reverse engineer the policy engine by analyzing blocked requests
Solution Approach 1:
The patent converts the harmful behavior of attackers analyzing blocked requests into a beneficial detection mechanism. Instead of blocking suspicious traffic immediately, the system allows it to proceed and engage with honeypots embedded in the resources. The attackers' own analysis and interaction with the system reveal their malicious intent through honeypot engagement, which triggers conviction and marking. This approach maintains security while preventing information exposure about the policy engine, as the conviction mechanism operates independently of the policy engine's blocking decisions.
Data Source
AI summary
Methods, non-transitory computer readable media, attack mitigation apparatuses, and network security systems that improve network security for web applications are illustrated. With this technology, a web application resource associated with a protected web application is obtained from a server following receipt of a request for the web application resource from a client. A determination is made when the client is suspicious, and when the determination indicates the client is suspicious. The web application resource is modified by injecting a honeypot into source code of the resource. The honeypot comprises a conviction trap that can be engaged by the client. The modified web application resource is then sent to the client in a response to the request for the web application resource. Subsequently the client can be convicted as malicious if it is determined that the honeypot is engaged, thereby providing a more effective and accurate identification of manual attackers.