Early Detection of Advanced Persistent Threats
Threat intelligence and signature based defenses are proving ineffective at stopping today's advanced cyber criminals. If your organization is a likely target, you should be operating on the assumption that you have already been hacked.
But even the most advanced criminals leave fingerprints in the form of unusual software connecting to networks, anomalous access and abnormal data traffic patterns. The problem is that it is not possible to invest the time needed to find these activities using traditional rule or signature based approaches.
That's where Anomaly Detective comes in. Machine learning algorithms automatically determine normal behavior patterns for hundreds of thousands of data points. Automated anomaly detection provides early detection of the suspicious behavior patterns that security analysts need to know about. Forensic analysis times are slashed. And the result is you see threats as they develop and stop them dead in their tracks.
Detect Rogue Users By Analyzing Netstat Data
- Scan your entire network in real-time for any host making network connections with new or unusual software
- Drill down to the forensic detail you need to make fast decisions
- Resolve threats before data exfiltration begins
Identify Attacking IP's By Analyzing Web Server Logs
- Spot outliers from normal behaviors along multiple dimensions like source, destination, time of day, data tranmission rates, etc.
- Find the unusual authorized access patterns that could indicate intrusion attempts
- Get the evidence you need as it is happening
Find Important IDS Events By Analyzing IDS Logs
- Stop letting attackers mask their activity in the noise of your IDS/IPS alerts
- Turn thousands of high severity alerts a day into a dozen important notifications a week
- Get real-time notification of developing attacks
Identify Attacking IP's By Analyzing ipTables Firewall Logs
- See how we handled a Honeynet Project firewall log analysis challenge
- In minutes, we flagged unusual port scan and connection attempts without rules or signatures
Identify Data Exfiltration By Analyzing NetFlow Logs
- You can't hide from NetFlow - changes to the norm can signal a compromised host
- Any deviations over time are flagged - whether small or large amounts of data
- Detect the earliest signs of a threat