IDatAlert monitors enterprise assets for suspicious activity and unusual behaviour, detecting critical events and compromised assets on your core infrastructure: Windows, UNIX/Linux, NAS, Active Directory, SharePoint, Exchange and Office 365.

Detect insider threats and cyber threats by analysing data, account activity and user behaviour. Automate responses to suspicious activity and alert on unusual behaviour – using deep analysis of metadata, machine learning and advanced User Behaviour Analytics (UBA) 

DatAlert establishes a baseline of normal activity for user, executive, administrator and service accounts. We use those behavioural baselines to flag suspicious activity so that you can investigate potential security issues before it’s too late.

DatAlert gives you insight into the behaviour and activity of your users: including peer analysis, working hours, device insight, data access, and more – and makes it easy for the right people and systems to get notified about the right things, at the right times, in the right ways.

DatAlert’s web UI makes it easy to spot threats to your data: who are behaving suspiciously, which data assets are threatened, and where you might be compromised by ransomware. Use a configurable web-based dashboard where you can easily identify and prioritize at-risk areas like global access, stale data, and overexposed sensitive information.

See if your data is under attack, and where to investigate and take action.

“Cryptolocker is a huge security threat, so having Varonis DatAlert in place to help prevent attacks is a no brainer for us. When anyone from the outside tries to encrypt a file on the network or use a compression tool like WinZip, DatAlert will let us know. Also, we can receive alerts about suspicious internal activity.

It’s nice to know Varonis is looking out for us and will be able to catch things and help us proactively prevent internal and external data breaches.”

– Jim Hanlon | SVP & CTO, Dedham Savings Bank

Varonis Threat Models utilize thresholds, statistical analysis and machine learning to trigger alerts on what looks unusual and uncover potential security issues. These threat models automate threat detection by identifying specific behaviours and actions: known malware behaviour, abnormal access to sensitive files, suspicious membership changes, unusual lockout activities, modifications to critical GPOs, crypto intrusion activity and much more.

Our professional behaviour research laboratory – comprised of security experts and data scientists – consistently introduces new threat models to DatAlert on a regular basis, while staying up-to-date with the latest in security issues, APTs, and insider threats.

DatAlert Analytics Rewind allows customers with 3 or more months of data to analyze past user and data activity with DatAlert Analytics threat models, and identify alerts that you would have gotten in the past. Pre-emptively tune out false positives and look back at your history to identify breaches that may have already occurred.