Research from Contrast Security's Software Under Siege 2025 report reveals that applications face an average of 81 viable attacks per month that reach actual vulnerabilities, while perimeter-based detection tools generate overwhelming alert volumes with minimal correlation to real-world exploits. Runtime analytics powered by the Contrast Graph detects attacks during code execution and correlates exploitation attempts with application architecture and business context to deliver verified, actionable threats.
Runtime analytics dramatically reduces SOC alert fatigue by observing attacks during code execution rather than guessing from network patterns. While traditional Web Application Firewalls (WAFs) generate millions of alerts with limited accuracy, runtime analytics correlates exploitation attempts with actual application vulnerabilities and architecture, delivering only verified threats with complete code-level context.
Alert accuracy determines SOC effectiveness, yet perimeter-based tools struggle to correlate with real-world exploits. Security Operations Centers (SOCs) process millions of alerts annually, with problematic accuracy rates. This overwhelming volume creates alert fatigue that masks real threats, leaving organizations vulnerable despite substantial security investments
Organizations invest in Web Application Firewalls (WAFs) at the perimeter and SIEM platforms for correlation. However, according to Contrast Security's ADR + WAF whitepaper, WAFs generate excessive false positives due to their reliance on generic signatures and lack of application context. The remaining noise floods SOC teams, while application-layer attacks go undetected because perimeter tools operate at the network edge rather than within the application runtime, where exploitation actually occurs. This is why Application Detection and Response (ADR) has become a critical component of modern security stacks.
Applications face an average of 81 viable attacks per month that bypass traditional perimeter defenses and reach actual vulnerabilities. This means SOC teams must investigate countless alerts while genuine threats targeting exploitable code continue to emerge during the investigation.
Tools designed to detect application-layer attacks have traditionally operated at the network perimeter, generating alerts based on traffic patterns without understanding what happens inside applications. This perimeter-focused approach creates three critical problems:
Consider an untrusted deserialization vulnerability. An attacker sends a crafted payload designed to execute arbitrary code. Your WAF might detect unusual serialization patterns and generate an alert. But it cannot determine whether deserialization occurred in a secure context or whether the attack successfully executed malicious code.
Consequently, SOC teams must investigate millions of alerts lacking application context without knowing which code was targeted, whether vulnerabilities made attacks viable or if exploitation succeeded.
Runtime analytics observes attacks as they execute within your code, not from outside your applications. This fundamentally different vantage point changes everything about detection accuracy.
|
Security approach |
Detection method |
Alert accuracy |
Context provided |
|---|---|---|---|
|
Runtime analytics |
Observes code execution during attacks |
Verified correlation to exploits |
Complete code paths, data flows and exploitation outcomes |
|
Web application firewall |
Analyzes traffic patterns at the perimeter |
Limited correlation to exploits |
HTTP request/response data, signatures matched |
|
SIEM platform |
Correlates alerts from multiple tools |
Depends on the source signal quality |
Aggregated logs and alerts from integrated tools |
When your application processes requests, runtime analytics monitors:
This visibility into application runtime execution is critical because attacks like deserialization, path traversal and business logic bypasses exploit vulnerabilities within the application layer, where WAFs and network monitoring tools lack visibility.
In a recent deployment, a financial services organization reduced their weekly alert volume from approximately 47,000 WAF alerts to 120 verified threats using runtime analytics. Their SOC team shifted from spending significant time investigating false positives to focusing exclusively on genuine exploitation attempts, enabling them to detect and block a coordinated attack targeting customer data within minutes of initial exploitation.
Graph intelligence eliminates the overwhelming majority of false positives by correlating attacks with actual vulnerabilities and code behavior. The Contrast Graph builds a comprehensive map of your application's architecture, vulnerabilities and runtime behavior.
When potential attacks occur, the Contrast Graph simultaneously:
This multi-factor analysis reveals relationships perimeter tools cannot see. An authentication bypass that your WAF flags as suspicious might target code implementing proper authentication controls. The Contrast Graph suppresses the low-priority alert or provides context showing the attack failed.
Runtime analytics achieves accurate correlation to actual exploits by observing code execution directly, representing a significant improvement over signature-based perimeter tools.
Graph intelligence also learns your application's normal runtime behavior. When path traversal attempts probe directories your application never accesses, the Contrast Graph recognizes automated scanning noise. When similar attempts target directories containing sensitive configuration files your code reads, the Contrast Graph flags high-priority threats requiring immediate investigation.
Complete runtime context accelerates every stage of incident response. When your SOC receives a deserialization alert, traditional tools provide traffic captures and signatures. Runtime analytics provides the full story:
Organizations implementing runtime analytics report significantly faster remediation of critical vulnerabilities. SOC analysts can immediately determine threat validity without extensive log analysis or developer consultation.
In a recent deployment, a healthcare provider's SOC identified a deserialization attack exploiting a zero-day vulnerability within their patient portal. Perimeter tools generated no alerts because the attack used encrypted traffic and legitimate API endpoints. Runtime analytics detected the abnormal deserialization behavior immediately, providing the exact code path, data accessed and exploitation method. The SOC deployed compensating controls within minutes, preventing exposure of patient data.
Runtime intelligence also reveals attack progression. When attackers probe multiple vulnerabilities across your application, the Contrast Graph shows the complete attack chain: reconnaissance attempts, vulnerability discovery and escalation toward critical assets.
SIEM platforms excel at correlating alerts and centralizing security data. However, SIEM can only correlate the signals it receives. When signals lack application context, even perfect correlation produces imperfect results.
Runtime analytics enriches your existing SIEM with application intelligence that transforms correlation effectiveness:
Integration follows standard patterns that preserve your existing SIEM investment. The Contrast Graph sends alerts through your established security workflows, whether you use Splunk, QRadar or cloud-native SIEM platforms. Your analysts continue working in familiar tools, now with access to runtime intelligence that dramatically improves detection accuracy.
Alert fatigue occurs when SOC teams have more work in their queues than they can comfortably handle. While overwhelming volumes of security alerts, with high false-positive rates, contribute significantly to alert fatigue, other factors include understaffing, complex investigation requirements, and alerts lacking actionable context. Perimeter-based detection tools generate excessive alerts because they analyze traffic patterns in isolation, flagging suspicious activity that may not represent actual threats. When analysts investigate hundreds of alerts daily, with fewer than 1% of them leading to genuine threats, they experience cognitive overload, which can cause real attacks to go unnoticed.
Many tools employed to detect and stop application-layer attacks operate at the network perimeter or system level, lacking visibility into application runtime, where modern attacks execute. When attacks exploit application vulnerabilities such as deserialization flaws or business-logic bypasses, perimeter-based tools cannot detect them because the attack occurs entirely within normal-looking application behavior.
Web Application Firewalls (WAFs) operate at the network perimeter, analyzing traffic patterns before requests reach applications. Runtime analytics operates inside applications, observing actual code execution as attacks unfold. This fundamental difference means WAFs guess at threats based on external patterns, while runtime analytics confirms exploitation by observing what actually happens in your code.
The Contrast Graph builds a comprehensive map of your application's architecture, vulnerabilities and runtime behavior, enabling intelligent correlation that traditional tools cannot achieve. When potential attacks occur, the Contrast Graph simultaneously evaluates whether vulnerabilities exist in targeted code, tracks data flow to determine exposure and assesses whether security controls prevented exploitation.
No code changes are required. Runtime analytics deploys through instrumentation that observes code execution without modifying application logic. Implementation methods include language-specific agents that load with your application runtime, sidecar containers for Kubernetes-based microservices or eBPF-based observation for Linux environments.