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Description
The recognition of web attacks utilizes a combination of AI and predefined rules, ensuring robust anti-bypass capabilities and maintaining low rates of both false negatives and false positives. This system effectively protects against prevalent web threats, such as those listed in the OWASP top 10, which encompasses issues like SQL injection, unauthorized access, cross-site scripting, and cross-site request forgery, among others. Additionally, users have the option to store essential web content in the cloud, enabling the publication of cached web pages that serve as backups to mitigate the risks associated with web page alterations. The backend infrastructure is safeguarded through a comprehensive strategy that includes concealing servers and applications before an attack occurs, preventing attacks during ongoing incidents, and replacing or concealing sensitive data after an event. Furthermore, the Web Application Firewall (WAF) conducts extensive DNS verification across the nation for the domains provided by customers, allowing it to identify and report any hijacking attempts affecting the protected domain names in different areas, which is crucial for preventing data breaches and financial losses linked to user hijacking on websites. This multifaceted approach not only fortifies security but also enhances user trust in web services.
Description
open-appsec is an open-source initiative that builds on machine learning to provide pre-emptive web app & API threat protection against OWASP-Top-10 and zero-day attacks.
It can be deployed as add-on to Kubernetes Ingress, NGINX, Envoy and API Gateways.
The open-appsec engine learns how users normally interact with your web application. It then uses this information to automatically detect requests that fall outside of normal operations, and sends those requests for further analysis to decide whether the request is malicious or not.
open-appsec uses two machine learning models:
1. A supervised model that was trained offline based on millions of requests, both malicious and benign.
2. An unsupervised model that is being built in real time in the protected environment. This model uses traffic patterns specific to the environment.
open-oppsec simplifies maintenance as there is no threat signature upkeep and exception handling, like common in many WAF solutions.
API Access
Has API
API Access
Has API
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Tencent
Founded
2013
Country
China
Website
intl.cloud.tencent.com/product/waf
Vendor Details
Company Name
open-appsec
Founded
2022
Country
Israel
Website
www.openappsec.io
Product Features
Web Application Firewalls (WAF)
Access Control / Permissions
Alerts / Notifications
Automate and Orchestrate Security
Automated Attack Detection
DDoS Protection
Dashboard
IP Reputation Checking
Managed Rules
OWASP Protection
Reporting / Analytics
Secure App Delivery
Server Cloaking
Virtual Patching
Zero-Day Attack Prevention
Product Features
Application Security
Analytics / Reporting
Open Source Component Monitoring
Source Code Analysis
Third-Party Tools Integration
Training Resources
Vulnerability Detection
Vulnerability Remediation
Web Application Firewalls (WAF)
Access Control / Permissions
Alerts / Notifications
Automate and Orchestrate Security
Automated Attack Detection
DDoS Protection
Dashboard
IP Reputation Checking
Managed Rules
OWASP Protection
Reporting / Analytics
Secure App Delivery
Server Cloaking
Virtual Patching
Zero-Day Attack Prevention