The connection between detection and response (DR) practices and cloud security has historically been tenuous. As businesses worldwide increasingly transition to cloud-based environments, security strategies have predominantly centered on “shift-left” methodologies—prioritizing secure code, maintaining proper cloud configurations, and rectifying misconfigurations. This focus has inadvertently fostered a dependence on a broad array of DR tools intended for cloud infrastructure, workloads, and applications. Despite these sophisticated tools, organizations frequently face delays of weeks, or even months, in identifying and rectifying incidents.
The complications of tool sprawl, escalating cloud security expenditures, and the inundation of false positives have compounded the challenges faced by security teams. Many organizations are left contemplating which cloud breaches they can realistically counteract. To bolster their real-time detection and response capabilities against cloud attacks, security teams are encouraged to implement five strategic steps.
Step 1: Enhance Runtime Visibility and Protection
Without real-time visibility, security teams operate in a reactive mode, struggling to respond effectively to emerging threats. While various cloud-native monitoring tools, container security solutions, and endpoint detection and response (EDR) systems provide essential insights, they generally focus on individual layers of the cloud environment. A more holistic approach can be achieved through the use of Extended Berkeley Packet Filter (eBPF) sensors. These tools offer comprehensive, real-time insight across all layers—network, infrastructure, workloads, and applications—without disrupting operational environments. Operating at the kernel level, eBPF provides visibility without imposing performance penalties, making it an effective choice for runtime security.
Key capabilities to harness for this step include topology graphs that illustrate how hybrid or multi-cloud assets interconnect, full asset visibility showcasing every asset in the environment, insights into external connectivity that reveal sources and DNS information, and risk assessments that evaluate each asset’s potential impact on business operations.
Step 2: Employ a Multi-Layered Detection Strategy
As adversaries adapt their tactics to avoid detection, identifying and thwarting breaches before they occur becomes increasingly difficult. The primary obstacle lies in detecting attacks that exploit multiple vulnerabilities and entry points, ranging from network exploitation to data manipulation within managed services, while circumventing standard cloud detection and response protocols. This fragmented tactical approach has been insufficient, allowing attackers to slip through gaps between defense layers unnoticed.
Combining cloud, workload, and application monitoring into a single platform enhances coverage and defenses. This integration facilitates the real-time correlation of application activity and infrastructure changes, ensuring that attacks cannot evade detection.
Security teams can gain from capabilities such as full-stack detection that captures incidents across various platforms and APIs, anomaly detection using machine learning for identifying irregular patterns, and incident correlation that synthesizes alerts across sources to identify potential threats.
Step 3: Integrate Vulnerability Insights with Incident Data
Isolating vulnerabilities from incident details can lead to delayed responses and increased oversight. Security teams often lack the necessary context to understand how these vulnerabilities are exploited or how urgently they need to be addressed in light of ongoing incidents.
By leveraging runtime monitoring, as outlined previously, organizations can significantly enhance their vulnerability management practices, prioritizing active and critical risks while reducing unnecessary alerts by more than 90%. Key capabilities for this step should focus on risk prioritization—assessing vulnerabilities based on critical factors such as execution status and public exposure—and root cause analysis to uncover the fundamental source of vulnerabilities.
Step 4: Incorporate Identity Context to Assess Threats
Compromised credentials often facilitate attackers’ maneuvers, allowing them to masquerade as legitimate users within the system. This is why establishing a baseline for identity behavior, whether human or machine, is crucial. Understanding the typical access patterns enables teams to detect anomalies effectively.
Security frameworks should encapsulate baseline monitoring tools that record activity patterns, security for human identities by integrating with identity providers, and oversight of non-human identities to identify abnormal interactions with cloud resources. Additionally, managing secrets and identifying all secured components in use further reinforce defenses against unauthorized access.
Step 5: Adopt a Flexible Response Strategy
Each attempted breach presents unique challenges that necessitate a dynamic response strategy. For instance, a malicious process may require immediate termination, while other interventions might involve isolating a compromised workload to prevent further damage. Following detection, it is imperative for security teams to have context readily available, including attack narratives and remediation playbooks.
The strategies employed should include a variety of response playbooks tailored to specific incidents, the ability to implement customized interventions, root cause analysis to avert repeat occurrences, and integration with Security Information and Event Management (SIEM) systems to enhance threat detection through contextual data.
By implementing these strategic steps, organizations can significantly enhance their detection and response capabilities, positioning themselves to combat cloud breaches in real time with greater accuracy. The moment to take decisive action is now—begin your journey with comprehensive security solutions today.
