Runtime protection: Threats, technologies, and 5 best practices

What is runtime security and protection?

Runtime protection (or runtime security) safeguards active applications and workloads from threats by monitoring for malicious behavior, vulnerabilities, or misconfigurations while code executes. Unlike static scanning, it offers real-time detection and response for cloud workloads, containers, and applications, providing a critical last line of defense against zero-day exploits and active attacks.

The scope of runtime security spans a range of environments, including on-premises servers, cloud workloads, containers, and end-user devices. Key components involve detecting malicious behaviors, enforcing access controls, isolating processes, and automatically responding to threats. By focusing on live environments, runtime protection helps prevent breaches, data loss, and service disruptions that can occur after initial security checks have been passed.

This is part of a series of articles about application security.

Why runtime security matters

Runtime security matters because most real-world attacks happen after an application is deployed and running. While pre-deployment checks reduce known risks, they cannot account for every runtime condition, user interaction, or emerging threat. Systems today are highly dynamic, with constant changes in infrastructure, workloads, and integrations. This creates attack surfaces that only exist during execution.

• Covers gaps left by pre-deployment security: Static analysis and testing cannot predict all runtime conditions. New inputs, integrations, and user behaviors can introduce risks after deployment. Runtime security detects issues that appear in live environments.
• Detects active threats in real time: Attacks such as code injection, privilege escalation, and lateral movement happen during execution. Runtime protection monitors behavior continuously and flags anomalies as they occur.
• Reduces time to response: Automated detection and response mechanisms can block or isolate threats immediately. This limits attacker dwell time and reduces damage.
• Protects dynamic and distributed systems: Modern systems use microservices, containers, and cloud workloads that scale and change frequently. Runtime security adapts to these changes without requiring constant manual updates.
• Prevents data loss and service disruption: By stopping malicious actions early, runtime controls help maintain system availability and protect sensitive data from exfiltration or corruption.
• Supports compliance and audit requirements: Continuous monitoring and logging provide visibility into system activity. This helps meet regulatory requirements for security controls and incident tracking.
• Complements other security layers: Runtime protection works alongside static analysis, network security, and identity controls. It acts as a final defense layer when other measures fail or are bypassed.

Common runtime security threats

Malware and ransomware

Malware and ransomware are among the most prevalent runtime threats, targeting active processes and systems. Malware can run undetected during normal operations, extracting sensitive data, altering system configurations, or serving as a launchpad for further attacks. Ransomware encrypts critical files or systems during runtime, demanding payment to restore access. Both types of attacks exploit the period when systems are operational and user activity is high.

These threats can propagate quickly and disrupt business operations. Traditional security tools may fail to detect them if they rely solely on signature-based detection or static analysis. Runtime security solutions use behavioral analysis and real-time monitoring to catch malicious actions as they occur, enabling containment and response before significant damage occurs.

Fileless attacks

Fileless attacks operate directly in memory, leaving little or no trace on disk. These attacks leverage legitimate system tools and processes, such as PowerShell or Windows Management Instrumentation (WMI), to execute malicious code during runtime. Because they do not rely on files, traditional antivirus solutions that scan for known malware signatures are often ineffective.

Detecting and preventing fileless attacks require runtime security tools that monitor system behavior, process activity, and command execution in real time. By focusing on anomalies and unauthorized actions, organizations can identify fileless threats even when they mimic legitimate operations. This approach helps defend against persistent threats that use fileless techniques to remain undetected within a compromised environment.

Privilege escalation

Privilege escalation occurs when attackers gain higher access rights within a system or application by exploiting vulnerabilities or misconfigurations during runtime. Once elevated, attackers can bypass security controls, access sensitive data, and move laterally within an environment. Runtime security detects suspicious privilege changes, unauthorized account usage, and attempts to exploit system processes.

Attackers often use privilege escalation as a step toward activities such as data exfiltration or ransomware deployment. Continuous monitoring and real-time alerting enable organizations to respond promptly. By enforcing strict access controls and auditing privilege-related actions during runtime, security teams can reduce the risk of unauthorized escalation and limit the impact of a breach.

Code injection

Code injection attacks involve inserting malicious code into a running process, which is then executed by the target application. Examples include SQL injection, command injection, and cross-site scripting (XSS). These attacks exploit vulnerabilities in input handling, often bypassing security controls when the application processes user-supplied data. The injected code can manipulate application behavior, exfiltrate data, or provide remote access to attackers.

Runtime security tools detect code injection attempts by monitoring input validation, analyzing process memory, and inspecting network traffic for suspicious payloads. Rapid detection and response are necessary because successful code injection can give attackers persistent control over systems. Implementing runtime protection mechanisms, such as web application firewalls and real-time code integrity checks, helps prevent exploitation of these vulnerabilities.

Unauthorized access and lateral movement

Unauthorized access occurs when attackers gain entry to systems or data without proper credentials, often by exploiting weak authentication, stolen credentials, or software vulnerabilities. Once inside, attackers use lateral movement techniques to traverse the network, compromise additional systems, and escalate privileges. Runtime security addresses this threat by continuously monitoring for unusual login attempts, session hijacking, and abnormal network communications.

Lateral movement is particularly dangerous in complex environments where segmentation is weak or monitoring is limited. Runtime protection solutions detect suspicious patterns, such as a user accessing multiple systems in rapid succession or initiating connections from unusual locations. By identifying these behaviors in real time, organizations can contain threats before attackers achieve their objectives or cause widespread damage.

Key components of runtime security and protection

Process isolation and sandbox techniques

Process isolation and sandboxing are foundational techniques for runtime security. Isolation ensures that each process runs in its own protected environment, preventing malicious code from affecting other processes or accessing sensitive resources. By restricting the privileges and access of individual processes, organizations can limit the impact of a compromised application or service, reducing the risk of lateral movement and data leakage.

Sandboxing executes untrusted or potentially dangerous code in a controlled environment that mimics the production system. This allows security teams to observe application behavior and detect threats without exposing core infrastructure. Sandboxes are useful for analyzing unknown files, monitoring third-party code, and testing updates before deployment.

System call monitoring and filtering

System call monitoring tracks the requests that running processes make to the operating system. Many attacks rely on abusing system calls to perform unauthorized actions, such as reading sensitive files, modifying system settings, or spawning new processes. Monitoring these interactions provides insight into runtime behavior. Security solutions can detect anomalies or policy violations by analyzing system call patterns in real time.

Filtering blocks or restricts specific system calls that are unnecessary or commonly abused by malware. This reduces the attack surface and prevents exploitation of vulnerabilities in the operating system or application runtime. Combining monitoring and filtering supports rapid detection and mitigation of threats.

Behavioral analytics and anomaly detection

Behavioral analytics uses machine learning and statistical models to profile normal system and user activities, establishing baselines for expected behavior. During runtime, deviations from these baselines, such as unusual process activity, abnormal resource consumption, or unexpected network connections, are flagged as potential threats. This method supports identification of previously unknown or zero-day attacks that do not match existing signatures.

Anomaly detection is valuable in dynamic environments where rules-based systems struggle to keep pace with new tactics. By continuously analyzing runtime data, behavioral analytics can adapt to changing usage patterns and detect attacks that attempt to blend in with legitimate activity. This detection capability enables faster response and reduces the likelihood of successful breaches.

File integrity monitoring (FIM)

File integrity monitoring (FIM) tracks changes to critical files and directories. By establishing a baseline of trusted file states, FIM solutions alert security teams when unauthorized modifications, deletions, or additions occur. This helps detect tampering, such as installation of rootkits, backdoors, or alteration of configuration files that could compromise system integrity.

FIM operates in real time, providing visibility into suspicious changes that may indicate an ongoing attack. Implementations can integrate with broader security workflows, triggering automated responses or forensic analysis when anomalies are detected. This helps organizations maintain compliance with regulatory standards and ensures that unauthorized changes are contained and remediated.

Intrusion detection and prevention systems (IDPS)

Intrusion detection and prevention systems (IDPS) monitor network and system activity for signs of malicious behavior during runtime. IDS components analyze traffic and event logs to identify patterns that match known attack signatures or indicate anomalies, while IPS components can automatically block or mitigate detected threats. By operating in real time, IDPS solutions help prevent attacks from progressing beyond initial compromise.

Modern IDPS platforms combine signature-based detection with analytics and machine learning to improve accuracy and reduce false positives. They are often deployed alongside other runtime security tools to provide visibility across the environment. Effective IDPS implementations enable organizations to detect threats, enforce security policies, and respond to incidents as they unfold.

Types of runtime security solutions

Application runtime protection

Application runtime protection focuses on safeguarding applications during execution by monitoring behavior, validating inputs, and enforcing security policies. These solutions detect and prevent attacks such as code injection, privilege escalation, and unauthorized access in real time. By embedding security controls within the application runtime, organizations can stop threats that bypass perimeter defenses. A well-established example of this category is runtime application self-protection (RASP), which embeds security instrumentation directly into the application to detect and block attacks from within.

Modern tools often integrate with development pipelines and production environments, enabling continuous security throughout the software lifecycle. They provide visibility into application processes and can remediate threats without significantly affecting performance or user experience. This approach helps defend against attacks that target application logic and business data.

Container and Kubernetes runtime security

Container and Kubernetes runtime security focuses on protecting containerized workloads while they are running in orchestration environments. Containers are short-lived and dynamic, which makes traditional security approaches less effective. Runtime protection monitors container behavior, including process execution, network activity, and interactions with the host system, to detect anomalies and policy violations.

Kubernetes adds complexity with its control plane, APIs, and scheduling mechanisms. Runtime security tools enforce policies such as limiting container privileges, restricting communication between pods, and detecting suspicious activity like container escapes or unauthorized access to the Kubernetes API. These controls help prevent attackers from exploiting misconfigurations or vulnerabilities in containerized environments.

Solutions can integrate with Kubernetes primitives such as namespaces, network policies, and admission controllers. They provide visibility across clusters and can automate responses like terminating compromised containers or isolating affected workloads. This helps security keep pace with the rapid scaling and changes typical of container environments.

Cloud runtime security

Cloud runtime security protects workloads running in cloud environments, including virtual machines, serverless functions, and managed services. Cloud systems are elastic and often distributed across regions, which increases the attack surface. Runtime protection monitors activity across these resources to detect threats such as unauthorized access, misconfigurations, and abnormal usage patterns.

A key aspect of cloud runtime security is visibility into cloud-native events, such as API calls, identity usage, and resource provisioning. Attackers often exploit weak identity and access management (IAM) controls or exposed services during runtime. Security tools analyze these activities in real time to identify suspicious behavior, such as unusual login locations or excessive privilege use.

Cloud runtime solutions also enforce security policies continuously, ensuring that configurations remain compliant as infrastructure changes. Automated responses, such as revoking access keys or isolating compromised instances, reduce the impact of attacks. This approach helps maintain control in environments where manual oversight is limited.

Endpoint runtime protection

Endpoint runtime protection secures end-user devices such as laptops, desktops, and mobile devices while they are in use. These endpoints are common entry points for attacks, especially through phishing, malicious downloads, or compromised applications. Runtime protection monitors processes, memory usage, and user activity to detect threats as they execute.

Modern endpoint protection platforms go beyond traditional antivirus by using behavioral analysis and real-time monitoring. They can identify fileless attacks, ransomware activity, and suspicious system changes that do not match known signatures. This supports detection of threats that evade conventional defenses.

Response capabilities are a core component of endpoint runtime security. Solutions can isolate infected devices from the network, terminate malicious processes, and roll back harmful changes. By acting during an attack, endpoint runtime protection helps prevent data loss, limit lateral movement, and maintain system integrity.

Best practices for implementing runtime security and protection

1. Adopt a layered (defense-in-depth) approach

Runtime security should not operate in isolation. It works best when combined with network controls, identity management, pre-deployment testing, and other application security best practices. Each layer addresses different attack vectors, reducing the chance that a single failure leads to a breach.

In practice, this means enforcing least privilege at runtime, monitoring network traffic, and validating application behavior simultaneously. If an attacker bypasses one control, other layers can still detect or block the activity. This approach limits impact and improves resilience.

It is also important to ensure that layers are independent. For example, runtime monitoring should not rely on the same trust assumptions as identity systems. Decoupling controls reduces the risk of cascading failures and makes detection more reliable during complex attacks.

2. Integrate runtime security into DevSecOps

Runtime security should be part of the continuous delivery pipeline, not an afterthought. Security teams need visibility into how applications behave in production and must feed that data back into development. This creates a loop where runtime insights improve future builds.

Integration involves embedding monitoring agents, defining runtime policies as code, and aligning alerts with CI/CD workflows. Developers can then reproduce and fix issues based on real execution data, reducing the gap between detection and remediation.

Over time, this integration enables automated decision-making. For example, deployments can be blocked if runtime policies are violated in staging, or rolled back automatically if anomalies appear in production. This makes security an active part of delivery rather than a passive control.

3. Correlate code vulnerabilities with runtime exploitability

Not all vulnerabilities are equally dangerous in production. Some may never be reachable or exploitable at runtime. Correlating static findings with runtime data helps prioritize risks based on actual exposure.

This requires mapping vulnerabilities to running processes, APIs, and user paths. If a vulnerable function is actively used or exposed externally, it becomes a higher priority. This focus helps teams address real threats instead of spending time on low-impact issues.

Additional context, such as user roles, network exposure, and data sensitivity, further refines prioritization. A medium-severity flaw in a public-facing service may matter more than a critical issue in an internal tool with limited access. Runtime context clarifies this distinction.

4. Combine SAST, SCA, and runtime context

Static application security testing (SAST) and software composition analysis (SCA) identify issues in code and dependencies before deployment. However, they lack context about how the application behaves in production. Runtime data fills this gap.

By combining these approaches, teams can see which vulnerable components are loaded, executed, or exposed at runtime. This reduces false positives and improves remediation accuracy. It also helps validate whether fixes are effective once deployed.

This combination also supports better risk scoring. Instead of treating all findings equally, teams can rank issues based on execution frequency, exposure, and real-world usage. This leads to more efficient use of engineering time and faster reduction of meaningful risk.

5. Leverage container and dependency intelligence

Modern applications rely heavily on containers and third-party libraries. Runtime security should track which images, packages, and dependencies are in use. This clarifies the actual attack surface.

Tools can monitor container layers, running processes, and loaded libraries to detect outdated or vulnerable components in execution. When combined with threat intelligence, this allows identification of risky dependencies and targeted updates without disrupting the entire system.

It is also useful to track drift between deployed and running states. Containers may start from a trusted image but change over time due to updates or compromise. Runtime intelligence can detect these deviations and trigger remediation, ensuring that what runs in production remains aligned with approved configurations.

Runtime protection with Mend.io

Mend.io delivers runtime protection through dynamic application security testing (DAST), scanning live applications for vulnerabilities that only surface during execution. Where static analysis finds issues in code before deployment, DAST validates what attackers actually see: running endpoints, active authentication flows, and real application behavior under real conditions.

Mend.io’s DAST capabilities connect directly to the broader Mend platform, so runtime findings land in the same workflow as your SAST and SCA results. Teams get a complete picture of risk across the software lifecycle without switching tools or reconciling separate reports.

For AI applications, Mend AI Guardrails delivers runtime protection at the interaction layer, detecting and blocking threats like prompt injection, toxic outputs, and policy violations as they occur. As AI becomes a core part of application architecture, securing it at runtime is no longer optional.