See your real exposure. Resolve it where it actually lives.
Scanners produce findings. GRC platforms log them. Neither tells you which applications are actually deployed, who currently owns them, or whether the fix is already in flight. DevGrid is the engineering graph that turns scanner output into action your teams can actually route, verify, and close.
Exposure is an engineering problem before it’s a security problem.
Every enterprise has the same secret: nobody trusts the asset inventory. Scanners report on services that no longer exist. CVE alerts route to engineers who left last quarter. Compensating controls map to a CMDB that was wrong the day it was published.
And then, when a high-profile CVE drops on a Monday, three different teams produce three different blast-radius answers in three different spreadsheets. And the regulator wants the fourth one by Friday.
You don’t have a vulnerability problem. You have a “you can’t see what you have” problem. DevGrid fixes that, and everything downstream of it.
Four steps. One graph. No new tool.
DevGrid's threat exposure pipeline doesn't replace your security stack — it threads the engineering graph through it. The four verbs that make every scanner, every owner, and every audit response actually work together.
Built on top of the tools you already run. No agents. No rip-and-replace. No second source of truth.
Your asset inventory
DevGrid sits on top of your Git, CI/CD, cloud, scanners, and on-call systems — and continuously maps every service, dependency, runtime, and accountable team into a live engineering graph. The CMDB stops being fiction. The service catalog stops being a graveyard. And ownership actually stays current.
- Continuous service inventory from real systems — not surveys
- Live SBOM and dependency lineage
- Owner mapping that updates when people, teams, and services move
- Runtime presence: what’s actually deployed, not what was deployed last year
Scanner noise, resolved.
Most “critical” vulnerability tickets target a service that was retired, an owner who left, or a vulnerability already remediated upstream. DevGrid applies engineering context — runtime presence, ownership, change history, control coverage — to every scanner finding, so engineering only sees what is still real, still owned, and still open.
- Cross-scanner normalization (open source, AppSec, infra, license, cloud)
- Engineering-context scoring on top of CVSS / vendor scores
- Compensating-control coverage view: what’s protected, what’s exposed
- De-duplication of overlapping findings across tools
Real findings to real humans.
The engineering graph already knows who currently owns each service. DevGrid uses that to route every real exposure to the right team, attach the relevant change-set and runbook, and open the ticket in the system they already work in. No more bouncing aliases. No more “this isn’t my service anymore.”
- Integration with ServiceNow, Jira, and your GRC platform
- Tickets routed to current, named owners — not last quarter’s roster
- Change-set, runbook, and dependency context attached to every ticket
- SLA tracking against your existing remediation policies
payments-appOne defensible record
When the regulator asks — and they will — DevGrid produces point-in-time, drillable evidence that each finding was identified, routed, owned, remediated, and verified. The same lineage feeds your audit committee, your GRC platform, and the engineering team that did the work. One source of truth. No reconciliation required.
- Point-in-time, immutable audit lineage per finding
- Reconcile with your GRC platform
- Drillable timeline: discovery → ownership → remediation → closure
“Were you exposed to CVE-2025-31141 on May 14th, 2026? Show your work.”
Ask the graph anything. The answer is already in your data.
Every team in a regulated enterprise has the same problem: the answer to their question is somewhere in the engineering stack, but they need to wait on an engineer to find it. DevGrid’s natural-language layer lets Risk, Compliance, Audit, and Engineering query the graph directly. Same data, same lineage, every answer traceable to the system of record.
- Which services run log4j-core 2.14.x in production right now?
- Map the blast radius of CVE-2025-XXXXX across our portfolio.
- Which internet-facing services are exposed to RegreSSHion?
- Who currently owns payments-app? Who owned it three months ago?
- List every critical ticket assigned to someone who no longer works here.
- Which services are running in production without a named owner?
- Generate an evidence pack for SOC 2 covering Q3 for our top-20 services.
- Show me the audit lineage for finding F-2026-2934.
- Which services have a SOC 2 control gap, grouped by team?
- Which services still depend on Java 8 in production?
- List every EOL component with an active audit finding.
- Show EOL exposure across our top-20 critical applications.
- Which services have a change failure rate above 15% this quarter?
- Compare MTTR across tier-1 services for the last 90 days.
- Show me services that missed deployment-frequency SLA.
- Which compensating controls cover internet-exposed services?
- Show me services where the EDR agent stopped reporting > 48 hours ago.
- Map every active CVE to its current compensating control.
Plug into Claude, Codex, Cursor, GitHub Copilot, or whatever your engineers already use.
DevGrid doesn’t write the fix. Your AI coding tools do — and they do it better when they have the engineering context they’ve been missing. DevGrid feeds Claude, Codex, Cursor, GitHub Copilot, and any other coding agent the same live engineering graph that powers everything else on this page: current ownership, runtime presence, dependency lineage, change history, and the exposure context that turns a generic CVE into a specific, actionable PR.
The output: AI-drafted fixes that target the right service, in the right repo, with tests, routed to the right human for review. Resolution closure flows back into the audit lineage automatically — without anyone having to update a spreadsheet.
- Plug into any AI coding tool via MCP, API, or native integration
- Live engineering context (ownership, runtime, dependencies, change history) feeds the agent as input
- AI-drafted PRs include the original exposure context and verification path
- Resolution closure feeds back into audit lineage automatically
Claude
Codex
Cursor
GitHub CopilotThe exploit isn’t a single CVE. It’s the combination.
The next class of breach won’t come from a CVE your scanner missed. It’ll come from two technologies you have running side-by-side that no single-system scan can put together. The risk isn’t a single vulnerability — it’s the composite. The chain that crosses applications, owners, and tech stacks. Existing scanners look at one system at a time. DevGrid sees the whole graph.
| Capability | Existing tools | DevGrid |
|---|---|---|
| Single-system vuln scanning | ✓ Yes | ✓ Yes (ingested) |
| Static code analysis (one repo) | ✓ Yes | ✓ Yes (ingested) |
| “Which apps use Tech X and Tech Y?” | ~ Limited | ✓ Yes |
| Full technology inventory per app | ~ Partial | ✓ Yes |
| Inter-app dependency graph | ✗ No | ✓ Yes |
| Multi-tech combination queries | ✗ No | ✓ Yes |
| Cross-app dependency chain detection | ✗ No | ✓ Yes |
| Cross-service exploit chain detection | ✗ No | ✓ Yes |
| Toxic combination queries at portfolio scale | ✗ No | ✓ Yes |
| Owner identification + remediation routing across the chain | ✗ No | ✓ Yes |
Cross-service exposure in practice
/v1/login/authHypothetical example — a single request traverses four applications, each with its own technology stack. Each app scans clean on its own.
| Stack layer | App A · gateway | App B · session-api | App C · auth-engine | App D · audit-log |
|---|---|---|---|---|
| Operating system | Linux (RHEL 8) | Linux (RHEL 8) | Red Hat 7 | Linux (RHEL 8) |
| Runtime | Java 11 | Node.js 18 | Python 3.9 | Java 17 |
| Framework | Spring Boot 2.7 | Express.js 4.x | Flask 2.3 | Spring Boot 3.1 |
| Web server | Embedded Tomcat | Nginx 1.24 | Gunicorn | Embedded Tomcat |
| Auth library | OAuth2 Client | Passport.js | PyJWT | Spring Security |
| Logging | Log4j 2.20 | Winston 3.x | structlog | Logback 1.4 |
| Container base | distroless | node:18-slim | python:3.9-rhel7 | distroless |
*Hypothetical example for illustration purposes only. We are not declaring vulnerabilities in any of these technologies.
The next named CVE drops. Where do you stand?
Every regulated institution runs the same 72-hour scramble when a high-profile CVE makes the news. Slack channels light up. War rooms convene. Engineering leaders are asked the question they cannot answer fast: are we exposed?
Already have scanners? Vulnerability tools? A GRC platform? Good.
DevGrid is not a replacement for your security stack. It is the engineering substrate underneath it. Your vulnerability scanners, AppSec tools, and cloud-security posture tools produce findings — DevGrid binds those findings to live ownership, runtime presence, change history, and dependency lineage, then routes the resulting action back into the tools your engineering, risk, compliance, and audit teams already use.
Sources of findings
change history · dependency lineage
Consumers of truth
Stop chasing exposure.
Start resolving it.
The engineering graph that turns scanner output into action you can actually close.