Use case
AI-assisted vulnerability triage: KEV, EPSS and CVSS together
Triage CVEs faster by asking your AI assistant for CVSS severity, CISA KEV exploited status, and EPSS exploitation probability in one answer, grounded in current data.
Add the CVE brain to your AI assistant
A security engineer's hardest daily question is not what is vulnerable, it is what to fix first. A raw feed of new CVEs, each with a CVSS score, is not a plan. Two vulnerabilities can both be rated critical while only one is being exploited in the wild. The KBrain CVE brain lets you triage inside the AI assistant you already use, combining three signals in a single question, from data that is refreshed daily rather than recalled from training.
Why CVSS alone is not enough
CVSS measures the potential impact of a vulnerability if it were exploited. It does not tell you whether anyone is exploiting it, or how likely that is to happen soon. A patch queue ordered by CVSS alone spends effort on high-impact issues that no attacker is touching, while a medium-scored bug under active exploitation waits its turn.
Two extra signals fix this. CISA KEV lists vulnerabilities that are known to be exploited right now. EPSS, the Exploit Prediction Scoring System, estimates the probability that a vulnerability will be exploited in the next 30 days. Read together, they turn a flat severity list into a real priority order.
The three signals, in one answer
- CISA KEV: is this being exploited today? If yes, it jumps the queue. This is the single strongest signal for urgency.
- EPSS: how likely is exploitation in the near term? A high EPSS score with no KEV listing flags something worth patching before it becomes a KEV entry.
- CVSS severity and vector: if it is exploited or likely to be, how bad is the impact and what is the attack path?
A simple rule that works: patch KEV entries first, then high-EPSS items, then remaining high-CVSS items. The CVE brain returns all three fields on every lookup so you can apply that rule without leaving the chat.
What triage looks like in practice
You paste a list of CVEs from a scanner report into Claude or ChatGPT and ask which to fix first. The assistant calls the CVE brain for each identifier, gets the KEV flag, the EPSS score, and the CVSS severity, and returns a ranked list with the reasoning attached. Because the data is current, a CVE added to KEV yesterday is treated as urgent today, not missed because the model was trained last year.
- Ask: "Of CVE-2024-3400, CVE-2024-21762 and CVE-2023-46805, which should I patch first and why?"
- Ask: "Show me this week's critical CVEs that are already in CISA KEV."
- Ask: "Is the EPSS score for this CVE high enough to justify an emergency change?"
Every answer carries a last-updated timestamp, so a triage decision can cite when the underlying data was current. That matters when the same question, asked to a generic model, would return a confident but stale or invented score.
Add the CVE brain to your AI assistant
Look up CVEs, CISA KEV exploited status, and EPSS scores from Claude, ChatGPT, or any MCP compatible assistant. Hosted and refreshed daily, with no self-hosting and no API keys to manage.
Frequently asked questions
Why not just sort by CVSS score?
CVSS measures potential impact, not whether a vulnerability is actually being exploited or likely to be. Sorting by CVSS alone can push a medium-scored, actively-exploited bug below high-scored issues that no attacker is touching. Combining CISA KEV and EPSS with CVSS produces a priority order that reflects real risk.
Where does the KEV and EPSS data come from?
CISA KEV comes from the official Known Exploited Vulnerabilities catalog, and EPSS from FIRST.org. The CVE brain refreshes both daily and joins them onto each CVE, so a single lookup returns all three signals.
Do I need to set anything up?
No. The CVE brain is hosted and refreshed for you. You add it to Claude, ChatGPT, or any MCP compatible assistant once and start asking triage questions. There is no server to run and no API key to manage.
How current is the data during an incident?
The brain runs a daily incremental sync from NVD and a full refresh of CISA KEV and EPSS, and every record carries a last-updated timestamp. That is far fresher than a general model's training data, which can be many months behind.