TRUEFORT SOLUTION
Mitigating Software Supply Chain Attacks
Using third-party code (the software supply chain) in enterprise applications has made products vulnerable to attack. Cybersecurity incidents can occur, forcing security teams to re-evaluate their applications, including the supply chain software within their code. TrueFort limits these incidents by continuously discovering and understanding the application interactions and workload behaviors to detect changes quickly.
Malicious Third-Party Code is Larger Than You Think
- Zero-day attacks are continually morphing – Relying on existing tools like code signing certificates and known bad detection methods, indicators of attack (IOA), and indicators of compromise (IOC), are not stopping supply chain attacks.
- Network-centric tools are easily thwarted – attackers understand how to avoid detection from these tools easily by not crossing a perimeter.
- Service accounts are easy-to-access points – Unchecked and rogue service accounts provide a seamless path for lateral movement.
- Software updates may contain supply chain vulnerabilities – Understanding application and automated account behavior quickly enables the detection of anomalous activity as it emerges from supply chain code.
Automate Understanding Application Behaviors to Block Exposure
Achieve intra-application visibility
Achieve intra-application visibility: Identify and map applications, their dependencies, and communications within to immediately spot anomalous behavior indicating exploited supply chain software
Establish normal and acceptable
Understand workload activity and enforce acceptable behavior to defend against software supply chain vulnerabilities that enable the spread of larger attacks
Analyze changing behaviors
Real-time detection for workloads against an application behavior baseline provides the best approach for detecting threats that bypass traditional snapshot cloud security methods
Limit blast radius
Prevent an intrusion from becoming a breach by enforcing microsegmentation policies based on known behavior
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.
