Clear visibility across your data environment. See results, their importance, and next steps.
Automation combines known attacker techniques with machine learning to identify data access.
Reduce manual effort and boost security team productivity with accurate and appropriate threat context.
Identifying insider threats is harder than ever
Internal users have legitimate access to valuable information; cybercriminals leverage valid accounts through exploitation of system weaknesses, misconfiguration and vulnerabilities. Threats can come from anywhere and organizations must be prepared to respond.
Privilege misuse is common to successful attacks
Threat context is important
Overwhelmed by excessive alerts, incident response teams require intelligent tools to aid the manual evaluation of low severity events and prioritize response efforts.
IT security teams need force multipliers
Organizations need to differentiate between appropriate data access and an insider threat incident. Automation enables focus on events that require human interpretation.
More applications, more paths to data
Firms struggle with solutions that don’t allow for an increased number of applications and the exponential growth of data found in most organizations.
Risk-based analytics and automation increase accuracy
Adopting a risk-based methodology to your digital protection allows evaluation of data according to your organization’s risk profile and priorities, reducing the likelihood of a breach. User data access activity should be consistent across all environments.
Trust, but verify and track
Database activity monitoring detects suspicious commands and access patterns. Businesses need to log historical records for future evaluation and auditing.
Prioritizing the handling of incidents is critical
Even small improvements in accuracy can multiply incident response effectiveness. Automated prioritization of high-risk incidents allows security teams to stay focused.
Less noise, for more signal
Context is essential to decision making. Effective data risk mitigation requires advanced security analytics to help security staff pivot from one issue to the next.
What happened and was it important?
44% of companies are blind to data activity and need to see data across the entire enterprise to monitor which sensitive data is being used and accessed, and by whom.
Automate discovery of non-compliant, risky, and malicious data access behavior anywhere
Analyze user behavior and data access activities to accurately identify threats. Quickly understand critical, high, medium and low incidents, the users associated with them, and the data accessed.
Answer prioritization challenges
Incidents are automatically assigned a risk score that includes sensitive data volume, privileged account, and prevalence.
Boost effectiveness and team confidence
Empower incident response teams through strong tools, and reduce repetitive tasks.
Simple risk indication
Threat intelligence platforms and SIEMs can leverage new data access behaviour context during event enrichment.
How Imperva helps against insider threats
Database Risk and Compliance
Reduce exposure to insider threats by remediating vulnerabilities and protecting sensitive data.
Data User Behavior Analytics
Detect compromised accounts and malicious insiders as soon as behavior changes.
Cloud Data Security
Prevent unwanted insider access to the data moved to the cloud.