The Tool Desk
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What the available fix-rate data shows
The strongest application-security benchmark in the available evidence is Veracode’s 2025 State of Software Security. Its findings draw on 1.8 million static analysis (SAST), dynamic analysis (DAST), and software composition analysis (SCA) scans of nearly half a million applications. Veracode’s report says average time to fix flaws increased 47% since 2020, and its landing page says half of organizations had critical security debt. These are vendor-reported findings about its dataset, not a universal industry rate. (Veracode, 2025 State of Software Security.)
The long-term comparison is SAST-only
In its 15-year retrospective, Veracode reports an average of 59 days to fix flaws in Volume 1 and 252 days in Volume 15. That historical trend uses SAST scans only, to keep the comparison consistent with earlier reports. The report’s contemporary findings generally combine SAST, DAST, and SCA. The two views should not be treated as interchangeable: one is a consistent historical series, and the other reflects a broader mix of scan types.
Veracode summarizes the challenge this way: “Finding flaws is easy these days; fixing them is where the challenge lies.” The quote describes the report’s broad finding; it does not identify a particular cause for any one team’s delay.
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Critical security debt includes third-party code
Veracode reports that 70% of critical security debt in its 2025 analysis came from third-party code and the software supply chain. That finding is a reason to include dependencies in remediation planning, not proof that dependency ownership is the cause of a particular authentication defect. Application flaws, dependency vulnerabilities, infrastructure vulnerabilities, and authentication failures are different categories and should not be collapsed into one fix-rate figure.
What is known about authentication failures
Veracode’s Security Flaw Heat Map describes authentication issues as insecurely implemented authentication functions that can expose passwords and session tokens. It recommends secure coding practices, security scans, strong password policies, and multifactor authentication. The prevalence percentages visible on that page are tied to State of Software Security Volume 12; they are a historical snapshot, not a current prevalence estimate or a remediation rate.
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Why the causes cannot be reduced to developer neglect
The available figures show that remediation can be slow across application-security findings, but they do not identify a single reason authentication flaws persist. Nor do they establish that authentication defects are fixed at the same pace as operating-system vulnerabilities. A vulnerability may involve application code, a third-party component, or an underlying system, and the evidence measures different populations and outcomes.
It is therefore more accurate to say that authentication bugs can remain among broader security backlogs than to claim that a specific auth-only repair pattern has been measured. The available sources do not establish a current longitudinal rate for fixing authentication flaws or a cause unique to those flaws.
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Why vulnerability statistics are easy to misread
A fix-rate comparison is useful only when the measured object, population, timing measure, and definition of “fixed” are clear. An average number of days in a scan dataset cannot be directly compared with the share of vulnerability instances still open on a particular day.
| Measure | What it describes | What it does not establish |
|---|---|---|
| Veracode’s 252-day average in Volume 15 | Average days to fix flaws in Veracode’s historical SAST-only comparison, reported in 2025. | A universal average, an authentication-only rate, or a direct comparison with an open-at-day-N statistic. |
| Veracode’s 47% increase since 2020 | Veracode’s reported change in average time to fix security flaws. | That every organization or flaw type experienced the same increase. |
| Verizon’s 35% open at day 28 | 35% of KEV vulnerability instances in Verizon’s 2025 analysis remained open at day 28, as reported in the 2026 DBIR. | The share of companies, application-code flaws, or authentication failures left open. |
Before comparing studies, check whether they count flaw instances, scanned applications, systems, or organizations; whether the timing measure is a mean, median, or still-open share; how a fix is verified; which scan methods and severity rules apply; and the observation period and geography. If those definitions differ, the numbers answer different questions.
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How teams can prioritize vulnerabilities
Treat remediation as a risk-ranked work queue rather than a race to close every finding in discovery order. CISA’s FY2024–2025 Vulnerability Review identifies poor patching and end-of-support technology as contributors to compromise and recommends considering exposure, whether a flaw appears in the Known Exploited Vulnerabilities (KEV) Catalog, the potential for exploitation to be automated, and technical impact. CISA does not set an authentication-specific fix deadline.
Build the queue around risk and ownership
- Establish exposure: identify whether the affected asset or application is exposed and what it protects.
- Check KEV status: determine whether the vulnerability is listed in CISA’s Known Exploited Vulnerabilities Catalog.
- Assess exploitability and impact: include the potential for automated exploitation and the technical consequences of compromise.
- Assign a remediation owner: make clear which team can change the application, dependency, or system and who can verify the result.
- Confirm closure: validate the remediation with an appropriate scan or other verification step rather than relying only on a ticket being marked complete.
Connect scanning to remediation
NIST SP 1800-31 presents an enterprise example of combining software discovery and vulnerability scanning with dashboards and reporting to decide which systems and remediation actions to handle first. It is an implementation example, not a comparative evaluation of products. The useful operational principle is to connect findings with asset context, prioritization, assigned work, and verification so that a scan result can lead to a tracked remediation action.
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What organizations should—and should not—conclude
The evidence supports a measured conclusion: remediation is a substantial challenge in the datasets described, third-party code contributes materially to Veracode’s reported critical security debt, and risk-based prioritization is more useful than treating every finding as equally urgent. It does not show that all authentication failures persist for a set number of days, that neglect explains them, or that infrastructure patch statistics can stand in for application-code fix rates.
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