What Is Runtime Security?
Runtime security involves protecting applications during their operational phase. Unlike build-time security measures, which focus on preparing safe code and environments, runtime security is about protecting live applications from threats as they execute. This includes observing application behavior, identifying anomalous activities, and preventing exploits while maintaining performance.
Runtime security systems integrate with existing infrastructure to provide protection without disrupting application workflows. Runtime security requires deploying multiple strategies to protect the application environment. Techniques can range from simple access control to complex anomaly detection algorithms.
This type of security detects threats and includes alert mechanisms for rapid response and remediation. By applying layered security measures, organizations can defend against a wide spectrum of potential threats.
This is part of a series of articles about cyber security
What Threats Does Runtime Security Protect Against?
Runtime security protects applications from a variety of cyber threats that can only be detected while the application is running. These threats exploit vulnerabilities that may not be visible in static or dynamic code analysis. Key threats include:
- Malware and malicious code: Some malware can evade traditional detection methods by hiding in software dependencies or disguising its intent until execution. Runtime security detects and mitigates these threats in real time by monitoring application behavior and identifying unexpected activities.
- Code injection and memory corruption: Attackers can inject malicious code into a running application through buffer overflows and other injection techniques. Since this type of threat is introduced at runtime rather than during development, runtime security is essential for identifying and blocking such attacks.
- Unauthorized access and privilege escalation: Runtime security can detect unauthorized access attempts and privilege escalation efforts, where attackers try to gain higher system privileges. Security policies can be enforced to deny unauthorized actions and log these attempts for further investigation.
- Zero-day exploits: Previously unknown vulnerabilities (zero-days) in software can be exploited before patches are available. While runtime security cannot prevent zero-day vulnerabilities, it can detect their effects, such as unusual system behavior or network activity, allowing security teams to respond quickly.
- Suspicious behavior and anomalous activity: Attackers often use stealthy techniques, such as outbound connections to command-and-control (C2) servers or obfuscated command-line scripts, to avoid detection. Runtime security continuously monitors application activity, flagging deviations from expected behavior that could indicate an attack in progress.
Key Components of Runtime Security
Process Isolation and Sandbox Techniques
Process isolation involves creating boundaries around each running process, ensuring that if one is compromised, the impact is minimized to just that process or container. Sandbox techniques are commonly applied here, utilizing dedicated, isolated containers to execute applications in a controlled manner that prevents deviation from expected behavior.
These techniques provide a predictable and secure execution space for applications, reducing the risk of lateral movement within the system architecture. By confining applications to strict operational environments, organizations can ensure a higher level of security and integrity, especially in complex systems that host multiple applications simultaneously.
System Call Monitoring and Filtering
System call monitoring involves tracking application requests to the operating system. By observing these interactions, security systems can identify irregular or unauthorized activities that could signal an ongoing attack. This method is effective in spotting malware attempting unauthorized access or data exfiltration, which often manifest through unexpected system calls.
Filtering unauthorized calls helps maintain a secure and controlled application environment, deterring potential breaches. Filtering improves security by allowing only permitted interactions, reducing the risk of exploits that could compromise system resources. This selective access is essential for preventing unauthorized actions while enabling legitimate operations.
Behavioral Analytics and Anomaly Detection
Behavioral analytics involves evaluating application activity to detect deviations from established norms, often indicative of security incidents. Utilizing machine learning models, these systems learn standard behavior patterns and flag variances that suggest potential threats. This helps identify subtle, sophisticated attacks that traditional security measures might miss.
Anomaly detection complements behavioral analytics by providing insights into unexpected system activities, allowing security teams to differentiate between legitimate deviations and harmful behavior. Early detection enables quicker responses, reducing the potential damage from undetected threats.
File Integrity Monitoring (FIM)
File integrity monitoring (FIM) involves the continuous scanning and verification of files to ensure they haven’t been tampered with. This process provides a layer of security by detecting unauthorized changes, whether intentional or accidental, that could indicate a security breach or system compromise.
FIM tools provide instant alerts when deviations from established baselines are detected, allowing for timely investigation and response to potential threats. FIM techniques protect critical system and application files from illicit access, ensuring that core processes remain uncompromised.
Intrusion Detection and Prevention Systems (IDPS)
Intrusion detection and prevention systems (IDPS) are a traditional security component that complements other runtime security measures. It scrutinizes network traffic and system activities to identify and prevent suspicious actions. IDPS combines real-time monitoring with historical analysis to detect patterns that suggest a potential threat, ranging from unauthorized access attempts to exploit delivery.
When such patterns are detected, the system can respond automatically to block threats, minimizing damage by neutralizing attacks before they reach critical assets. IDPS can quickly analyze complex data and react. This is essential in environments with rapid deployment and change.
Runtime Security in Different Environments
Application Runtime Security
Application runtime security focuses on protecting applications during execution by monitoring their behavior and preventing attacks without affecting performance. Application runtime security solutions, provide protection against threats like code injection, privilege escalation, and anomalous activities.
A key component is real-time application monitoring, where security tools observe interactions such as memory usage, API calls, and database queries. This allows detection of deviations from normal behavior that may signal attacks. For example, unauthorized file modifications or unexpected network activity could indicate malware or an exploit in progress.
Enforcing access controls and runtime policies is another important aspect. By applying least privilege principles and restricting access to sensitive resources, runtime security reduces potential attack surfaces. Security measures such as encryption of sensitive data in memory and runtime application self-protection (RASP) further improve defenses.
Runtime Security in Container Environments
Containers provide a lightweight and scalable approach to application deployment, but their ephemeral nature introduces unique security challenges. Runtime security in containerized environments focuses on monitoring and securing containers while they execute, ensuring threats are detected and mitigated without disrupting operations.
One key aspect is container isolation, which enforces strict boundaries between containers to prevent lateral movement of threats. Additionally, runtime security tools analyze container behavior, detecting anomalies such as unexpected process execution, privilege escalation attempts, or unauthorized network connections.
Another critical area is visibility and logging. Since containers are transient, logging security-relevant activities in real time is essential for forensic analysis and threat response. Tools like eBPF-based monitoring and kernel-level security modules improve detection capabilities without imposing significant performance overhead.
Runtime Security in Kubernetes
Kubernetes introduces additional complexity to runtime security due to its dynamic orchestration of containers across clusters. Threat actors often target Kubernetes environments to exploit misconfigurations, weak access controls, and vulnerabilities in workloads.
A core component of Kubernetes runtime security is monitoring pod and container activity to detect unauthorized privilege escalation, suspicious network traffic, or unexpected process execution. Security policies, such as those enforced by Kubernetes network policies or Open Policy Agent (OPA), help restrict communication between pods and limit potential attack vectors.
Runtime security also involves securing the Kubernetes API, which is a common target for attackers. Role-based access control (RBAC) should be enforced to limit access to cluster resources. Additionally, admission controllers can validate pod security policies before deployment, preventing risky configurations from reaching runtime.
Runtime Security in Serverless and Cloud-Native Environments
Serverless computing abstracts infrastructure management, enabling developers to focus on code execution. However, this abstraction does not eliminate security concerns—runtime threats in serverless environments often stem from insecure code, misconfigured permissions, and third-party dependencies.
One major security challenge is monitoring ephemeral functions, which spin up and terminate rapidly. Traditional security tools designed for persistent workloads may struggle with this model, making event-driven security monitoring essential. Cloud-native security platforms and function-level monitoring tools analyze execution logs and detect anomalies in real time.
Identity and access management (IAM) is crucial for securing serverless applications. Overly permissive IAM roles can allow attackers to move laterally within cloud environments, so enforcing the principle of least privilege is critical. Additionally, API security is important, as serverless applications frequently interact with APIs.
4 Best Practices for Runtime Security
Here are some of the ways to ensure stronger security at runtime.
1. Implement a Defense-in-Depth Strategy
A defense-in-depth strategy involves establishing multiple layers of security controls to protect critical assets across different stages. Each layer consists of separate security technologies and practices, ensuring that if one layer is breached, others remain intact. Typical layers include perimeter defenses like firewalls, network segmentation, intrusion detection systems, and internal security policies such as access control and encryption.
By deploying varied defenses, organizations create additional obstacles for potential attackers, decreasing the likelihood of successful breaches. Incorporating this strategy extends security throughout the application spectrum. Defense in depth also involves regular security assessments to ensure each layer remains effective against emerging threats.
2. Continuous Monitoring and Logging
Continuous monitoring and logging enable real-time insight into system activities and user actions across environments. By integrating advanced monitoring tools with automated alerting systems, organizations can detect anomalies, such as unauthorized access attempts or unusual data flows, in real time. This visibility is essential for swiftly mitigating risks.
Logging practices provide a detailed record of activity and interactions within the ecosystem, critical for operational diagnostics and forensic investigations. Storing logs securely and analyzing them regularly helps in understanding the context of security events and supports compliance audits.
3. Incident Response and Forensics Planning
Incident response and forensics planning involve detailing the steps necessary for reacting to and analyzing security breaches. A well-prepared incident response plan includes protocols for identifying, containing, and eradicating threats, ensuring minimal impact on business operations. Establishing clear communication channels and roles within response teams enables quick, coordinated actions during an incident.
Forensics planning focuses on gathering and analyzing post-incident data to determine the event’s scope and origin. This helps organizations understand vulnerabilities that led to the breach and develop measures to prevent future occurrences. Including regular drills and reviews in forensics planning ensures that response teams remain practiced.
4. Integrate Runtime Security into DevOps Processes
Integrating security into DevOps processes, known as DevSecOps, emphasizes embedding security throughout the software development lifecycle. This involves incorporating security checks at every stage—from code design to deployment—ensuring vulnerabilities are identified and resolved early.
By shifting security to the left in the development pipeline, DevSecOps improves the overall security posture while maintaining development agility and speed. Automated security testing tools, such as static and dynamic application security testing (SAST/DAST), support this integration, providing continuous feedback and ensuring compliance with security standards.
Application Security with Imperva
Imperva provides Runtime Protection – real-time attack detection and prevention from your application runtime environment wherever your applications go. Stop external attacks and injections and reduce your vulnerability backlog.
Beyond runtime protection, Imperva provides comprehensive protection for applications, APIs, and microservices:
Web Application Firewall – Prevent attacks with world-class analysis of web traffic to your applications.
API Security – Automated API protection ensures your API endpoints are protected as they are published, shielding your applications from exploitation.
Advanced Bot Protection – Prevent business logic attacks from all access points – websites, mobile apps and APIs. Gain seamless visibility and control over bot traffic to stop online fraud through account takeover or competitive price scraping.
DDoS Protection – Block attack traffic at the edge to ensure business continuity with guaranteed uptime and no performance impact. Secure your on premises or cloud-based assets – whether you’re hosted in AWS, Microsoft Azure, or Google Public Cloud.
Attack Analytics – Ensures complete visibility with machine learning and domain expertise across the application security stack to reveal patterns in the noise and detect application attacks, enabling you to isolate and prevent attack campaigns.
Client-Side Protection – Gain visibility and control over third-party JavaScript code to reduce the risk of supply chain fraud, prevent data breaches, and client-side attacks.
