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AI can help threat actors automate and scale vulnerability-related activity, adding pressure to already busy security teams. But rising disclosure or exploitation counts do not prove that AI caused every increase. The practical problem is more immediate: a spreadsheet can store findings, but it cannot keep asset data, exploit signals, exposure, ownership, and remediation status current by itself.
How is AI changing vulnerability management?
AI can make parts of an attack workflow more efficient, including tasks that may help threat actors find, assess, or exploit weaknesses at greater scale. CISA put the point cautiously in its August 26, 2026 bulletin: “Emerging technology, such as AI, introduces efficiencies threat actors can leverage to automate and scale threat activity.” That describes a capability and a source of pressure—not proof that AI caused a particular exploit or trend. CISA’s vulnerability review also describes a baseline before AI-enabled vulnerability discovery becomes more widespread.
Recent figures reported by ITPro from Google Threat Intelligence Group (GTIG) are consistent with a busier environment, but do not establish a single cause. GTIG reported monthly vulnerability disclosures reached 10,740 in August 2026. It also reported an average of 10.5 exploited vulnerabilities per month in 2025, compared with 18 per month from January through August 2026; zero-day exploitation averaged eight cases per month in 2025 and 11 per month from January through August 2026. These are GTIG figures as reported by ITPro, not proof that AI alone produced the changes. ITPro’s October 1, 2026 report provides the secondary account.
For defenders, the consequence is not that every new flaw will be exploited instantly. It is that more findings and faster-moving threat activity can increase the cost of deciding what matters. That makes reliable inventory, context, and follow-through more important than simply adding rows to a vulnerability spreadsheet.
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Why a severity score is not a remediation queue
CVSS and other severity ratings help describe a vulnerability’s technical seriousness. They do not, on their own, tell a team whether the affected software is deployed, exposed to attackers, already being exploited, easy to exploit at scale, or critical to the organization. CISA’s August 2026 framework evaluates four practical dimensions: exposure status, known exploitation in its KEV catalog, potential for exploitation to be automated, and technical impact. CISA’s bulletin highlights these factors as a way to understand and proactively address software vulnerabilities.
Exploit-related data points answer different questions. Treating them as interchangeable—or treating one score as a complete answer—can misdirect limited remediation capacity.
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| Signal | What it tells you | What it does not establish |
|---|---|---|
| CISA KEV | There is evidence that a vulnerability is known to have been exploited; CISA prioritizes catalog entries for remediation. | Absence from KEV does not prove that exploitation has never occurred. The catalog has a defined scope and is not a complete record of every vulnerability or exploit. |
| EPSS | A predictive estimate of the likelihood of exploitation during the next 30 days. | It is not evidence of past exploitation. NIST notes EPSS does not use past exploitation as a model input, so a previously exploited vulnerability can still receive a low score. |
| LEV | NIST’s proposed metric estimates the probability that a vulnerability has been observed exploited at some point in the past, and may help assess KEV comprehensiveness. | It is not definitive ground truth. NIST describes an unknown margin of error and says public exploitation data is insufficient for thorough performance testing. |
| CVSS or severity | Technical context about how serious a vulnerability may be. | It does not establish whether your affected asset is exposed, whether exploitation is known or likely, or how consequential compromise would be in your environment. |
NIST’s 2025 white paper explains the distinction between prediction and evidence of past exploitation, and presents LEV as a proposed metric rather than a settled standard. NIST CSWP 41 also cautions that the public data available for assessing LEV is incomplete.
KEV coverage should be interpreted with the same care. NIST’s white paper compared 1,228 KEV entries with roughly 260,000 CVEs in a December 2024 snapshot, a ratio of 0.5%. That is a dated comparison of catalog coverage against the CVE population—not a current KEV count and not an estimate that only 0.5% of vulnerabilities have been exploited. NIST says vulnerabilities absent from a KEV list have unknown status relative to past exploitation. The CSWP 41 paper explains the limits of interpreting the catalog this way.
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What a spreadsheet can—and cannot—do
A spreadsheet is not inherently unsafe or useless. It can be a workable record for a limited, stable environment if someone maintains accurate data and follows each item through verification. Its weakness is not the file format; it is the gap between recording information and keeping that information connected, current, and actionable as assets and advisories change.
For each vulnerability that could affect the organization, the process needs to connect the finding to the software and version actually deployed, the asset using it, that asset’s exposure and business importance, and the person responsible for action. It also needs to capture remediation state—including patches, mitigations, and approved exceptions—and revisit the record when threat or advisory information changes. Without those connections, a list can look orderly while leaving teams unable to tell which finding is urgent or whether it has really been resolved.
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CISA’s emphasis on exposure, KEV status, automation potential, and technical impact is a useful minimum view for prioritization. Organizations may need additional context, such as business criticality and the availability of compensating controls, to choose a safe response. Automation can help import and correlate changing data; people still need to validate whether the affected software is present, what operational disruption a change could cause, and whether a mitigation actually reduces risk.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to decide whether your process needs more than a spreadsheet
Assess the process by what it can reliably do, not by whether it uses a spreadsheet, scripts, or a vulnerability-management platform. A tool is useful only if its data and workflow fit the organization’s assets and decisions.
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| Capability to assess | Questions to ask |
|---|---|
| Inventory and product coverage | Can the process identify the relevant assets, software products, and deployed versions—and show where coverage is missing? |
| Freshness and imports | How often are advisories and exploit signals updated? Can reliable, machine-readable sources be imported without losing provenance or creating unreviewed duplicates? |
| Risk context | Can a reviewer see exposure, KEV status, predictive signals such as EPSS, technical impact, and business context together rather than relying on a severity score alone? |
| Remediation workflow | Can the team assign an owner and deadline, record mitigation or patch status, verify the fix, and track exceptions to review? |
| Integration | Does the process connect to the existing asset inventory and ticketing workflow, so that findings can be assigned and their status reconciled? |
| Data quality and transparency | Can users see when a finding is uncertain, an asset match is incomplete, or a source has known gaps? Is there a way to resolve false positives without silently discarding them? |
If the answers depend on repeated manual copying, stale exports, or knowledge held by one person, the process is unlikely to scale smoothly as finding volumes rise. Improving inventory and ownership may be more valuable than buying a new tool; where automation is introduced, it should make updates and handoffs more reliable rather than obscure the source or confidence of a finding.
Keep familiar weaknesses in the queue
New AI capabilities do not make basic security work obsolete. CISA’s 2026 review points to simple known vulnerabilities, poor patching, and continued use of end-of-support technology as persistent sources of risk. A sophisticated exploit scenario should not automatically outrank an exposed, business-critical system running software that no longer receives security support. CISA’s review emphasizes that these longstanding weaknesses remain relevant.
A useful vulnerability process therefore balances new signals with disciplined maintenance: keep the asset inventory credible, identify unsupported technology, make ownership explicit, and confirm that remediation or mitigation has actually reached the affected system. AI may increase pressure on the process; it does not remove the need to know what you run and who is fixing it.
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