Tuning Microsoft Sentinel and Defender

Tuning False Positive Alerts

Combat alert fatigue by automatically removing false positive alerts. 

No more alert fatigue

Decrease alert handling time with AI/ML

The average handling time of a false positive alert is 32 minutes. By tuning false positives, you save 32 minutes per false positive alert. Tune Microsoft Sentinel with advanced machine learning to gain more time for in-depth threat analysis and reduce alert fatigue.

As we are not using static, fixed rules, the algorithm is agnostic to changed data schemes. If you use fixed rules or playbooks, you would have to change them every time

Adding enrichment to alert improves the efficiency of the ML/AI tuning algorithm because it adds more context

You algorithm is improved as we use anonymized data from other clients to tweak the algorithm. Then launched attacks across different sectors or customers are more easy discovered

Minimize false positive alerts

Automatically tune Microsoft Sentinel alert rules

Leveraging open data sources and threat intelligence, Seculyze machine learning surveys your threat landscape for new alerts. Based on similarities between incoming alerts, you are automatically recommended tuning rules that identify the real threats while tuning-out false positives.

Spend less time analyzing false positives and save resources for the critical alerts that require your full attention.

Read how we tune
Simple asssembly

Automatic or manual tuning: Your call

Leverage machine learning-generated recommendations to fine-tune your alert rules. Based on our best practice recommendations, you decide if the software automatically tunes out the alert or you do it manually with a simple click. You can choose to manually decide on a time frame for running the rule and its severity.

Read about control functions