Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Be aware of the indicators that suggest privileged account misuse. Notable signs include a sudden surge in access to privileged accounts by specific users or systems, unusual patterns of access to the most sensitive accounts or secrets, multiple privileged accounts being accessed simultaneously, and logins occurring at odd hours or from unexpected locations. Utilizing Privileged Behavior Analytics can effectively identify these irregularities and promptly notify your security team of a potential cyber threat or insider risk before a major breach occurs. With the help of Delinea's Privileged Behavior Analytics, which employs sophisticated machine learning techniques, you can monitor privileged account activities in real-time to detect anomalies and generate threat assessments along with customizable alerts. This advanced technology scrutinizes all actions associated with privileged accounts, allowing you to recognize issues and evaluate the severity of a potential breach. By enhancing security measures, your organization can significantly lower security risks, ultimately saving your department valuable time, resources, and money while optimizing the investment you have already made in security solutions. Additionally, staying vigilant about these warning signs fosters a culture of cybersecurity awareness within your organization.
Description
Protecting against unseen dangers through user and entity behavior analytics is essential. This approach uncovers irregularities and hidden threats that conventional security measures often overlook. By automating the integration of numerous anomalies into a cohesive threat, security analysts can work more efficiently. Leverage advanced investigative features and robust behavioral baselines applicable to any entity, anomaly, or threat. Employ machine learning to automate threat detection, allowing for a more focused approach to hunting with high-fidelity, behavior-based alerts that facilitate prompt review and resolution. Quickly pinpoint anomalous entities without the need for human intervention. With a diverse array of over 65 anomaly types and more than 25 threat classifications spanning users, accounts, devices, and applications, organizations maximize their ability to identify and address threats and anomalies. This combination of human insight and machine intelligence empowers businesses to enhance their security posture significantly. Ultimately, the integration of these advanced capabilities leads to a more resilient and proactive defense against evolving threats.
API Access
Has API
No
API Access
Has API
No
Integrations
Accenture Cloud Retail Execution
No
Amazon API Gateway
No
Amazon Ads
No
Amazon S3
No
Amazon SES
No
Amazon Simple Notification Service (SNS)
No
Amazon SimpleDB
No
Amazon Sumerian
No
Booz Allen MDR
No
Cisco AnyConnect
No
Integrations
Accenture Cloud Retail Execution
Yes
Amazon API Gateway
Yes
Amazon Ads
Yes
Amazon S3
Yes
Amazon SES
Yes
Amazon Simple Notification Service (SNS)
Yes
Amazon SimpleDB
Yes
Amazon Sumerian
Yes
Booz Allen MDR
Yes
Cisco AnyConnect
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Delinea
Country
United States
Website
delinea.com/products/privileged-behavior-analytics
Vendor Details
Company Name
Cisco
Founded
1984
Country
United States
Website
www.splunk.com/en_us/products/user-behavior-analytics.html