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Start from a neutral baseline and add what matters to you. Criteria are labeled by source — the platform baseline is architecture-neutral; buyer-contributed criteria are shown separately.
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Look for external, attacker-perspective discovery beyond the existing CMDB, since unknown assets are often the actual exposure.
Strong answers describe real exploitability testing (safe simulated exploitation or attack-path validation), not just vulnerability scan aggregation, with a concrete reduction figure.
A unified cross-domain score is stronger than siloed per-category scores requiring manual reconciliation.
Attack-path/graph modeling that shows the chain to a defined crown-jewel asset is materially more actionable than a flat findings list.
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Verified buyers can suggest criteria (anonymized before pooling).
Look for automated re-validation after a fix, not just relying on a closed ticket as proof of remediation.
Strong answers state a concrete detection-latency figure for newly appeared exposures, not just scan frequency.
Native trend reporting suitable for board-level consumption is stronger than requiring the customer to build it themselves.
Look for clarity on which sources are native versus requiring separate licenses/integrations from other vendors.
Look for transparent, predictable scaling economics; per-asset pricing that spikes unpredictably with cloud elasticity creates real budget risk for CTEM specifically, given its continuous/dynamic nature.
An orchestration-layer approach that unifies existing tooling investment is materially less disruptive than a rip-and-replace requirement — ask explicitly which model this vendor uses.
Active validation via BAS/red-team integration (safely confirming exploitability) is a materially stronger claim than passive analysis alone, which can still misjudge real-world exploitability.
Purpose-built compliance/audit-ready reporting is a distinct capability from internal dashboards — a vendor should be explicit about whether external-audience reporting exists.
Strong answers give a concrete timeline backed by a real customer and are honest about the customer-side effort required, not just vendor-side setup time.
A vendor willing to explicitly name their coverage boundaries and recommend complementary tools is more credible than one implying comprehensive coverage of every exposure type.
Identity exposures require different validation logic than infrastructure vulnerabilities — a vendor should describe identity-specific validation explicitly rather than treating all exposure types identically.
Look for explainable prioritization logic (not a black-box score) — security teams need to understand and defend prioritization decisions to stakeholders, not just trust an opaque AI output.