Contrast Security and IBM Consulting Partner to Strengthen Application-Layer Defense

Most security programs still miss the layer where attackers spend most of their time - inside applications. Contrast Security and IBM Consulting are taking that on together, combining real-time visibility inside running apps with AI-driven response to close the gap between detection and developer action.

As businesses ship code faster and more often, attackers have shifted their focus. They’re probing APIs, business logic, and custom code, areas traditional scanners rarely touch. Tools like SAST and DAST help during development, but once apps go live, they lose sight of what’s actually happening. That’s where attackers move in, turning runtime gaps into real incidents within seconds.

The new IBM-Contrast model changes that. It gives teams continuous, in-app visibility across live environments and connects runtime insights directly to development workflows. The result is a tighter feedback loop between security and engineering, one that keeps protection active long after code is deployed.

Sambit Misra, Offering Manager, Application Security Services, IBM Consulting, Cybersecurity Services told MSSP Alert, "The joint solution brings live visibility into applications and APIs as they run, closing the gap between runtime risk and developer action,. It detects attacks in real time through Contrast ADR’s in-app sensors and blocks them before they can spread or exploit vulnerabilities. Security teams gain insight into how applications actually behave in production without requiring the traditional testing cycles that slow releases. Auto-integration with developer tools generates actionable remediation tasks, accelerating mean time to respond (MTTR) by automatically routing findings into existing development workflows.”

This design makes runtime protection part of the development process itself, not an afterthought layered on top. By embedding detection directly inside applications, security becomes continuous and dynamic, adjusting to the speed of modern software delivery rather than holding it back.

Built for AI-Driven Development

Development now moves in hours, not weeks. Static scans can’t keep pace with AI-driven release cycles. Contrast monitors live applications in real time, flagging vulnerabilities as they appear, while IBM’s Predictive Threat Intelligence (PTI) adds global context so teams can focus on real risks.

Together, they create a security model that runs at developer speed. With attacks on public-facing apps happening every few minutes, the IBM–Contrast approach replaces slow, reactive patching with continuous, proactive protection.

Real-Time Visibility for MSSPs and Managed AppSec

The collaboration also extends its impact beyond the enterprise, giving MSPs and MSSPs new capabilities to deliver managed AppSec services that include real-time protection and developer-ready remediation.

“For the first time, MSSPs can see what’s happening inside running applications,” said Tracey Mead, VP Global Alliances & Channels, Contrast Security. “IBM’s AI and Contrast’s runtime intelligence bring the application layer into view so partners can deliver real-time protection and developer-ready fixes as part of managed AppSec.”

For most MSSPs, the application layer has long been a blind spot. They’ve had visibility into networks and endpoints but little understanding of what’s happening inside the code itself. Without that view, offering full coverage has been tough, especially now that attacks are moving deeper into the software stack.

“By feeding Contrast’s runtime telemetry directly into IBM’s Cybersecurity Services platform, partners gain live visibility into application-layer attacks,” Mead explained. “IBM’s AI triage and Contrast’s AI SmartFix remediation make it possible to detect, enrich, and resolve issues in one workflow. That means MSSPs can now deliver end-to-end managed AppSec with real-time protection and developer-ready fixes, something no other partnership offers today.”

This integrated capability allows them to expand from monitoring and detection into full-cycle security - detection, triage, remediation, and continuous improvement - all through a unified platform.

AI-Driven Correlation and Developer Integration

At the heart of the IBM Contrast model is context. By fusing Contrast’s in-app telemetry with IBM’s predictive intelligence, the joint solution provides code-level visibility and smarter, context-aware triage that helps teams make better, faster decisions.

“The joint solution brings code-level threat visibility combined with IBM’s predictive intelligence, providing context-aware triage by correlating telemetry with global threat data and accelerating response,” said Misra. “Partners can demonstrate value by showing which threats actually matter and require immediate attention, reducing noise. Ninety percent of alerts are non-actionable, leading to alert fatigue and security not scaling with development velocity. Partners differentiate by offering a solution that reduces false positives while catching real threats.”

This streamlined flow from detection to remediation ensures that developers spend time fixing real issues, not chasing false alarms. Through IBM’s centralized service portal, customers can view application telemetry, analyst insights, and incident data in one place, enhancing collaboration across teams and tightening governance around remediation timelines.

“Managed AppSec services with Contrast Security bring unified real-time visibility, collaboration, and governance into one place,” Misra added. “Auto-integration with developer tools accelerates remediation and minimizes disruption. The autonomous AI triage capability adds scale to managed AppSec monitoring while maintaining service quality.”

The result is a system where security and development move together - automated, data-driven, and built for the pace of modern DevOps. By combining Contrast’s runtime intelligence with IBM’s AI and operational expertise, the two companies are changing how organizations and their partners secure applications at scale. What was once a reactive, post-deployment task becomes a continuous, real-time practice that evolves with every release.