TECH & AI
Traditionally, companies maintain rapid emergency procedures for critical, highseverity flaws. However, medium- and low-priority vulnerabilities are routinely left unpatched, lingering as technical debt. This neglect creates a dangerous window of exposure, with traditional testing and deployment pipelines typically stretching from 40 to 90 days across complex enterprise environments.
To close this gap, organisations must compress deployment timelines to align with standard embargo windows before fixes become public knowledge.
“ If your patch-to-production time is 30, 50 or 90 days, and the embargo window is a couple of weeks, we have got to help you find ways to get down to a couple of weeks,” Brian says.
This issue affects businesses of all sizes, though large enterprises face heightened complexity due to sprawling legacy infrastructure. Red Hat and IBM provide AI-driven testing and deployment automation to help organisations overcome this operational lag.
“ If you only have a plan for highseverity vulnerabilities, and everything else takes a long time, you need to reevaluate that because there is an additional vulnerability gap,” Brian warns.
Levelling the field against AI threats As malicious cyber actors leverage the same frontier AI models as defenders, organisations face an asymmetric threat landscape where attackers often possess greater motivation to uncover software vulnerabilities.
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