Almost nine in ten organizations, 87%, are running services with at least one known vulnerability, according to a DevSecOps report. It’s not that teams are skipping code scans. Code is simply shipping faster than static scanning alone can keep pace with, and manual triage falls farther behind with every release.
That’s why today, runtime sensors, application-layer instrumentation, and automated response capabilities need to be tied directly into the deployment pipeline. This way, the moment code ships, it can be watched and handled automatically, instead of waiting for a security analyst to notice issues later. Wiz and a handful of other cybersecurity providers are already building detection and response directly into pipeline workflows.
Which cybersecurity platform is actually best for threat detection as well as incident response depends on where in the pipeline it’s expected to operate. The platforms in this list all operate at different layers. Some specialize in kernel-level runtime signals. Others work at the application layer, or focus on closing the loop between detection and verification. To choose the best, teams need to hone in on which aspect of the pipeline they’re trying to cover.
Where Runtime Context Fits in the Detection Pipeline
Only 18% of critical dependency vulnerabilities remain critical after applying runtime context, that same report found. In other words, over 80% of what a static scanner flags as urgent isn’t actually running or reachable.
Runtime sensors operate at the kernel level to determine what’s happening behind the scan result. They look at elements like process execution, network connections, or file modifications to see whether a vulnerable package is truly active in memory.
Runtime sensors use the kernel technology eBPF on Linux, Kubernetes, VMs, and serverless containers. For Windows, sensors use a memory-safe kernel-mode driver that registers with Windows security APIs. Either way, the mechanism produces the same thing: a real-time answer to whether a flagged package is actually loaded and running.
Before a team spends hours fixing every “critical” finding, runtime context tells them which ones are actually worth the time. That’s why teams need runtime context feeding into prioritization before remediation work starts.
Because runtime context matters this much, several platforms in this list, including Wiz, AccuKnox, and Upwind, are built around this exact runtime-first model. Read below to find out what sets them apart.
1. Wiz
Wiz provides detection and response through Wiz Defend. It works in three steps. First, it watches for suspicious activity across your cloud, workloads, and logs. Second, it checks that activity against the Security Graph, which is Wiz’s map of your environment. That way, it knows what that workload can reach and who owns it. Third, it investigates automatically and hands your team a plain-language explanation instead of a raw alert.
The first step runs on the Threat Detection Engine, which watches cloud audit logs, workload telemetry, and Runtime Sensor data for anything that looks off. Once something is flagged, the Security Graph adds the context. From there, Wiz Blue Agent investigates on its own and returns a verdict your team can read without having to do any digging.
If a threat is confirmed, Wiz can act right away, whether that means killing the process, isolating the VM, or revoking IAM access.
Key Features
- Security Graph adds identity, exposure, and data context to every runtime alert.
- Threat Detection Engine checks cloud audit logs, workload telemetry, and Runtime Sensor data against continuously updated rules.
- Wiz Blue Agent investigates automatically and hands back a plain-language verdict.
- Incident Readiness dashboard maps your telemetry coverage against the MITRE ATT&CK framework.
- Runtime Sensor runs on eBPF for Linux, Kubernetes, VMs, and serverless. Windows gets a separate, memory-safe kernel-mode driver instead.
2. Darktrace
Darktrace takes a different approach than signature-based tools. Instead of looking externally for signs of attacker behavior, it learns what normal looks like in your environment first. When behavior deviates from the baseline, its Antigena module responds by taking a proportionate action based on the level of the threat.
Each environment has a unique baseline of normal behavior, spanning across network, cloud, email, and OT, on top of core workloads.
This breadth of coverage is particularly relevant for DevSecOps teams operating in hybrid or complex environments.
Key Features
- Self-learning AI models a baseline of normal behavior per environment rather than relying on signature-based rules.
- The Antigena autonomous response module takes proportionate, targeted containment actions.
- Coverage spans network, cloud, email, and OT alongside core workloads.
- Attack path visualization supports investigation.
- Built for complex, hybrid, and multi-cloud environments.
3. AccuKnox
AccuKnox is another runtime context provider, but distinct from a graph-correlation platform like Wiz. It’s a policy-enforcement-first option that combines eBPF for kernel-level visibility with Linux Security Module (LSM) enforcement. That second part allows it to block unauthorized behavior directly, rather than just alert on it.
This pairing is what sets AccuKnox apart architecturally. Every other platform here works by detecting malicious activity first, then responding to it, even when that response is a real-time block. AccuKnox’s LSM policies work upfront by defining what’s allowed by default, so unauthorized behavior gets blocked because it violates policy, whether or not a detection engine ever flags an attack.
For DevSecOps use cases specifically, AccuKnox also covers the CI/CD pipeline directly. That means infrastructure-as-code, image registries, source code, and build processes receive the same coverage as the workloads running downstream of them.
Key Features
- Pairs eBPF-based observability with LSM (AppArmor/SELinux) enforcement via its open-source KubeArmor project.
- Blocks unauthorized process execution, file access, and network activity as part of a Zero Trust setup.
- Automatic incident containment isolates compromised workloads and prevents lateral movement.
- Behavioral anomaly detection with AI-driven policy recommendations generated from actual workload behavior.
- CI/CD pipeline security coverage across IaC, image registries, and build processes.
4. Contrast Security
Contrast is the application-layer option, making it distinct from the other platforms on this list. Its Application Detection and Response (ADR) embeds lightweight sensors into the application runtime.
Contrast monitors all code execution, data flow, and request handling from the inside.
SQL injection, unsafe deserialization, and zero-day exploits often happen entirely within the application layer, in ways that rarely show up as anomalous network activity or suspicious process behavior. An infrastructure-focused runtime tool can’t see them. Contrast can, because it’s already inside the code path where they occur.
Key Features
- Application Detection and Response (ADR) embeds sensors directly into the application runtime.
- Detects application-layer attacks from inside the code, not by inferring from external traffic.
- Real-time blocking capability for zero-day exploits and API attacks in production.
- Powered by the Contrast Graph, a real-time security model of the application and API ecosystem.
- Integrates with SIEM/SOC platforms, including a confirmed integration with Google Security Operations, to feed verified runtime application telemetry into broader detection workflows.
5. Rapid7
Rapid7 specializes in confirming that a response actually worked, not just that it ran.
There are several distinct technologies at play. InsightIDR handles detection, watching for suspicious activity across the environment. Once InsightIDR flags something, InsightConnect kicks off an automated response playbook.
Many detection tools stop at triggering the response, but Rapid7 feeds the playbook’s outcome back into InsightIDR for correlation and confirmation. The same goes for vulnerability management findings through InsightVM. Flagged issues trigger a remediation workflow, and the fix is tracked through to verification.
Key Features
- InsightConnect runs automated response playbooks triggered by InsightIDR detections.
- Results feed back into InsightIDR for correlation and post-incident confirmation, closing the loop.
- InsightVM extends the same detect-remediate-verify pattern to vulnerability management.
- Broad integration ecosystem (Jira, ServiceNow, Slack) for routing confirmed findings into existing workflows.
- SOAR-based orchestration reduces manual, repetitive triage work.
6. Sysdig Secure
Sysdig Secure is built on Falco, the open-source runtime detection engine widely used across the DevSecOps community. That open-source foundation gives teams more visibility into detection logic.
Falco by itself only detects and alerts. Sysdig Secure is the commercial platform built on top of it that adds the response element.
When a detection fires, Sysdig can kill the container, pause it, or capture an EBS snapshot for forensics. If an identity looks compromised, it can quarantine that too. And if the team wants to dig in manually, Sysdig provides them a secure remote shell.
Key Features
- Built on Falco, the open-source runtime detection engine.
- Response Actions layered on top of Falco’s detections: kill, stop, or pause a container, quarantine a file.
- Cloud Response Actions for AWS support EBS volume snapshots, IAM quarantining, and removal of public access.
- Rapid Response provides a secure remote shell for hands-on investigation.
- Forensic capture at the moment of a runtime event.
7. Upwind
Upwind is the newest platform on this list, and it was built around runtime from the ground up. Most CNAPP platforms started with static scanning, later adding runtime on top. Upwind is the opposite.
Here, runtime comes first, as Upwind continuously observes what’s actually happening across traffic, API calls, and processes, rather than maintaining a separate vulnerability list to check against runtime data afterward. Everything else, including how it prioritizes vulnerabilities, builds directly on what it’s already watching.
Upwind also fits into existing SOC infrastructure through integrations with Microsoft Sentinel and Azure Defender for Cloud.
Key Features
- eBPF-native architecture treats runtime telemetry as the primary signal, not an add-on to static scanning.
- Correlates process, network, and API-level behavior into “Threat Stories,” dynamic timelines of an attack with root-cause and exploitability context.
- Response capabilities include killing malicious processes and automated containment.
- AI Detection & Response (AI-DR) module extends the same runtime intelligence to AI workloads.
- Integration with Microsoft Sentinel and Azure Defender for Cloud.
How to Choose a Detection and Response Platform for Your Pipeline
Before comparing any of these platforms head to head, it can be helpful to investigate where your current coverage falls short.
Then, compiling the answers to the below questions will give you a general idea of the type of platform you can benefit most from:
- Does it operate at the layer where your team actually needs coverage, kernel, application, or orchestration?
- Does it distinguish between a finding that’s merely present and one that’s actually running or reachable?
- Does it close the loop by verifying that responses actually resolved the issue?
- Does it integrate with the CI/CD tooling your team already uses?
- Does it correlate findings with identity and exposure context, or leave that correlation to your team manually?
Real-time detection and response spans several layers, and no single platform covers all of them the same way. A DevSecOps team’s real job is matching the right layer of coverage to where their current setup falls short, and making sure whatever platform they choose closes the loop.
Frequently Asked Questions
What is the best platform for detection and response in a DevSecOps pipeline in 2026?
The best platform is the one that matches your pipeline’s actual layer of need, kernel-level runtime, application-layer, or orchestration, while still closing the loop on verification rather than stopping at containment. Wiz is one example built to unify several of these layers through Security Graph correlation.
Why does runtime context matter for vulnerability prioritization?
Only 18% of critical dependency vulnerabilities remain critical after runtime context is applied. That means over 80% of what a static scanner flags is just noise. Without runtime context, teams waste their time on alerts that don’t matter.
What’s the difference between eBPF-based detection and application-layer detection?
eBPF-based tools watch from the kernel level. Wiz, AccuKnox, Upwind, and Sysdig all work this way. They track processes, connections, and file activity across a workload. Application-layer tools work from inside the app instead. Contrast sits inside the application’s own runtime, watching code execution and request handling within the app.
Can detection and response be automated in a DevSecOps pipeline?
Yes, but not end-to-end. Killing a process or isolating a VM can be done automatically. However, actually fixing the root cause, such as patching a vulnerable system or updating IAM roles, requires human attention.