Predict, Don’t Enumerate
I wrote an article for O’Reilly about the urgent need to change exposure management in the face of Mythos and the coming disclosure of vulnerabilities at scale. This is the final section of that article.
The policy shifts that actually matter
The interventions that will decide whether a security program survives the next 24 months aren’t purely technical. A CISO can put most of them in motion without buying anything.
Rewrite the SLA. Most vulnerability-management SLAs are organized by severity. Criticals in 15 days, highs in 30, mediums in 90. That structure was built for a world where the count of open criticals was small enough to matter. It’s now actively harmful, because it forces teams to spend the same effort on a 9.8 nobody is exploiting and a 7.5 that’s under active attack. SLAs should be rewritten in terms of probability of exploitation and asset exposure, not severity. A CISO who can’t get that past her GRC team can at least add a second tier that makes the probability-based cut enforceable alongside the severity-based one.
Change what the board sees. If the monthly security report counts the numbers of vulnerabilities, exposures or findings in different buckets (“critical,” “open past 30 days,” etc.), the organization is being managed to the wrong metric. The metric should be exploitability-weighted exposure over time, with a second line for predicted versus observed exploitation. Boards will accept this once somebody explains it. This beats showing them a number that has no relationship to risk and is growing exponentially as new LLM models are released. More to the point: A great team can do amazing volumes of remediation work, and risk can still rise because they’re measuring and remediating the wrong thing. An efficient, context-rich team can do far less work and meaningfully move the probability of an event down.
Invest in telemetry. The single most valuable instrument a security program can build is a feedback loop between what was prioritized and what was exploited. If the loop shows you were wrong, the model improves. If the loop does not exist, you will keep being wrong indefinitely (or just not being aware of misses).
Fix the compliance conversation. The reason CVSS survives is regulatory inertia. PCI, HIPAA, and most state breach-notification frameworks still reference severity. The CISOs who will come out of the next two years in the best shape are the ones who engage their auditors now, in writing, about what a probabilistic prioritization framework looks like under the existing rules.
Staff for the bottleneck, which isn’t scanning. The industry has spent a decade hiring people to find bugs. The bottleneck now is deciding which bugs matter, getting the fixes deployed, and measuring whether the prioritization was correct. The job descriptions should reflect this. A security-data engineer may be able to increase efficiency to meet SLAs more than increasing capacity would.
None of this requires a new product. All of it requires a CISO willing to say, out loud, that the old dogma is broken and that the new one will be managed by data and probabilities. That is the shift Anthropic’s five-word sentence was really announcing. The technology is available and the models are here—both the LLM-based ones to find the vulnerabilities and the predictive knowing machines to prioritize efficiently.
