Lacework®, the data-driven cloud security company, today announced new capabilities that enable organisations to uncover more critical threats to their infrastructure and empower teams to collaborate more efficiently in alert investigation and response.
Lacework has added fully automated time series modeling to the existing anomaly detection capabilities of the Polygraph® Data Platform.
Using automated learning and behavioural analytics, the time series model builds a baseline of the volume and frequency of activity within a customer’s environment and actively monitors for spikes that deviate from that unique baseline to detect potential threats such as cryptominer attacks and compromised accounts with accuracy.
Organisations can also proactively discover increased cloud usage due to misconfigurations — gaining a better understanding of their environment to help control costs.
Lacework does this without the need for constant tuning of thresholds, significantly reducing both manual work and false positive alerts. Lacework has also upgraded its alerting experience with features that empower teams to collaborate more efficiently in alert investigation and response.
The enormous amount of activity in the cloud and adoption of new technology makes it difficult to gain visibility into risks, investigate alerts efficiently, and take action, especially when teams are siloed into different workstreams and tools.
Signature and rules-based approaches can’t keep pace with this dynamic environment and often overwhelm security teams with thousands of contextless alerts across a range of environments.
Polygraph, the Lacework cloud behavioral analytics engine, uses dozens of models to build a baseline of normal behaviors in the cloud.
The time series model introduces a new dimension of analysis by tracking changes in activity frequency and volume over time in a cloud environment. It works with the existing models to uncover more anomalies with fewer alerts.
Lacework also automatically adjusts the severity of alerts based on continuous learning and a fine-grained understanding of how much the observed behaviours deviate from the predicted baseline for improved accuracy.
According to Cybersecurity Ventures, the number of unfilled cybersecurity jobs worldwide grew by 350% between 2013 and 2021 with no sign of relief in the next five years.
By consolidating alerts into only those that matter and providing security teams with more context about what is happening across their environment, Lacework allows these overburdened teams to uncover more risks and deal with them more efficiently.
Frank Dickson, IDC Group Vice President, Security and Trust said “It’s critical organisations get transparency as to what is happening across their multicloud environments, but security teams face a massive challenge keeping up with the dynamic nature of cloud environments while threats like cryptomining continue to proliferate,”
“As an industry plagued by a seemingly insurmountable skills shortage, simply layering more alerts on the SOC does not help. Context matters; context quickly forwards SOC investigations from awareness to understanding by enabling correlations across datasets.”
Alerts are thus replaced with context rich incidents that are quickly actionable and facilitate outcomes for customers. In the end, secure outcomes are the goal of every SOC.” said Dickson
Lacework has also revamped the alerting experience to help organisations better collaborate with teams to prioritise, investigate, and track the status of all alerts. This includes:
- Context-rich insights: Richer insights give the complete picture of what happened, associated events, timelines, and other details, helping organisations understand where to focus and make better decisions.
- Configurable bi-directional sync: When teams update an alert on the Lacework user interface or the associated ticket in backend workflow tools like Jira, the alert status is automatically updated on both sides with bi-directional sync for accelerated resolution. Organisations can even give feedback on Lacework alert severity levels, which in turn helps the Polygraph Data Platform learn and optimise modeling to further improve alerting experience.
- Easy to manage alert lifecycle: Teams can more easily organise alerts, view tags, filter to see a set of specific alerts, change the state of an alert to indicate whether it needs to be investigated or has been resolved, and add comments to classify and better collaborate with teams.
Arash Nikkar, VP of Engineering, Lacework said, “Lacework relentlessly innovates to deliver features that help customers gain the visibility and controls they need to stay ahead of the evolving threat landscape,”
“The Polygraph Data Platform is the only cloud security solution to combine automated time series analysis with sophisticated cloud behavioural analytics to build baselines that are tailored to a company’s unique environment.”
“Combined with our enhanced alerting capabilities, we’re making it easier for teams to identify relevant risks and prioritise threats, even as their organisation scales, the attack surface grows bigger, and security incidents increase exponentially, Nikkar
Time series modeling is available now for Lacework customers in AWS environments. Configurable bi-directional sync enhancements to the Lacework alerting experience are available to select customers in beta.
