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What is HookProbe?

HookProbe represents a cutting-edge open-source intrusion detection and prevention system (IDS/IPS) tailored for deployment on Raspberry Pi and edge computing devices. By utilizing eBPF/XDP for kernel-level packet filtration alongside sophisticated machine learning techniques for classifying threats, it offers a comprehensive network security solution that operates independently of cloud infrastructures. Within its architecture, components such as NAPSE, which conducts AI-enhanced packet scrutiny; HYDRA, overseeing the threat intelligence flow; SENTINEL, acting as the engine for machine learning classification; and AEGIS, which coordinates self-sufficient defense strategies, work in concert. Impressively, a single Raspberry Pi 5 can efficiently process over 11 million security events, accurately classify 177,000 machine learning assessments, and track more than 11,800 attacker IP addresses, all without the need for human oversight. Key features include: - An extremely swift installation process that takes just five minutes on a Raspberry Pi 5 or any compatible Linux device - Rapid packet filtering and protection against DDoS attacks utilizing eBPF/XDP - Threat classification driven by machine learning that sorts incidents into benign, suspicious, or malicious categories - Instant evaluation of security posture through QSecBit scoring - An intuitive web dashboard that allows for real-time visualization of threats - Adoption of post-quantum cryptography standards, specifically Kyber KEM - A cooperative mesh defense system that enhances security across multiple interconnected nodes. These diverse capabilities ensure that HookProbe not only provides a resilient and flexible security solution but also meets the evolving demands of contemporary network environments, making it an essential tool for safeguarding digital assets.

What is Cryptomage?

Threat detection involves a meticulous analysis of each network packet and its data, which includes identifying and verifying network protocols to uncover both hidden and obscure ones. It utilizes machine learning methodologies that enable a forward-looking evaluation of traffic risk, employing scoring systems to quantify potential threats. The identification of network steganography plays a crucial role in detecting concealed traffic within the network, potentially revealing data breaches, espionage, and botnet activities. By applying specialized algorithms for detecting steganography, this approach effectively exposes various strategies used to hide information. In addition, a distinctive database filled with a wide range of known steganography techniques significantly boosts detection efficacy. Forensic analysis is employed to assess the ratio of security incidents in relation to their traffic origins, providing valuable insights. This also aids in isolating high-risk network traffic for targeted analysis based on specific threat levels, and storing the metadata from processed traffic in an extended format further streamlines the trend analysis process. Overall, this comprehensive strategy not only deepens the understanding of network security issues but also improves the responsiveness to new and evolving threats, ensuring that organizations remain vigilant and prepared.

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Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

$9/month
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

HookProbe

Date Founded

2022

Company Location

Romania

Company Website

hookprobe.com

Company Facts

Organization Name

Cryptomage

Date Founded

2015

Company Location

Poland

Company Website

cryptomage.io/cybereye

Categories and Features

Categories and Features

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