TRUEFORT SOLUTION
Enterprise-grade Ransomware Protection Software
Threat actors and cybercriminals have grown more capable, frequent, and successful in ransomware attacks. Entering via a vulnerability and moving undetected, exploiting user credentials, legacy systems, and misconfigurations, ransomware spreads at will. TrueFort isolates ransomware from reaching critical workloads by only allowing previously understood application and workload behavior.
Detect initial ransomware compromise before it spreads.
- Slow, meaningless detection – Ransomware doesn’t mind if you detect it. It often announces itself after spreading broadly across the entire environment in a few minutes.
- Complex application and workload environments – Organizations are challenged with understanding what constitutes normal application activity including communications Between them, processes that execute, and the service accounts running privileged commands.
- Vulnerable, unsupported systems – Legacy systems are inherited, acquired, or minimally supported and often forgotten until they are encrypted to cause an outage.
The race to detect and stop before devastation
Understand relationships
Discover and map the full environment to understand relationships between applications, workloads, and service accounts while verifying that cross-communications are valid and acceptable by generating an application baseline
Hardened systems
Implement CIS benchmarks and best practice file configurations to prevent unauthorized changes that make workloads more vulnerable to the tools ransomware uses to automatically spread
Prevention of unnecessary actions
Use approved baselines of workload behavior to enforce policies that block unknown malicious behavior before it’s known to threat intelligence
Automate enforcement
Block unauthorized network connections between applications, disable incorrectly used privileged accounts, or kill unknown processes as they execute to minimize the blast radius
FAQ
Microsegmentation is a security approach which helps administrators implement the principle of least privilege and Zero Trust for individual workloads. Instead of applying one policy to an entire network or data center, microsegmentation allows security to manage traffic between workloads or applications within a network. Security policies deny user requests by default unless they present the right credentials for the specific data they’re trying to access.
Microsegmentation may be used to isolate workloads in development, testing, and production, manage connections to specific applications, limit application visibility by user, user group, or tier, and apply fine-grained controls to specific software services and processes.
Microsegmentation plays an important role in reducing an organization’s attack surface because it gives security teams control over what lateral movement to permit in any environment. With this control, experts can monitor lateral movement against predefined security policies or against a model of expected application behavior, which improves the speed of detection, response, and remediation.
Microsegmentation makes it possible to implement granular control of network communications, credential usage, and approved behavior to help organizations minimize the impact of a cyber security incident, and solutions with automated application discovery will simplify security management even as networks grow increasingly complex.
Microsegmentation doesn’t require a new architecture for implementation. Security teams can deploy an agent-based solution which leverages software existing agents on the workload to isolate individual hosts and containers. Solutions can apply security policies based on physical and virtual devices, including load-balancers, switches, or software-defined networks. Some cloud service providers also offer microsegmentation capabilities.
Organizations will typically deploy both agent-based and network device models to handle all environments, including public or private cloud and on-premises networks. Solutions will use the visibility microsegmentation provides and data analytics to develop a model of normal network behavior against which anomalous events stand out for fast detection and response.
