Automated audits often generate massive lists of findings that require manual review to determine which alerts actually matter in your specific context. They typically work well for cloud components but struggle with on-premises data, which may be incomplete or lag by days. These tools also miss nuanced, business-logic risks and novel attack paths that weave between cloud and on-premises systems.
Automated audits often generate massive lists of findings that require manual review to determine which alerts actually matter in your specific context. They typically work well for cloud components but struggle with on-premises data, which may be incomplete or lag by days. These tools also miss nuanced, business-logic risks and novel attack paths that weave between cloud and on-premises systems.
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Automated audits often generate massive lists of findings that require manual review to determine which alerts actually matter in your specific context. They typically work well for cloud components but struggle with on-premises data, which may be incomplete or lag by days. These tools also miss nuanced, business-logic risks and novel attack paths that weave between cloud and on-premises systems.
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