Malware is one of the most common causes of endpoint compromise. Various types of malware such as Trojans, Worms, and Botnets are used by cybercriminals to infect devices and launch attacks.
Malware activities include:
More alarmingly, Zero-Day Malware and Ransomware have the potential to cause massive financial and operational damage, and their unpredictable nature makes them particularly worrisome for industries globally.
Endpoints outside organizational firewall are often unguarded against malicious websites or torrent-based activities that invite malware.
Evasive techniques, including obfuscation, encryption, and stealth mode, make malware detection significantly more challenging.
Evolution of known vectors over time renders futility to previous tried defenses, signatures and heuristic-based detection techniques.
Behavioral detection across endpoints, memory and the network finds unknown and fileless malware, then contains it automatically.
Behavioral EDR
Behavioral detection from day one, with process chain analysis that follows every step a threat takes.
Illustrative example.
Memory analysis
Memory forensics catches threats that never touch the disk.
Ransomware
Flags mass file-encryption behavior before the payload spreads.
Potential Ransomware in Progress alert
Built-in alerts
Threat intelligence
IOCs from 100+ sources, plus DGA prediction for malware such as WannaCry, Conficker and Ramnit
Automated response
70% automated response rate through native SOAR.
Investigation
Full attack chain reconstruction, with built-in file integrity monitoring that records file creation, modification and deletion.
Works with what you have
aiXDR-PMax integrates with existing EDR tools, so their telemetry correlates with network, identity and cloud data.
Lightweight agent
Under 1% idle CPU on Windows, macOS and Linux, deployable through AWS SSM, Azure VM Extension, GCP OS Config or Kubernetes.
Explore how AI-powered malware detection helps identify evolving threats, detect suspicious behavior, and support faster incident response with Seceon.
Traditional antivirus software often relies on known malware signatures, which can make unfamiliar or modified threats harder to detect. Businesses can strengthen detection by monitoring suspicious processes, file changes, user activity, and network connections alongside threat intelligence.
Seceon uses AI/ML-driven behavioral analysis through its aiSIEM and aiXDR solutions to help identify suspicious activity associated with unknown malware and evolving threats. Detection depends on the telemetry available and deployment configuration.
Businesses should evaluate malware detection solutions based on behavioral analytics, threat intelligence, endpoint and network visibility, incident investigation, response automation, integration support, and scalability. The ability to correlate related events is particularly important when malware activity spans multiple systems.
Seceon's OTM (Open Threat Management) Platform brings together aiSIEM and aiXDR to correlate security events, analyze behavioral patterns, and support threat detection and response. Businesses should assess product capabilities and integrations against their specific security requirements.
Zero-day malware may evade defenses that depend on previously known signatures. Organizations can improve detection by monitoring behavioral anomalies, suspicious process execution, unexpected file changes, and unusual network connections instead of relying exclusively on known malware indicators.
Seceon uses AI/ML-based behavioral analysis and Dynamic Threat Models through its aiSIEM and aiXDR solutions to help identify zero-day threats and advanced evasive activity. No security solution can guarantee detection of every zero-day attack before damage occurs.
Security teams should monitor unusual file modifications, suspicious process activity, abnormal network connections, and lateral movement between systems. When ransomware activity is detected, isolating affected endpoints and stopping malicious processes can help limit its spread.
Seceon combines aiSIEM event correlation with aiXDR endpoint detection and response capabilities. Depending on the deployed integrations and configuration, response actions can include endpoint isolation, stopping malicious processes, and quarantining malicious files.
Fileless malware can operate through system memory, scripts, or legitimate administrative tools, making file-signature scanning alone insufficient. Detecting these threats requires analyzing process execution, process relationships, scripts, and network activity for suspicious behavior.
Seceon aiXDR supports behavioral detection and endpoint telemetry analysis to help identify suspicious process activity and evasive techniques. Combined with aiSIEM, these capabilities help security teams correlate endpoint signals with other events to investigate potential threats. Detection coverage depends on the telemetry and features enabled in the deployment.
Malware detection software can automate selected response actions when configured rules or response policies identify a qualifying threat. Actions may include isolating an affected endpoint, stopping a malicious process, or quarantining a malicious file. Complex incidents may still require investigation and analyst approval.
Seceon aiXDR supports endpoint containment and remediation, while aiSIEM helps correlate events and investigate threats. Security teams can determine the appropriate level of automation based on their risk tolerance, integrations, and response policies.
Seceon’s AI-driven solution detects and prevents malware by analyzing system behavior, identifying malicious activity in real-time, and automatically blocking threats to ensure strong protection against malware infections and system compromise.
