Metrics to Measure AppSec Testing Program Success

What gets measured gets funded.

But metrics can do more than just prove ROI. They’re how you position AppSec as a business enabler rather than a bottleneck. That distinction matters more than ever as AI-accelerated development pushes code velocity to levels that would’ve seemed impossible a few years ago.

We’ve seen DAST programs stall not because the technology failed, but because teams couldn’t demonstrate impact. Leadership didn’t see how security testing connected to shipping faster, reducing incidents, or managing risk at scale. Without that visibility, programs plateau—or worse, get deprioritized when budgets tighten.

The solution is a success metrics framework organized around three questions your program needs to answer:

1. “Are we testing what matters?”
2. “Are we actually reducing application risk?”
3. “Are we scaling effectively?”

While this framework can apply to any AppSec testing program, it’s especially critical for DAST. Dynamic testing requires more infrastructure, configuration, and cross-team coordination than static analysis, which means more ways for programs to stall, and more need to prove the investment is paying off.

The 3 Categories of Success Metrics

1: Coverage & Adoption Metrics

“Are we testing what matters?”

These metrics tell you whether your program is actually reaching the applications that need testing. It’s easy to run and track scans. It’s harder to ensure you’re scanning the right things and scanning them consistently.

Coverage metrics matter because they’re your leading indicators. If adoption is stalling, you’ll see it here before vulnerabilities start slipping through. They also help you identify gaps: maybe you’ve got great coverage on new microservices, but legacy apps remain untested.

For executive reporting, coverage metrics answer a fundamental question: what percentage of our attack surface is under active security testing?

Example coverage & adoption metrics:

• Testing Coverage Rate: % of high-risk apps under active testing
• Application Onboarding Velocity: # of new apps onboarded per month
• Scan Frequency: Average scans per application per week
• CI/CD Integration Rate: % of apps with automated scanning in pipelines
• Audit Readiness Score: % of apps meeting compliance requirements

2: Risk Reduction Metrics

“Are we actually reducing application risk?”

This is where you prove the value of shift-left runtime testing. Coverage is necessary but not sufficient. What matters is whether you’re actually catching and fixing vulnerabilities before they reach production.

Risk reduction metrics are your lagging or outcome metrics. They answer the question leadership actually cares about: Is our application security posture improving? They also help you make the business case for continued investment. A program that catches 80% of vulnerabilities pre-production and reduces mean time to remediation (MTTR) by 40% is a program that earns its budget.

These metrics also surface process problems. If you’re finding vulnerabilities but remediation rates are low, you’ve got a workflow issue. If MTTR is climbing, something’s blocking developers from fixing what you find.

Example risk reduction metrics:

• Pre-Production Detection Rate: % of vulnerabilities caught before production
• Vulnerability Trend: Critical/High findings discovered over time
• Mean Time to Remediation (MTTR): Days from discovery to fix, by severity
• Remediation Rate: % of identified vulnerabilities fixed within SLA
• Production Incidents Prevented: Estimated vulnerabilities that would have reached production

3: Efficiency & Health Metrics

“Are we scaling effectively?”

These metrics tell you whether your paved road is actually working. You can have great coverage and strong risk reduction, but if it requires heroic effort from your AppSec team, it won’t last.

Efficiency metrics matter because they determine sustainability. A program that requires AppSec engineers to hand-hold every onboarding will plateau. A program where developers self-serve and scans run fast enough to stay in CI/CD will scale indefinitely.

These metrics also protect developer experience. If scan times creep up or false positive rates climb, developers will find workarounds (and hurt your coverage and risk reduction metrics). Tracking efficiency keeps you honest about whether security testing is a source of friction or flow.

Example efficiency & health metrics:

• AppSec Team Leverage: Applications per AppSec FTE
• Developer Self-Service Rate: % of onboarding done without AppSec help
• Scan Duration: Average time per scan
• Developer Satisfaction: NPS or survey scores on security tooling
• Time to Market Impact: Days saved vs. manual security reviews

Best Practices for Defining Your Metrics That Matter

Match metrics to audience. Executives need coverage rates and risk reduction trends. AppSec teams need operational metrics like scan duration and false positive rates. Dev teams need efficiency rates like time to market and developer satisfaction scores.

Tie metrics to business outcomes. Don’t just say “we scanned 50 applications.” Say “we prevented 12 high-severity vulnerabilities from reaching production, avoiding potential incidents that could have impacted customer trust.”

Show trends, not snapshots. A single number lacks context. Month-over-month and quarter-over-quarter trends tell a story about whether your program is improving.

Lead with what’s working. Celebrate fixes publicly, not just report vulnerabilities. Positive framing builds support; leading with problems puts leadership on the defensive.

Keep it tight for executives. Board-level reporting should fit on one page: coverage rate, risk reduction trend, and one efficiency metric. Save the operational details for your AppSec team reviews.

Start Simple, Evolve Over Time

Don’t let metrics become a project unto themselves. You don’t need to track all 15 metrics from day one. Start with what matters for your current implementation phase, and as your program matures, add sophistication:

• During pilot: Focus on proving the concept works through activity and efficiency metrics. Track scan duration, developer feedback, and vulnerabilities found/fixed. Keep it simple with 3-5 metrics maximum.
• During scale: Add coverage and adoption metrics. You need to show the program is expanding, not just working for a handful of apps. This is also when risk reduction metrics become critical to justify your investment.
• At maturity: Layer in trend analysis and business impact metrics. Leadership wants to see quarter-over-quarter improvement and ROI calculations. Be sure to keep an eye on efficiency as well to ensure your program doesn’t lose steam.

No matter your phase, always keep the focus on metrics that drive decisions, not just metrics that fill slides.

The right metrics don’t just measure your program—they improve it.

To get the full metrics and benchmarks, download our SOAR Framework for Scaling DAST.