DevSecOps Statistics 2026: Shift-Left & AppSec Trends

DevSecOps statistics for 2026 show that organizations are embedding security earlier in software delivery through shift-left testing, SAST, SCA, secrets scanning, IaC scanning, container checks, and CI/CD controls. But the core issue is no longer only whether teams have security tools. The larger question is whether high-risk findings are prioritized, fixed, retested, and prevented from recurring.

Recent AppSec and software supply chain research shows that many teams still carry security debt, outdated dependencies, long-lived credentials, slow remediation cycles, and high-risk vulnerabilities. Shift-left security helps teams find issues earlier, but it does not automatically eliminate runtime risk, API authorization flaws, cloud misconfiguration, CI/CD exposure, or business logic weaknesses.

This report uses publicly available 2024-2026 research and labels each statistic by data type. The goal is to help CISOs, AppSec leaders, DevSecOps teams, engineering leaders, and product security teams turn raw statistics into a practical validation roadmap.

Methodology note

This 2026 guide combines DevSecOps-specific research, application security reports, software supply chain studies, cloud-native security research, secure SDLC guidance, and testing trend data. Each statistic is labeled by data type so general AppSec or cloud-security benchmarks are not treated as DevSecOps-only evidence. Where a statistic is not DevSecOps-specific, it is used only as context for DevSecOps risk and maturity. Source pages and report editions should be checked during final editorial review so the published article points to the latest available source.

Top DevSecOps Statistics for 2026

Statistic	Data type	What it shows	DevSecOps implication	Source
82% of organizations have security debt	DevSecOps / AppSec benchmark	Most teams carry unresolved critical risk.	Shift-left tools alone do not eliminate risk. Teams need ownership, remediation SLAs, and retesting.	Veracode State of Software Security
36% year-over-year surge in high-risk vulnerabilities	DevSecOps / AppSec benchmark	More flaws combine high severity with exploitability.	Prioritization should be based on exploitability and business impact, not alert volume.	Veracode State of Software Security
74% of codebases contain at least one high-risk open source vulnerability	Software supply chain benchmark	Open source risk remains common in modern applications.	SCA coverage, dependency governance, and exploitability review should be core DevSecOps controls.	Synopsys OSSRA
91% of codebases use components more than 10 versions behind	Software supply chain benchmark	Many dependencies are stale or unsupported.	Teams need automated dependency updates and clear upgrade policies.	Synopsys OSSRA
38% of AWS deployments rely on manual operations	Cloud-native benchmark	Automation gaps still exist in cloud delivery.	Manual operations can bypass security checks and create inconsistent controls.	Datadog State of DevSecOps
63% of organizations have used long-lived credentials in CI/CD pipelines	Cloud-native / pipeline benchmark	Secrets management remains a CI/CD risk.	Teams should reduce long-lived secrets, rotate keys, and use short-lived workload identity where possible.	Datadog State of DevSecOps
71% of AWS organizations and 55% of GCP organizations are adopting infrastructure as code	Cloud-native benchmark	IaC adoption is growing across cloud teams.	IaC enables shift-left infrastructure security, but insecure templates can deploy risk at scale.	Datadog State of DevSecOps
45% of organizations replaced a vulnerable build component in 2024	Software supply chain survey	Vulnerable components affect real build pipelines.	SBOMs, SCA, package governance, and build validation should be part of DevSecOps.	Snyk Open Source Security Report
52% of teams often miss vulnerability SLA deadlines	AppSec remediation benchmark	Finding vulnerabilities is easier than fixing them on time.	DevSecOps maturity depends on remediation workflow, ownership, and retest discipline.	Snyk Open Source Security Report
97% of organizations use or plan to use AI in the SDLC	DevSecOps / developer survey	AI-assisted development is becoming mainstream.	AI-generated code and dependencies still need review, scanning, and manual validation.	GitLab Global DevSecOps Survey
156% year-over-year rise in malicious open source packages	Software supply chain benchmark	Package ecosystems are increasingly abused.	DevSecOps teams need package allowlists, dependency trust controls, and registry monitoring.	Sonatype State of the Software Supply Chain
80% of application dependencies remain un-upgraded for more than one year	Software supply chain benchmark	Dependency drift is a major process weakness.	Known vulnerabilities often persist because upgrade discipline is weak.	Sonatype State of the Software Supply Chain
35 days average MTTR for a critical web application vulnerability	AppSec benchmark	Critical web vulnerabilities can remain open for more than a month.	MTTR should be a board-visible AppSec metric for critical applications.	Edgescan Vulnerability Statistics Report
More than 50% of teams run SAST in CI/CD pipelines	DevSecOps testing benchmark	Static analysis is now common in pipelines.	Adoption is not the same as maturity. Teams still need triage, fix ownership, and validation.	Practical DevSecOps

These statistics show that DevSecOps maturity is not measured by tool count. The decisive question is whether high-risk findings move from detection to remediation and validation. If SAST, SCA, IaC scanning, and secrets scanning produce alerts that are not triaged or fixed, the program creates visibility without meaningful risk reduction.

Shift-left security works best when findings are actionable, assigned to an owner, prioritized by exploitability, and retested after remediation. The most important statistics are tied to real gaps: vulnerable dependencies, alert fatigue, unresolved findings, API flaws, cloud/IaC exposure, secrets leakage, CI/CD risk, and weak retesting discipline.

What Counts as DevSecOps?

DevSecOps is the integration of security into the software development lifecycle. It combines people, process, tooling, and validation so security is designed, tested, fixed, and measured throughout delivery instead of added after release.

A mature DevSecOps program includes threat modeling, secure coding, automated testing, manual testing, build-time checks, deployment gates, runtime monitoring, remediation workflow, retesting, and feedback loops into engineering teams.

DevOps focuses on collaboration and automation for faster delivery. DevSecOps adds security into that delivery system.
AppSec focuses on application security testing and remediation. DevSecOps embeds AppSec practices into the development and deployment pipeline.
Product security covers the broader security of a product, including architecture, abuse cases, cloud, data, integrations, and operational controls.
Secure SDLC is the formal secure development process. DevSecOps is the continuous, automated, and engineering-integrated version of that process.
Shift-left security moves security earlier into planning, coding, pull requests, and CI/CD.
Shift-right security validates what is deployed through monitoring, runtime checks, pentesting, and production-like testing.
Continuous penetration testing brings recurring security validation into fast-moving delivery cycles.
Software supply chain security protects dependencies, build systems, artifacts, registries, and deployment paths.

Why DevSecOps Matters in 2026

DevSecOps matters because modern applications change faster than traditional security testing cycles. Cloud-native architecture, APIs, third-party packages, AI-assisted coding, containerized workloads, and infrastructure as code all expand the attack surface. Security teams need controls that fit developer workflows and validation that proves risk is actually reduced.

DevSecOps risk area	Why it matters	Common failure mode
Open source dependencies	Modern apps depend heavily on third-party code.	Vulnerable, stale, abandoned, or malicious packages enter production.
APIs	APIs expose business logic and sensitive data directly.	Broken authorization, excessive data exposure, and weak token validation.
CI/CD pipelines	Pipelines control builds, tests, and deployments.	Leaked secrets, overprivileged runners, poisoned builds, weak branch protection.
Cloud and IaC	Infrastructure is defined and deployed as code.	Public storage, broad IAM permissions, insecure templates, runtime drift.
Containers	Applications depend on images, registries, and orchestrators.	Vulnerable base images, weak Kubernetes controls, exposed services.
Secrets	Tokens and keys grant direct access to systems.	Hardcoded credentials in repositories, logs, CI variables, or images.
Developer workflow	Security must work without blocking delivery unnecessarily.	Alert fatigue, unclear ownership, ignored findings, poor remediation guidance.
Manual validation	Automation misses many business logic and chained exploit paths.	Auth flaws, API abuse, multi-step attacks, and business workflow abuse remain untested.

DevSecOps Adoption Trends in 2026

1. Adoption is growing, but maturity varies

Many organizations now use SAST, SCA, DAST, secrets scanning, IaC scanning, and container scanning. But adoption is not maturity. Mature programs have ownership, SLAs, triage rules, security gates, metrics, and retesting. Immature programs have tools but no reliable path from finding to fix.

2. Shift-left security is necessary but insufficient

Shift-left reduces late-stage surprises by catching coding, dependency, and configuration issues earlier. But it can also produce noisy alerts. If teams cannot prioritize and resolve findings, shift-left becomes alert relocation rather than risk reduction.

3. Shift-right and runtime validation are becoming more important

Runtime validation finds risks that only appear when services, cloud resources, identities, APIs, and business workflows operate together. Monitoring, production-like testing, attack path validation, and retesting close gaps that shift-left tools cannot fully cover.

4. Developers need security that fits workflow

Security should appear where developers work: IDEs, pull requests, issue trackers, CI/CD gates, and architecture reviews. Findings need clear remediation guidance, owner assignment, and severity that reflects exploitability and business impact.

5. AI-assisted development changes AppSec risk

AI coding assistants can increase delivery speed, but they also require review. AI-generated code, dependency suggestions, insecure patterns, and package hallucination risk should be handled through secure code review, SCA, secrets scanning, tests, and manual validation on high-risk workflows.

DevSecOps Trends: Shift-Left, Shift-Right, AI, and Supply Chain Security

The strongest DevSecOps programs in 2026 combine early feedback with continuous validation. They use automation to catch common defects quickly, manual testing to validate business impact, and metrics to prove security debt is shrinking. The trend is not simply more tools. It is tighter integration between engineering, AppSec, cloud, platform, and product security.

Application Security Gaps in DevSecOps Programs

AppSec gap	Why it matters	Example	Validation method
Tool noise	Developers ignore low-quality alerts.	SAST reports hundreds of non-exploitable issues.	Triage by exploitability and manual review.
No ownership	Findings remain unresolved.	A critical issue is not assigned to a service owner.	Remediation workflow audit and SLA tracking.
Weak API testing	Business logic flaws are missed.	Customer API allows IDOR/BOLA access.	Manual API penetration testing.
Incomplete SCA	Transitive dependency risk remains hidden.	A vulnerable child dependency is never reviewed.	Full dependency-tree SCA and SBOM review.
Secrets exposure	Tokens enable direct access.	API key committed to GitHub or CI logs.	Secrets scanning and key rotation test.
CI/CD misconfiguration	The build pipeline becomes an attack path.	Overprivileged runner can deploy malicious code.	CI/CD security review.
Cloud/IaC gaps	Infrastructure deploys insecurely.	Terraform creates public storage or broad IAM.	IaC scanning and cloud security review.
No retesting	Fixes are assumed, not proven.	Patch deployed but exploit still works.	Remediation retest.
No threat modeling	Design flaws appear late.	Payment workflow lacks abuse controls.	Threat modeling workshop.
No manual testing	Automation misses chained risk.	Auth flaw plus API flaw creates account takeover.	Manual web/API penetration testing.

Testing Trends in DevSecOps

Testing method	Best used for	What it misses	Where it fits in DevSecOps
SAST	Code-level security patterns.	Runtime logic, exploitability, cloud context.	IDE, pull request, and CI checks.
SCA	Open source dependency and license risk.	Business logic, configuration, proprietary code flaws.	Build pipeline and dependency governance.
DAST	Runtime web testing in staging or pre-production.	Deep authorization logic, API workflows, code-level issues.	QA, staging, nightly testing.
IAST	Runtime feedback from instrumented test environments.	Paths not exercised by tests.	Test environments with representative coverage.
Secrets scanning	Hardcoded credentials and tokens.	Secrets shared outside code systems.	Pre-commit, repository, CI, and image scans.
API security testing	Authorization, token handling, workflow abuse.	Static dependency risk.	Pre-release and major API changes.
IaC scanning	Misconfigured Terraform, CloudFormation, Kubernetes manifests.	Runtime drift after deployment.	Pull request and CI gates.
Container image scanning	Vulnerable base images and layers.	Runtime cluster misconfiguration.	Build, registry, and deployment gates.
Cloud security review	IAM, storage, public services, logging.	Application business logic.	Major releases and periodic review.
Manual web/API pentesting	Exploit chains and business logic flaws.	Continuous code drift if not repeated.	Critical releases, audits, high-risk systems.
Continuous penetration testing	New exposure between annual tests.	Requires triage discipline and expert review.	Recurring validation for fast-moving teams.

Shift-Left vs Shift-Right: What the Statistics Miss

Shift-left reduces late-stage rework by finding security issues during design, coding, pull requests, and CI/CD. But shift-left does not eliminate runtime risk. Real applications fail in the interactions between code, APIs, cloud, identity, data, deployment, and user behavior.

Mature DevSecOps combines shift-left, shift-right, continuous validation, and manual testing. Security gates should be risk-based rather than blanket blockers. Exploitability, business impact, asset criticality, and compensating controls should guide prioritization.

Approach	Strength	Limitation	Best use
Shift-left	Finds issues earlier.	Can create alert fatigue and miss runtime logic.	Code, dependencies, IaC, pull requests.
Shift-right	Validates deployed behavior.	May discover some issues later.	Runtime monitoring, staging, production-like tests.
Continuous validation	Tracks ongoing exposure.	Requires ownership and triage.	Fast-moving teams and critical services.
Manual security testing	Finds logic and chained exploits.	Not continuous by default.	Critical releases, audits, high-risk systems.

Software Supply Chain and CI/CD Security

DevSecOps must protect not only application code but also dependencies, build systems, artifacts, registries, secrets, and deployment paths. Software supply chain risk includes vulnerable dependencies, malicious packages, exposed credentials, weak build permissions, unsigned artifacts, public container images, and missing SBOMs.

Open source dependency risk: Known CVEs, stale packages, abandoned libraries, and malicious packages can enter production through normal development workflows.
Transitive dependencies: A vulnerable package can be pulled indirectly several levels deep, making SBOM and full dependency-tree scanning important.
Secrets in repositories and CI: Tokens in code, logs, build variables, or container images can become direct compromise paths.
CI/CD runner compromise: Overprivileged build agents can deploy malicious code, exfiltrate secrets, or tamper with artifacts.
Artifact signing and provenance: Signing and provenance reduce the risk of tampered build outputs.
Branch protection: Pull request review, status checks, and protected branches reduce unauthorized or unreviewed changes.
Container registry security: Image scanning, hardening, and restricted registries reduce runtime exposure.
Policy-as-code: Automated policies can block insecure IaC, Kubernetes, or deployment configurations before release.

Supply chain risk	How it happens	Impact	Control / validation
Vulnerable dependency	Known CVE in package.	Exploitable application path.	SCA and exploitability review.
Malicious package	Typosquatting, dependency confusion, poisoned package.	Backdoor in build or application.	Package governance and registry allowlists.
Secrets leak	Token committed to repository or CI logs.	Cloud, API, database, or SaaS compromise.	Secrets scanning and rotation.
Weak CI/CD permissions	Build runner has excessive access.	Deployment compromise or code theft.	CI/CD security review and least privilege.
Unsigned artifacts	Build output cannot be verified.	Tampering risk.	Artifact signing and provenance.
Public container image risk	Vulnerable or untrusted base image.	Runtime compromise.	Image scanning and hardened base images.
No SBOM	Unknown component inventory.	Slow incident response and missed updates.	SBOM generation and review.

DevSecOps Metrics That Matter

Metric	What it measures	Why it matters
MTTR for critical findings	Speed of remediation.	Shows whether risk is actually reduced.
Remediation retest pass rate	Whether fixes worked.	Prevents false closure and repeated vulnerabilities.
Exploitability ratio	Real impact vs theoretical alerts.	Reduces tool noise and focuses teams on true risk.
Critical app coverage	Whether important apps are tested.	Aligns security work with business risk.
Security debt backlog	Unresolved vulnerabilities by severity.	Shows accumulated risk and process health.
Secrets incidents in CI/CD	Credential exposure in build systems.	Measures pipeline hygiene.
API test coverage	API routes and workflows tested.	Measures coverage of business logic exposure.
Gate exception rate	How often security gates are bypassed.	Reveals weak policy fit or risk acceptance patterns.
Time to owner assignment	Delay between finding and accountability.	Identifies remediation workflow friction.

DevSecOps Maturity Model

Level	Characteristics	Common gap	Next step
1. Reactive	Security happens after release or during audits.	No ownership, no metrics, ad-hoc fixes.	Start SAST/SCA, assign owners, define critical apps.
2. Tool-based	SAST, DAST, and SCA exist, but triage is weak.	Tool noise and long remediation queues.	Standardize tooling, add SLAs, define severity rules.
3. Integrated	Security checks run in CI/CD with owners and gates.	Prioritization may still lack business context.	Add exploitability and business-impact triage.
4. Risk-based	Teams prioritize by asset criticality, exploitability, and impact.	Gaps remain in APIs, cloud, CI/CD, and supply chain.	Expand API, cloud, IaC, and manual validation coverage.
5. Continuous validation	Automated and manual testing feed continuous improvement and executive reporting.	Complacency and overreliance on automation.	Maintain red teaming, threat intelligence, retesting, and metrics hygiene.

How Organizations Can Improve DevSecOps in 2026

First 30 days

Inventory critical applications and APIs.
Identify current AppSec tools and coverage gaps.
Enable secrets scanning across repositories and CI/CD.
Enforce branch protection and required code review.
Review CI/CD permissions and remove stale tokens.
Define critical application list and service owners.
Create remediation SLAs for critical and high findings.
Create a lightweight security champion network.

First 90 days

Add SAST, SCA, DAST, and IaC coverage where missing.
Run API security review for critical APIs.
Review cloud and IaC configuration for critical services.
Add threat modeling for high-risk workflows.
Define risk-based security gates.
Establish weekly triage for critical findings.
Start remediation retesting for high-risk fixes.
Build an AppSec metrics dashboard.

First 12 months

Move toward continuous validation for critical applications.
Run annual penetration testing on critical web apps and APIs.
Implement SBOM generation for all major builds.
Harden CI/CD pipelines with least privilege and signed artifacts.
Integrate runtime feedback into issue tracking.
Run mobile application testing where mobile clients exist.
Run red team exercises for mature, high-risk programs.
Review security exceptions quarterly and report DevSecOps risk to executives.

Priority	Control	Risk reduced	Validation method
Critical	Secrets scanning and rotation	Credential compromise.	Repository and CI review.
Critical	Complete SCA coverage	Vulnerable dependencies.	Dependency review and SBOM validation.
High	API penetration testing	Broken authorization and workflow abuse.	Manual API test.
High	Web application penetration testing	Authentication and business logic risk.	Manual web test.
High	CI/CD security review	Build compromise.	Pipeline assessment.
High	Cloud/IaC review	Misconfiguration and data exposure.	Cloud assessment.
Medium	Threat modeling	Design flaws.	Workshop and architecture review.
Medium	Continuous penetration testing	New exposure between releases.	Recurring validation.

How Penetration Testing Fits DevSecOps

DevSecOps does not eliminate penetration testing. It changes how penetration testing is scoped, timed, and fed back into engineering. Automated tools are useful for coverage and early detection, but manual testing validates exploitability, business logic, chained attacks, and abuse cases that scanners often miss.

In mature DevSecOps, pentest findings become engineering feedback. Repeated findings should lead to secure coding patterns, guardrails, tests, and developer education. Retesting proves whether remediation actually reduced risk.

Testing type	Best for	What it validates
Web app pentest	Customer-facing applications.	Authentication, session handling, input validation, business logic.
API pentest	Backend APIs, microservices, integrations.	BOLA, token handling, excessive data exposure, workflow abuse.
Cloud review	AWS, Azure, GCP, SaaS platforms.	IAM, storage, logging, exposed services, privilege paths.
CI/CD security review	GitHub, GitLab, Jenkins, Azure DevOps.	Secrets, permissions, branch protection, build trust.
Mobile app testing	Mobile clients and API backends.	Local storage, authentication, API abuse, token handling.
Red team assessment	Mature programs and critical environments.	Detection and response to chained attacks.
Continuous pentesting	Rapid-release teams.	New exposure between releases.
Retesting	Post-remediation validation.	Whether fixes actually reduced risk.

DevSecOps Statistics: Executive Takeaways

DevSecOps maturity is not measured by tool count. It is measured by whether critical risks are found, fixed, and validated.
Shift-left security reduces late-stage rework, but it does not replace runtime validation or manual testing.
API security is now a core DevSecOps requirement because modern applications expose business logic through APIs.
Software supply chain security requires dependency governance, SBOMs, CI/CD hardening, and secrets management.
Security debt is a process signal. If critical vulnerabilities stay open, the pipeline is not reducing risk fast enough.
AI-assisted development increases the need for review, testing, and dependency validation.
Continuous testing matters because annual testing alone cannot keep pace with rapid release cycles.
Pentesting provides proof that controls work and that fixes actually close exploitable paths.

FAQs

What are the most important DevSecOps statistics for 2026?

The most important statistics are those tied to outcomes: security debt, high-risk vulnerabilities, open source dependency exposure, CI/CD secrets, remediation SLA misses, and retest pass rates. Tool adoption is useful, but the stronger indicator is whether critical risks are fixed and validated before attackers can exploit them.

Is DevSecOps adoption increasing?

Yes. More organizations are adding security checks into development and CI/CD workflows. Adoption is visible in broader use of SAST, SCA, IaC scanning, container scanning, secrets scanning, and pipeline security. However, adoption does not always mean maturity. Many teams still struggle with alert noise, ownership, slow remediation, and inconsistent validation.

What is shift-left security?

Shift-left security means moving security earlier into the software delivery lifecycle. Examples include threat modeling during design, SAST and SCA in pull requests, secrets scanning before commit, and IaC checks before deployment. Shift-left reduces late-stage rework, but it must be paired with shift-right validation for runtime and business logic risk.

Does shift-left security replace penetration testing?

No. Shift-left tools catch many issues early, but they do not replace manual penetration testing. Scanners often miss business logic flaws, chained exploits, broken authorization, and cloud/runtime interactions. Penetration testing validates whether deployed systems can actually be exploited and whether fixes worked.

What are the biggest AppSec gaps in DevSecOps?

The biggest gaps are tool noise, weak ownership, unresolved findings, incomplete API testing, shallow SCA coverage, secrets exposure, CI/CD misconfiguration, cloud/IaC drift, and lack of retesting. These gaps prevent DevSecOps programs from converting detection into measurable risk reduction.

What security testing tools are used in DevSecOps?

Common tools include SAST, SCA, DAST, IAST, secrets scanning, IaC scanning, container image scanning, API security testing, cloud posture checks, and CI/CD security controls. Mature teams combine automation with threat modeling, manual web and API penetration testing, red team exercises, and remediation retesting.

Why is API security important in DevSecOps?

APIs expose business logic, data, and workflows directly. Modern applications depend on APIs for mobile apps, microservices, integrations, and customer portals. API flaws such as BOLA, weak token validation, excessive data exposure, and poor rate limiting often require manual testing because automated tools may not understand authorization context.

How does software supply chain risk affect DevSecOps?

Software supply chain risk affects DevSecOps because applications depend on third-party packages, build systems, containers, registries, and CI/CD pipelines. A vulnerable dependency, malicious package, leaked secret, or compromised build runner can become a production compromise. DevSecOps teams need SCA, SBOMs, secrets management, signed artifacts, and CI/CD hardening.

What DevSecOps metrics should teams track?

Teams should track MTTR for critical findings, remediation retest pass rate, exploitability ratio, critical app coverage, security debt backlog, secrets incidents, API test coverage, gate exception rate, and time to owner assignment. These metrics show whether the program reduces real risk or only produces more alerts.

How often should DevSecOps teams perform penetration testing?

Critical applications and APIs should receive penetration testing at least annually and after major architectural, authentication, payment, API, or cloud changes. Fast-moving teams should use more frequent validation, continuous testing, and remediation retesting so new exposure is found between annual assessments.

What is the difference between DevSecOps and AppSec?

AppSec is the discipline of securing applications through testing, code review, threat modeling, and remediation. DevSecOps embeds those practices into DevOps workflows, CI/CD, developer processes, cloud delivery, and operational feedback loops. AppSec is a core component of DevSecOps, but DevSecOps is broader and more continuous.

Conclusion

DevSecOps in 2026 is about proving that security is integrated into delivery and that real risks are fixed, not only detected. Shift-left testing helps teams find issues earlier, but mature programs also need runtime validation, API testing, cloud review, CI/CD assessment, supply chain governance, manual penetration testing, and remediation retesting.

The strongest DevSecOps programs measure outcomes: security debt reduction, fix speed, retest pass rate, critical app coverage, and exploitability reduction. Tool adoption matters, but validation is what proves risk reduction.

DeepStrike helps engineering and security teams validate real-world exposure through web application penetration testing, API-focused security validation, cloud penetration testing, CI/CD security assessment, mobile application testing, red team assessments, continuous penetration testing, and remediation retesting.

About the author

Mohammed Khalil is a Cybersecurity Architect at DeepStrike, specializing in advanced penetration testing and offensive security operations. With certifications including CISSP, OSCP, and OSWE, he has led red team and application security engagements for organizations in technology, finance, healthcare, and regulated environments. His work focuses on real-world attack path validation, cloud security, application vulnerabilities, PCI exposure, and adversary emulation.

Source methodology and source list

All statistics in this article are drawn from public DevSecOps research, AppSec reports, software supply chain studies, cloud-native security research, secure development guidance, and testing trend data. DevSecOps-specific figures, AppSec benchmarks, cloud-native benchmarks, software supply chain benchmarks, and cross-industry benchmarks are labeled in the statistics table. Source names below link to official report pages or source hubs where available.

DevSecOps Statistics 2026: AppSec Gaps & Testing Trends