Dazz was a unified remediation platform that sat between security detection tools and development teams. Rather than adding another scanner, Dazz took findings from an organization’s existing security stack, correlated them to root causes in code, and automated the fix process.
Wiz acquired Dazz for $450 million in November 2024, folding the engineering team into Wiz’s product organization. The Dazz remediation engine now ships as part of Wiz Exposure Management (XM), in public preview as of 2026 — the standalone Dazz Unified Remediation Platform is no longer sold to net-new customers.
Where Dazz fits today (post-Wiz acquisition)
As of 2026, Dazz’s patented root cause analysis and remediation engine power Wiz Exposure Management. LinkedIn updates from former Dazz staff describe Wiz XM as “the result of months of incredible work by the original Dazz team.”
Existing Dazz contracts continue to be honoured during the migration window. Net-new buyers evaluating Dazz today should evaluate Wiz XM directly — the remediation logic is the same, but the platform now ships with Wiz’s cloud security graph instead of integrating with it.
If you arrived here looking for a remediation-first ASPM that is not folded into a CNAPP, the alternatives section below covers the closest standalone replacements.
What Dazz did
Security teams drowned in alerts. A single vulnerability in a base image might trigger hundreds of findings across container scanners, cloud security tools, and SCA platforms. Dazz collapsed that noise into what actually needed fixing.
Dazz raised $110 million in total funding before the Wiz acquisition and had built a customer base of enterprises that needed to move beyond passive vulnerability management toward automated remediation at scale.
Capabilities (historical)
Root cause analysis engine
The core differentiator was Dazz’s patented root cause analysis. Most security tools told you what was vulnerable. Dazz traced back to where in the code a vulnerability was introduced.
A single misconfigured base image might produce:
- 40 container vulnerability alerts
- 15 SCA findings across dependent services
- 8 cloud security posture findings
- 3 runtime detection alerts
Dazz collapsed all 66 alerts into one root cause — the base image selection in a Dockerfile. Fix the Dockerfile, and all 66 findings resolved together.
AI-powered remediation
Dazz generated actionable fixes rather than just surfacing findings:
| Capability | How it worked |
|---|---|
| Automated code fixes | AI generated specific code changes for container vulnerabilities and common code issues |
| Pull request creation | Remediation was delivered as a pull request with context explaining the fix and which alerts it resolved |
| Remediation guidance | For issues that could not be auto-fixed, the platform provided step-by-step guidance tailored to the stack |
| Fix validation | Tracked whether applied fixes actually resolved the underlying findings |
Workstreams
Dazz Workstreams let security teams organize remediation efforts around business priorities:
- Group findings by application, team, compliance deadline, or custom logic
- Track remediation progress against SLAs
- Respond to zero-day disclosures by organizing affected findings into a dedicated workstream
- Measure team velocity and identify bottlenecks
When a new zero-day landed, security teams could spin up a workstream that automatically gathered every affected finding, assigned them to the right teams, and tracked progress toward resolution.
Runtime exploitability
The platform prioritized based on real-world risk, not just theoretical severity:
| Factor | What it considered |
|---|---|
| Runtime exposure | Was the vulnerable component actually loaded and reachable in production? |
| Network path | Was there a network path from the internet to the vulnerable service? |
| Data sensitivity | Did the vulnerable service handle PII, financial data, or credentials? |
| Compensating controls | Were there WAF rules, network policies, or other controls mitigating the risk? |
A critical CVE in a library that was included in the build but never loaded at runtime got deprioritized compared to a high-severity finding in a public-facing service handling payment data.
Cross-tool correlation
Dazz normalized findings from diverse security tools into a single taxonomy:
Wiz
Snyk
Prisma Cloud
CrowdStrike
AWS Security Hub
Checkmarx
GitHub
GitLab
Jira
ServiceNow
SlackDazz alternatives and modern replacements
Five tools cover the territory standalone Dazz used to own.
- Wiz Exposure Management — The natural successor for cloud-heavy use cases. Wiz XM inherited Dazz’s root cause analysis and remediation engine and ships them with Wiz’s cloud security graph as a single product.
- Apiiro — Better fit if your stack is code-first rather than cloud-first. Apiiro’s Risk Graph does similar correlation and prioritization with stronger pre-commit AppSec coverage.
- ArmorCode — Better fit if you want correlation and remediation orchestration across 320+ scanners without bundling cloud security. Pure ASPM, no CNAPP overlap.
- Cycode — Better fit if you want native scanning (SAST/SCA/secrets) plus ASPM correlation in one platform.
- OX Security — Better fit if you want Active ASPM with PBOM-style supply chain context plus remediation playbooks.
The full ASPM hub lists every active platform if you need a wider scan.
Where to evaluate now
Net-new buyers should evaluate Wiz Exposure Management (XM) — the public-preview product that ships Dazz’s root cause analysis and remediation engine inside Wiz’s cloud security graph. The remediation logic is the same; what changes is that Wiz XM is integrated rather than agnostic, so evaluation makes the most sense for teams already standardizing on Wiz for CNAPP.
If standalone, scanner-agnostic remediation is the requirement, the alternatives section above lists the closest active replacements (ArmorCode, Apiiro, OX Security, Cycode).
