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What is PentenAmio?
CBG Deception is an AI-powered cyber deception and threat engagement platform developed by PentenAmio for organizations protecting sensitive networks, critical infrastructure, and government systems. The software uses artificial intelligence to accelerate the creation of realistic decoy networks that attract, divert, and expose sophisticated cyber adversaries. Unlike conventional honeypots that primarily simulate individual systems or services, CBG Deception generates interconnected digital environments containing realistic users, documents, communications, and operational activities. Its Content and Behaviour Generator creates artificial personas with defined characteristics and patterns of life that resemble legitimate activity within an organization. Simulated users interact with applications and network resources by sending emails, reading documents, editing files, making calls, and communicating with other users. These activities provide contextual realism intended to make decoy environments more convincing to attackers investigating compromised networks. Intelligent workflow tools guide security teams through designing deception environments, configuring attack paths, planning scenarios, and deploying simulated infrastructure. The platform allows organizations to tailor digital artifacts, user behaviors, environmental characteristics, and deception objectives to their operational requirements. Its automated generation capabilities reduce the time and resources needed to construct realistic deception environments compared with manual configuration. CBG Deception can operate through cloud-based or on-premises deployments and integrates with supported third-party deception platforms to complement existing security operations.
What is Fidelis Elevate?
If you lack visibility, you cannot safeguard your assets effectively. The Fidelis Elevateâ„¢ XDR solution empowers you to: achieve comprehensive oversight of network traffic, email communications, web interactions, endpoint behaviors, and enterprise IoT devices; swiftly identify, thwart, and react to adversarial actions and sophisticated threats; correlate attacker tactics, techniques, and procedures (TTPs) with the MITRE ATT&CKâ„¢ framework to anticipate the adversary's subsequent moves and respond accordingly. By leveraging machine learning, it provides robust indicators regarding advanced threats and potential zero-day vulnerabilities, enabling you to tackle these issues proactively before they escalate. Furthermore, Fidelis Elevate XDR automates the validation and correlation of network detection alerts across all managed endpoints in your environment, allowing you to minimize false positives while focusing your attention on the most critical alerts. Additionally, it monitors north-south traffic, potential data exfiltration, and lateral movements within the network to enhance overall security. With such comprehensive capabilities, organizations can better protect their digital assets.
Integrations Supported
API Availability
API Availability
Pricing Information
Pricing not provided
Pricing Information
Pricing not provided
Free Trial Offered?
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
Web-Based Support
Training Options
Documentation Hub
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
Company Facts
Organization Name
PentenAmio
Date Founded
2014
Company Location
Australia
Company Website
pentenamio.com/ai-cyber-defence/
Company Facts
Organization Name
Fidelis Security
Date Founded
2002
Company Location
United States
Company Website
fidelissecurity.com/fidelis-elevate-extended-detection-and-response-xdr-platform/
Categories and Features
Deception Technology
Not specified
Categories and Features
Cyber Resilience
Not specified
Deception Technology
Not specified
Endpoint Detection and Response (EDR)
Not specified
Extended Detection and Response (XDR)
Not specified
Network Detection and Response (NDR)
Not specified