How to Measure the Success of Your Security Champions Program

Attendance looks fine, a few trainings shipped, a Slack channel hums once in a while, yet critical findings keep repeating, remediation cycles drag, and product leaders keep asking what they’re paying for.

The thing is, you’re not short on effort, but you’re short on proof that the program changes developer behavior, shrinks real risk, and speeds releases that used to stall on the same categories of defects.

Pressure is climbing now because scrutiny is everywhere. Finance wants ROI that can stand up in a quarterly review, engineering leaders want fewer blocking issues with faster cycle time, and the board wants evidence that risk exposure is moving in the right direction. A Security Champions program that cannot show movement on leak rates, time to remediate, and recurrence of the top five defect types will get deprioritized or cut, and the next incident review will name that gap plainly.

And it isn’t about the lack of enthusiasm. The problem is that vague engagement metrics hide operational drag and mask where the program is misaligned with delivery reality. Counting volunteers and training hours says nothing about pull request quality, threat modeling depth in the teams that matter most, or the burn-down of backlog items that map to material business risk. You need metrics with teeth, tied directly to engineering workflows and to the risk register, not vanity numbers that read well and defend nothing.

Table of Contents

1. Why most security champions programs become stale
2. Success looks like measurable risk reduction tied to delivery
3. Key metrics to track (and what they tell you)
4. Are you building advocates or assigning homework?
5. Making the program sustainable (and actually useful to engineering)
6. A Security Champions program as an engineering capability

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Why most security champions programs become stale

A lot of Security Champions programs only start strong. The intent is solid, people are willing, yet the day-to-day reality of shipping code eventually overpowers an initiative that is not tightly connected to how engineers actually work.

Momentum fades quietly, then leaders notice that risk trends stayed the same while the program consumed time and attention.

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Expectations are unclear and the role feels optional

Many programs give Security Champions a title and a general mission, then hope the impact shows up on its own. Champions attend sessions, share reminders, and try to help, but none of it connects to actual SDLC checkpoints. And when responsibilities are not tied to specific artifacts or behaviors in the pipeline, the program turns into a chore they hate.

Security Champions need defined ownership inside engineering work. Threat modeling for their service, review of security-sensitive PRs, early triage of vulnerabilities, and clear time allocation must be documented and supported by their managers. 

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No feedback loop shows whether the work matters

Security Champions want to see that their actions change something measurable, and leaders need the same. Programs often track attendance, training hours, or message volume, which gives no visibility into whether security defects are shrinking or remediation is speeding up. No wonder engineers lose interest because nothing proves that their effort improves outcomes.

You need metrics that connect Security Champion work to real movement. Recurrence rate of top vulnerability classes, time to remediate for Champion-owned repos, policy pass rates in CI, and changes in critical findings across releases all provide a simple loop that shows cause and effect.

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Participation looks active but impact stays flat

Many programs shift into a pattern where Security Champions show up but nothing changes in the code. Training happens, Slack channels stay busy, and dashboards look full, but why do the same vulnerabilities appear every quarter? This is token participation, and it is one of the clearest signs the program is drifting.

Enablement has to live inside the workflow. CI checks, PR templates with lightweight threat prompts, tuned SAST and SCA rules, and clear code owner boundaries give them tools that influence daily development.

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Alignment with risk and delivery pressure breaks down

Programs stop working when they treat all teams equally and ignore where the real risk sits. Security Champions get spread thin, the highest-risk services receive minimal attention, and security interventions fail to match engineering cadence. And as usual, release pressure takes priority, and Security Champions cannot influence work that is already mid-flight.

Anchor the program to the risk register and to sprint schedules. Assign Champions to high-impact services, sync their responsibilities with release cycles, and ensure their work shows up in backlogs and planning discussions. Alignment creates relevance, and relevance drives adoption.

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Signs your program is heading toward failure

Leaders can confirm trouble quickly by watching a few concrete indicators.

• Participation stays steady while risk metrics stay flat. Critical findings, remediation time, and defect recurrence look the same every quarter.
• Repeated vulnerabilities show up in consecutive releases, which signals that training exists but code behavior did not change.
• No measurable influence appears in delivery metrics for Champion teams. Rollbacks and security hotfixes maintain the same frequency.
• Tool signal stays noisy, suppression grows, and engineers stop engaging with findings.
• Audit findings recur in the same areas even though the program claims coverage.

Most programs that don't work follow this same pattern. The program loses contact with engineering reality, the work becomes symbolic, and no metric shows movement. The good news is that the issues are fixable when leaders recognize them early and refocus on observable behaviors that reduce risk and improve delivery quality.

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Success looks like measurable risk reduction tied to delivery

A program that actually works produces fewer severe findings, tighter review patterns, and faster remediation cycles, and it should create technical signals you can point to without a long explanation. You’re basically laying out exactly what good looks like, why it matters, and how to confirm it in a few minutes of inspection.

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Pull requests show consistent and verifiable security coverage

You should be able to open a PR history for any Security Champion-owned service and immediately see security behaviors that changed how the code was written or reviewed.

• PRs include explicit security artifacts, such as threat notes, references to required controls, structured risk comments, or linked tickets that track mitigations tied to specific vulnerabilities.
• CI policies enforce security checks with predictable pass rates. SAST, SCA, secrets scanning, IaC rules, container scanning, and dependency policies should run automatically.
• Code owner rules flag critical directories and enforcement should ensure a Security Champion review lands on any change touching authentication, cryptography, secrets handling, or data access logic.
• Prevented vulnerabilities are captured as part of normal workflow. Review comments that identify a risk, followed by a code correction before merge, create a measurable signal.

A mature program shows these signals without prompting, and the engineering team treats them as normal practice rather than an extra layer.

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Critical and high-risk issues decline in a measurable way

Risk metrics tell a cleaner story than participation counts. Leaders want to know whether severe issues are shrinking and whether the program changed behavior in the repositories that matter.

• A 20 to 40 percent decline in Champion-owned services across two or three quarters is a strong indicator that guidance and tooling changes reached the right parts of the codebase.
• When SSRF, deserialization flaws, injection issues, or misconfigurations stop appearing in consecutive sprints, you know the preventive work is taking hold.
• Tracking by KLOC or active contributor count gives you a clean comparison across teams and surfaces where deeper intervention is needed.

When these numbers move, you’re seeing the outcome of tighter practices, tuned tooling, and more consistent developer involvement.

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Remediation cycles accelerate in Champion-owned teams

Nothing builds engineering credibility faster than reducing the long tail of open issues and speeding up the fix cycle without hurting delivery. Champions should influence triage, prioritization, and execution.

• Median time matters more than mean here because outliers distort the picture. Success looks like faster cycles every quarter, supported by cleaner feature branches and fewer.
• Critical and high issues older than 30 days should drop significantly once Security Champions take responsibility for triage and coordination with engineering leads.
• The time between detection, code change, and a green build that passes all security gates should get shorter as teams adopt clearer patterns and better testing.

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Champions drive security conversations before decisions get locked in

A fully functioning program turns Security Champions into multipliers. They should initiate reviews, propose design considerations, and point out risks early enough that engineers can correct course without rework.

• They initiate design reviews for features touching sensitive data or privileged workflows. These reviews should produce short decision records that link back to requirement updates, mitigations, or architectural changes.
• They also run targeted micro-trainings based on real defects. When the same flaw repeats, a Security Champion should deliver a short session using examples from the team’s own codebase.
• Champions lead structured threat modeling for services with high data sensitivity or complex integration paths. Participation should focus on the systems that carry the greatest business impact.

These behaviors show that security is embedded in the engineering culture instead of layered on after the fact.

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Key metrics to track (and what they tell you)

You want numbers that hold up in a budget review and in an engineering standup. The list below gives you exactly what to track, how to capture it, and what the signals mean.

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Vulnerability trends by Security Champion cohort

This is the anchor comparison that shows whether the program reduces real risk. Measure the same set of outcomes for Champion-owned repositories and for a matched set without Champions, then watch the spread over time.

Critical and high findings per release

• How to track: Pull issue counts from SAST, SCA, container, cloud, and IaC scanners, scoped to production services. Segment by repository and service ownership.
• Calculation: Findings of severity critical or high divided by number of releases in the period (or by KLOC for normalization).
• Cadence: Monthly rollup with a 90-day view, plus a quarter-over-quarter trend.
• What it tells you: Whether Security Champions are driving down severe issues where it matters most. A widening gap in favor of their teams signals effective prevention and review.

Recurrence rate for top vulnerability classes

• How to track: Tag findings by CWE or vendor rule category for the top five classes that matter to your stack.
• Calculation: Count of repeated occurrences in the same repo within 60 or 90 days divided by total occurrences.
• Cadence: Quarterly.
• What it tells you: Whether targeted guidance, rules, and patterns are sticking. A falling recurrence rate shows durable behavior change.

Mean and median time to remediate by severity

• How to track: Join scanner timestamps, ticket creation, PR merge, and deployment events.
• Calculation: Detection to production fix, reported as mean and median for critical and high severities.
• Cadence: Monthly with quarterly trend.
• What it tells you: Whether Champions accelerate the fix flow without harming throughput. Medians are the sanity check when a few long-running items skew the mean.

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Secure development signals in pull requests

Security maturity should be visible in everyday code review. Look for consistent artifacts and behaviors in PRs from Champion teams and measure them the same way every time.

PRs with explicit security artifacts

• How to track: Enforce PR templates with required security fields, then query for completion.
• Calculation: Percentage of PRs with a populated threat note, linked security requirement, or mitigation ticket.
• Cadence: Monthly with service-level drill-down.
• What it tells you: Whether security considerations are entering design and review at the right moment.

Policy pass rate on first attempt

• How to track: Collect CI outcomes for SAST, SCA, secrets detection, IaC, container baseline, and license checks.
• Calculation: Percentage of PRs that pass all security gates in the first run.
• Cadence: Weekly trend smoothed monthly.
• What it tells you: Whether code quality and dependency hygiene are improving upstream rather than through retries.

Champion reviews on sensitive paths

• How to track: Use code owner rules for auth, crypto, data access, and secrets directories.
• Calculation: Percentage of PRs touching tagged paths that include a Champion review plus a senior reviewer.
• Cadence: Monthly with examples highlighted in team reviews.
• What it tells you: Whether expertise is applied where risk concentrates.

Prevented vulnerabilities pre-merge

• How to track: Label PR comments that resulted in a code change addressing a distinct risk, then auto-link to the change set.
• Calculation: Count per class per service with a rolling 90-day view.
• Cadence: Monthly.
• What it tells you: Where Champions are stopping defects before they hit main and which patterns are improving.

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Threat modeling and design review activity with outcomes

You want early conversations that change designs instead of meetings that produce notes with no effect on code.

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Threat modeling sessions initiated by Security Champions

• How to track: Log sessions as issues linked to epics and architecture decision records.
• Calculation: Count per quarter for services with high data sensitivity or complex integrations, plus percentage that resulted in a change request or control update.
• Cadence: Quarterly.
• What it tells you: Whether Security Champions are moving risk discussions to the start of work and turning them into tangible design changes.

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Design review action effectiveness

• How to track: For each review, record the recommended control and verify implementation through PR tags or CI policy updates.
• Calculation: Percentage of reviews that produced at least one merged mitigation within the same release window.
• Cadence: Quarterly.
• What it tells you: Whether design reviews translate into shipped mitigations rather than documentation.

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Training completion and applied competency

Completion is a weak signal on its own. Pair it with applied performance that reflects what engineers do on the job.

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Completion with assessment delta

• How to track: Use role-based paths with pre and post assessments mapped to your tech stack.
• Calculation: Score improvement per learner and per team across secure code, cloud, and IaC topics.
• Cadence: Quarterly.
• What it tells you: Whether learning closed real knowledge gaps.

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Challenge performance tied to code outcomes

• How to track: Run CTFs or secure code challenges that mirror your stack, then correlate performance with PR policy pass rates and reduced recurrence for matching CWEs.
• Calculation: Median challenge score per team and correlation with pipeline metrics.
• Cadence: Quarterly.
• What it tells you: Whether hands-on skill gains are showing up in day-to-day development.
• Practical note: Platforms like AppSecEngineer provide role-specific labs that map well to this kind of measurement.

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Tool engagement and feedback loops

Security Champions should be shaping the tools and rules that engineers touch every day. Measure tuning, noise reduction, and closure quality.

Rule tuning throughput and effect

• How to track: Track rule updates, suppressions with justification, and configuration changes through PRs in your policy repositories.
• Calculation: Number of tuned rules per quarter and the resulting change in false positive rate for those rules.
• Cadence: Monthly with quarterly summary.
• What it tells you: Whether Security Champions are reducing noise and increasing developer trust in findings.

Alert closure quality

• How to track: Sample closed alerts and categorize as fixed in code, configuration change, accepted risk with expiration, or invalid suppression.
• Calculation: Percentage of closures that represent durable fixes versus administrative actions.
• Cadence: Monthly sampling.
• What it tells you: Whether teams are actually removing risk.

Mean time to first action on new alerts

• How to track: From detection to first triage activity, pulled from scanner webhooks and ticket updates.
• Calculation: Median hours to first action by severity.
• Cadence: Weekly trend.
• What it tells you: Whether Security Champions are triggering fast triage and keeping queues healthy.

Policy exception velocity and age

• How to track: Store exceptions as code with required owners and expiry dates.
• Calculation: Number created, average age, and percentage that expire and close on schedule.
• Cadence: Monthly.
• What it tells you: Whether risk debt is being paid down rather than rolling forward.

Track these KPIs with the same care you give throughput and reliability. You will know where Security Champions are moving the needle, which services need deeper coverage, and which rules or trainings deserve another round of tuning.

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Are you building advocates or assigning homework?

You want Security Champions who make decisions, change designs, and carry outcomes across sprints. A mature program treats them as accountable owners inside the SDLC. On the other hand, an immature program hands them reminders and asks them to push messages across Slack. The difference is obvious when you look at who leads the work, where decisions get recorded, and how consistently engineering teams act on those decisions.

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What mature programs look like in day-to-day engineering

Security Champions operate with defined authority, visible artifacts, and tight alignment to risk. You can open your repos, your runbooks, and your incident records and see their fingerprints without hunting.

1. They own the analysis timeline, write the contributing factor list, assign mitigations with due dates, and confirm completion with merged PRs and updated policies. The record links to commits, CI runs, and updated alerts.
2. They open architecture tickets for features that touch sensitive data or privileged flows, run threat modeling with the team, document decisions in ADRs, and get sign-off from both a staff engineer and a security architect.
3. They submit PRs to central repos for SAST rule tuning, IaC baselines, dependency policies, and license allowlists, then validate reduced false positives and improved pass rates.
4. They own code owner files for sensitive paths, ensure PR templates include security prompts, and enforce branch protection rules for services with higher risk.
5. They schedule micro-trainings that address the exact CWE patterns found in recent scans, then verify effect through pre-merge prevented vulnerabilities and recurrence drops.

These behaviors turn Security Champions into multipliers who improve code quality and reduce risk without adding ceremony.

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Common failure signals you can spot in minutes

Programs that stall have Champions who relay messages, log tickets for others, and host meetings with little follow-through. The signals show up quickly when you review a release or an incident.

• Champions act as messengers. They forward scanner alerts and play traffic cop, yet do not change rules, fix code, or close the loop with a verified mitigation.Decisions happen elsewhere. Design calls get resolved in private threads or leadership meetings, and no ADR or ticket shows Champion involvement.
• No policy ownership. Security rules live with platform teams or vendors, and Champions lack permission or time to propose and validate changes.
• Artifacts do not exist where engineers work. Threat models live in scattered documents, training records sit in a vendor portal, and PRs contain no security fields or references.
• Post-mortems generate tasks without verification. Tickets close due to status aging, not merged code or passing policies, and the same vulnerability class returns in the next release.

These patterns indicate a program that assigns homework rather than authority.

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Making the program sustainable (and actually useful to engineering)

Sustainability comes from treating security as normal delivery work. Champions become reliable partners when their responsibilities show up in sprint plans, in PR reviews, and in retros, using the same tools engineers already trust. The goal is a program that moves on its own because the work is defined, automated where possible, and measured in the same cadence as throughput and reliability.

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Embed security in planning, standups, and retros

Plan security activity with the same precision you use for features. Champions need time, artifacts, and clear acceptance criteria that engineering leaders can inspect without extra dashboards.

Sprint planning

• Pull a small, prioritized security backlog into every sprint. Focus on high-impact items such as refactoring a risky authentication path, rotating secrets, or fixing the top recurring CWE in that service.
• Add security acceptance criteria to user stories that touch sensitive data, auth, crypto, or external integrations. Examples include “no secrets in diff,” “no direct SQL string building,” “TLS pinning verified,” and “new endpoint covered by abuse cases.”
• Reserve capacity for rule tuning. Track one or two policy changes per sprint for SAST, SCA, IaC, or container baselines, then confirm impact through first-pass policy success rates.

Daily standups

• Champions call out security blockers next to functional ones. Treat a failing CI policy or noisy rule as a delivery concern, not an optional task.
• Keep a short list of hot spots. Services with recent incidents or audit findings get Champion attention until trend lines improve.

Retrospectives

• Review three security metrics alongside DORA: critical and high findings per release, median time to remediate, and policy first-pass rates.
• Record one improvement action with an owner and a due date. Examples include enabling code owners on a sensitive directory or adding a secrets pre-commit hook.

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Turn PR reviews into predictable security coverage

PRs are where decisions stick. Champions should influence reviews through templates, ownership rules, and checks that run without manual orchestration.

• Use PR templates with required security prompts. Ask for threat notes, data classification touched, and links to any relevant ADRs. The goal is a lightweight artifact that prompts the right thinking and gives reviewers context.
• Configure code owners for sensitive paths. Changes under auth, crypto, secrets handling, and data access should request a Champion review and a senior engineer by default.
• Run policy as code in CI. Enforce SAST, SCA, secrets detection, IaC, container scanning, and license checks with clear pass and fail criteria. Track first-pass rates and tune rules when failures cluster.
• Capture prevented vulnerabilities. Label review comments that resulted in a code change before merge and tag the CWE or rule category. This gives you a clean signal of pre-merge prevention without extra process.
• Add minimal guardrails for risky patterns. Pre-commit hooks for secrets and IaC, lints for unsafe APIs, and denied patterns for common injection vectors keep bad changes from reaching review at all.

Tools matter here, but so does fit. Many teams use native GitHub or GitLab features, plus dedicated scanners. Add targeted automation such as SecurityReview.AI to surface risky diffs in PRs and reduce reviewer fatigue.

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Use hands-on enablement that maps directly to the stack

Champions learn faster when training looks like their day job. Long workshops produce weak signals. Short, focused labs paired with code reviews produce durable results.

• Run role-based labs aligned to your languages, frameworks, and cloud provider. Map each lab to a policy or a rule you enforce in CI, then measure impact through improved first-pass rates and reduced recurrence for matching CWEs. AppSecEngineer.com is strong here because labs mirror real stacks and export assessment data you can join with pipeline metrics.
• Pair on live changes. Schedule one or two pairing sessions per sprint on security-sensitive features. The Champion and a senior engineer walk through the threat note, validate tests, and confirm CI passes with the updated rules.
• Build micro playbooks next to code. Store short guides in the repo that explain how to fix a class of issues, how to rotate credentials, or how to update a dependency safely. Reference these in PR templates and ADRs.
• Close the loop with metrics. After targeted training or rule tuning, review first-pass policy rates and recurrence in the next two sprints. Keep what works and drop what does not.

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A Security Champions program as an engineering capability

Security Champions programs tend to fail quietly, and it's not even because the idea is flawed, but because leaders mistake activity for leverage. The real risk is assuming that goodwill and participation will eventually translate into impact. That assumption breaks down fast once delivery pressure rises and security decisions compete with roadmap commitments.

On the other hand, secure development expectations are moving closer to release accountability, audits are demanding evidence inside pipelines, and engineering leaders are pushing back on any initiative that does not shorten feedback loops. Security Champions who lack authority, data, and workflow integration will get sidelined. And Security Champions who operate with ownership and measurable outcomes will shape how products ship.

So here's an idea: Treat your Champions program as an engineering capability instead of a security initiative. Fund it like one, measure it like one, and give it decision rights that map to risk. 

If you want to move faster on that transition, AppSecEngineer’s Security Champions program is designed to plug directly into engineering workflows. It combines hands-on and stack-specific training with measurable outcomes, so your people can build real capability and leaders get defensible signals that map to risk and delivery. It works best as the next conversation for teams ready to turn intent into execution.