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Unified discovery, response, and analysis powered by artificial intelligence
Advanced Endpoint Detection and Response (EDR) certification from the AV-TEST institute, Germany
The Padvish XDR AI system is an advanced solution for organizations that require comprehensive oversight of client security, servers, and network equipment, and wish to identify hidden threats within the organization's digital space.
Padvish XDR AI detects complex infiltrations in real-time by utilizing proprietary artificial intelligence. By analyzing memory and continuously monitoring behaviors, this system prevents data destruction and tracks Indicators of Compromise (IOCs).
The Padvish XDR AI system enables the use of sandboxing, machine learning analysis, and an IPS. With its network sensors and intelligent assistant, this system accelerates threat hunting and executes immediate corrective actions.
With the Padvish XDR AI system, no security threat remains hidden in your organization's network.
Padvish CyberGPT™ is the first Large Language Model (LLM) designed specifically for the cybersecurity domain. Developed with a combination of proven and emerging AI technologies, this model is not just a powerful text processing tool, but an intelligent security assistant capable of understanding, analyzing, and responding to complex cyber challenges.
In the design of Padvish CyberGPT™, organizational needs were considered with a realistic perspective on technical limitations and the current knowledge level of the security market.
Developed by Amnpardaz Software Company, this system provides a secure foundation for organizations to leverage AI for faster decision-making, threat analysis, and incident response.
Beyond a simple technology, Padvish CyberGPT™ is a starting point for organizations to adopt the next generation of security systems.
Detects and responds rapidly to Indicators of Compromise (IOCs), such as malicious file hashes and sequences of malicious code.
Analyzes and monitors cyberattacks and processes running in the system memory.
Monitors and analyzes system process behavior using various sensors and detects cyberattacks by identifying unusual patterns.
Utilizes machine learning algorithms to detect security threats, behavioral deviations, and suspicious code.
Detects and protects against network-based intrusions and exploits (such as Log4j and ZeroLogon).
Executes suspicious files in an isolated environment to analyze and monitor their behavior.
By examining raw traffic packets across the network, this sensor identifies attacks originating from unprotected endpoints or areas outside the scope of monitored assets.
Examines files to detect security threats, Indicators of Compromise (IoCs), or obfuscation techniques and determines their static characteristics.
An AI-powered assistant that summarizes suspicious activities, analyzes complex scripts, and generates threat hunting (search) queries.
Integrates multiple antivirus engines to increase threat detection accuracy.
Detects and responds rapidly to Indicators of Compromise (IOCs), such as malicious file hashes and sequences of malicious code.
Analyzes and monitors cyberattacks and processes running in the system memory.
Monitors and analyzes system process behavior using various sensors and detects cyberattacks by identifying unusual patterns.
Utilizes machine learning algorithms to detect security threats, behavioral deviations, and suspicious code.
Detects and protects against network-based intrusions and exploits (such as Log4j and ZeroLogon).
Executes suspicious files in an isolated environment to analyze and monitor their behavior.
By examining raw traffic packets across the network, this sensor identifies attacks originating from unprotected endpoints or areas outside the scope of monitored assets.
Examines files to detect security threats, Indicators of Compromise (IoCs), or obfuscation techniques and determines their static characteristics.
An AI-powered assistant that summarizes suspicious activities, analyzes complex scripts, and generates threat hunting (search) queries.
Integrates multiple antivirus engines to increase threat detection accuracy.
Aggregates telemetry data from various layers (beyond endpoints) for complete threat visibility.
Allows security teams to focus on high-priority incidents.
Uses AI to correlate data from multiple sources, reducing false positives and increasing detection accuracy.
Addresses the shortage of security specialists and counters rapidly changing threats.
Reduces Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR).
Enhances complex threat detection power using AI and machine learning to provide faster and smarter responses.
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