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Mitigating malicious data activity

Cybersecurity needs 24x7x365 vigilance and constant adaptation to keep pace with threats. Organizations focusing on indicators of compromise (IoC) from the perimeter, network, and endpoint may be blind to malicious activity at the end of the attack chain -- data access. To be resilient, companies need to protect the data itself.

Database expertise

Imperva monitors over 60 database software versions, on-premise and cloud.

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15-year data security leader

An industry pioneer; activity monitoring, data user behavior analytics, and more.

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Event enrichment

Relentless focus on actionable facts; breach categorization, data type and more.

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Advanced attacks are more common

Tycoon, REvil, application-level attacks, and supply chain compromise are threats that share a common goal - data. Monitoring raw data activity can overload even the most mature IT security or incident response teams.

Advanced attacks mobile
  • SOC teams need insight, not more raw events

    Alert volume is a constant challenge for incident responders. Security teams need useful insight that complements threat detection pipelines and trims workflows.

  • A lack of relevant metrics

    Teams need to be measuring activity they can act upon. Organizations often struggle to understand risk posture using existing data sources.

  • Too many security toolsets

    Organizations use too many security tools, some not integrated nor maintained, which slows response times by increasing manual work, introducing errors.

  • A reliance on native audit capabilities

    Native audit tools push the burden of discovery and classification downstream, where important insights can be lost due to lack of database-specific fidelity and volume.

Advanced attacks are more common

Tycoon, REvil, application-level attacks, and supply chain compromise are threats that share a common goal - data. Monitoring raw data activity can overload even the most mature IT security or incident response teams.

  • SOC teams need insight, not more raw events

    Alert volume is a constant challenge for incident responders. Security teams need useful insight that complements threat detection pipelines and trims workflows.

  • A lack of relevant metrics

    Teams need to be measuring activity they can act upon. Organizations often struggle to understand risk posture using existing data sources.

  • Too many security toolsets

    Organizations use too many security tools, some not integrated nor maintained, which slows response times by increasing manual work, introducing errors.

  • A reliance on native audit capabilities

    Native audit tools push the burden of discovery and classification downstream, where important insights can be lost due to lack of database-specific fidelity and volume.

Reduce time to action and increase team effectiveness

Respond to modern threats efficiently using a minimal set of tools, optimized for the environment. Layering contextual insight into the threat detection pipeline facilitates discovery, classification, detection, and response.

Reduced time to action mobile
  • Automate data discovery and classification

    Data classification is elemental to an efficient data security program, but is difficult to manually maintain across on-premise and cloud data stores.

  • Build actionable intelligence

    Inject meaningful threat intelligence into layered defense models. Without context, teams make decisions with vague information, or are delayed while they augment manually.

  • Increase resilience through consolidation

    Reduce the number of security tools to those with force multiplier capabilities. Fewer intelligence sources and meaningful insight reduce complexity and increase resilience.

  • Expand scope to include indicators of attack

    Increase visibility to malicious data activity, lower false positives, and reduce remediation time by adding insight into indicators of attack (IoA) at the data level.

Reduce time to action and increase team effectiveness

Respond to modern threats efficiently using a minimal set of tools, optimized for the environment. Layering contextual insight into the threat detection pipeline facilitates discovery, classification, detection, and response.

  • Automate data discovery and classification

    Data classification is elemental to an efficient data security program, but is difficult to manually maintain across on-premise and cloud data stores.

  • Build actionable intelligence

    Inject meaningful threat intelligence into layered defense models. Without context, teams make decisions with vague information, or are delayed while they augment manually.

  • Increase resilience through consolidation

    Reduce the number of security tools to those with force multiplier capabilities. Fewer intelligence sources and meaningful insight reduce complexity and increase resilience.

  • Expand scope to include indicators of attack

    Increase visibility to malicious data activity, lower false positives, and reduce remediation time by adding insight into indicators of attack (IoA) at the data level.

Contain malicious data activities and boost workflows

Force multiplier for the team

Reduce the number of low volume security tickets and amplify effectiveness.

Add clarity, not ambiguity

Use actionable insight to improve security posture and inform business leaders.

Foundational tooling

Data-centric security tooling, tuned for your workloads, with broad interoperability.

How Imperva can Help You Prevent Malicious Activities

Database Risk and Compliance

Database Risk & Compliance

Integrate with any database to implement universal policies and speed time to value.

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Data User Behavior Security Analytics 1

Data User Behavior Analytics

Automate detection of non-compliant, risky, or malicious data access behavior.

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Secure Cloud shopping

Cloud Data Security

Security and compliance for Amazon RDS, Amazon Redshift or Azure SQL Server database environments.

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