vulntel

vulntel

Most CVE tools hand your agent raw data. This one ranks it by what's actually being exploited, finds bugs by mechanism, catches the CVEs your agent invents — and transfers attack mechanics from ~14,000 disclosed bug-bounty reports.

A curated, hosted MCP corpus: ~422,000 CVEs, fused from NVD + CISA KEV + FIRST EPSS + OSV/GHSA + CISA Vulnrichment (SSVC), plus a mechanic layer distilled from ~14,000 disclosed, paid bug-bounty reports — refreshed daily. Not another live-API wrapper.

Free. Try it with no key (nine tools, 25 calls a day per IP address), then get a key: enter your email and your personal key is sent over. Tell me what you are hunting.

Why this, and not the next CVE wrapper

Most CVE MCP servers are thin wrappers: at query time they fan out to the same free public APIs and hand back whatever comes out. This is different in six concrete ways.

• A curated, embedded corpus, not a live proxy. One record per vulnerability, fused across NVD, OSV/GHSA and KEV through an identity graph, with roughly 2,100 vendor-qualified product aliases and embeddings for semantic search. Queried locally, ranked consistently.
• SSVC as priority, not just CVSS. Priority is exploitation-first: CISA SSVC (active / automatable / total impact), KEV and EPSS drive a P1 to P4 ranking. The wrapper MCPs do not carry SSVC at all.
• Search by mechanism, not keywords. Semantic search finds the same bug *class* across different products. Keyword tools structurally cannot.
• It fact-checks the agent. verify_cve_claim catches invented CVEs and wrong attributes. This is the one that matters most right now, with hallucinated AI bug reports flooding triage, and effectively no other CVE MCP does it.
• Backport-aware. Paste a server banner (OpenSSH_8.9p1 Ubuntu-3ubuntu0.10, Apache/2.4.62 (Debian)) and each CVE carries the Debian / Ubuntu / Alpine tracker's verdict for that exact build next to the upstream one. Upstream-only tools call a patched distro host vulnerable.
• Right vendor, and no false zeros. "GitHub Enterprise" resolves to the right vendor, not every product that ships an "enterprise_server." A product it cannot resolve returns resolved: false with suggestions, never a silent 0 that reads as "not affected." A false zero is the worst answer a security tool can give.

The hard part of AI-assisted security is not *finding* CVEs. It is triage, prioritization, and false positives. That is what this targets.

Everything below is real output from the live server, trimmed only for length.

It fact-checks your agent

The differentiator that matters most. Your agent cites CVE-2025-99999:

verify_cve_claim("CVE-2025-99999")

-> exists: false "No record in NVD / OSV / GHSA. Likely hallucinated or not-yet-published."

Or it gets the details wrong. Claim: *"CVE-2021-44228 is a medium-severity Apache Struts bug, and it is not exploited."*

verify_cve_claim("CVE-2021-44228", product="Apache Struts", severity="medium", exploited=false)

refuted "not exploited" -> in CISA KEV (added 2021-12-10) refuted "severity medium" -> actual CVSS 10.0, P1 refuted "affects Apache Struts" -> no product matching "Apache Struts"

The other feeds hand your agent data. This one tells you when the agent is wrong, before it reaches a report.

Priority is exploitation-first (SSVC, KEV, EPSS), not CVSS

check_technology("GitLab") returns 792 CVEs for the product, de-duped and ranked so the exploited ones float to the top:

P1  KEV  EPSS 99.8   CVE-2023-7028   account-takeover: password-reset email sent to an attacker address (CVSS 10)

P2 KEV EPSS 98.5 CVE-2021-39935 unauthenticated SSRF via the CI Lint API P3 EPSS 99.7 CVE-2023-2825 unauthenticated path traversal, arbitrary file read (CVSS 10) P3 EPSS 99.7 CVE-2022-2992 authenticated RCE via the GitHub import API (CVSS 9.9)

Names that map to more than one vendor are flagged ambiguous (here, gitlab vs a jenkins plugin) and kept separate, never silently merged. enrich_cve then gives you the full SSVC picture for any one of them:

enrich_cve("CVE-2024-3400")   PAN-OS GlobalProtect

P1 KEV CVSS 10.0 EPSS 99.95 unauthenticated command injection -> root RCE SSVC exploitation=active automatable=yes technical_impact=total Metasploit exploit/linux/http/panos_telemetry_cmd_exec (rank: excellent) Public PoC 44 repos (h4x0r-dz 162 stars, W01fh4cker 90 stars, ...)

Turn recon into a dig-order

hunt_plan(["craftcms 4.4", "nginx", "keycloak"]) ranks your stack by its most-exploitable bug and names where each component historically bleeds:

#1  craftcms 4.4    97 CVEs, 12 high-risk

recurring_loci CWE-94 code injection x7 (2 exploited in the wild) -> probe template / eval surfaces first dig here P1 KEV EPSS 99.8 CVE-2025-32432 unauthenticated RCE (CVSS 10) your 4.4 is AFFECTED, fixed in 4.14.15 P1 KEV EPSS 99.9 CVE-2024-56145 RCE when register_argc_argv is on AFFECTED, fixed in 4.13.2

#2 nginx HTTP/2 Rapid Reset CVE-2023-44487 (KEV) #3 keycloak recurring_loci CWE-287 auth x12. OIDC request_uri SSRF CVE-2020-10770

It does not just list CVEs. It names the bug *class* a product family keeps failing at, ranked by real exploitation, and tells you whether *your version* is in range. Where to look, and what shape to expect.

Search by mechanism, across products

search_vulns(cve_id="CVE-2021-44228"), "what else works like Log4Shell":

sim 0.88   CVE-2021-44832   Log4j2 JDBC Appender, JNDI LDAP RCE

sim 0.82 CVE-2022-40145 Apache Karaf, code injection via an attacker-controlled JNDI URL sim 0.79 CVE-2022-34916 Apache Flume, JNDI LDAP RCE via a JMS source

The same JNDI-injection mechanism, surfaced across *different products*. A keyword search for "log4j" never finds Karaf or Flume. Or search a concept directly, search_vulns("SAML SSO authentication bypass"):

P3      CVSS 9.1  CVE-2024-9487   GitHub Enterprise: SAML SSO bypass via signature verification

P3 CVSS 9.8 CVE-2025-25291 ruby-saml: auth bypass via a ReXML / Nokogiri parser differential P1 KEV CVSS 9.8 CVE-2025-59718 Fortinet FortiOS / FortiProxy: signature-verification bypass

See what is being exploited right now

search_vulns(days=7), run live today:

P1 KEV CVSS 10.0  CVE-2026-10520  Ivanti Sentry: unauthenticated OS command injection -> root RCE

P1 KEV CVSS 9.3 CVE-2026-50751 Check Point: IKEv1 auth bypass, remote-access VPN without a password P2 KEV CVSS 8.8 CVE-2026-11645 Chrome V8: out-of-bounds read/write -> sandbox escape RCE

Median time from disclosure to in-the-wild exploitation is now days, not months. The Ivanti bug above carried a CISA remediation deadline in the same week it landed. corpus_stats on 2026-11-03: ~422,800 CVEs, ~1,770 KEV entries, data under a day old. These figures are point-in-time and drift daily, so call corpus_stats yourself for the live count rather than trusting the numbers on this page.

Transfer attack mechanics from disclosed bug-bounty reports

Beyond CVEs, the corpus distills ~14,000 disclosed, paid HackerOne reports into product-agnostic *attack mechanics* — each bug's source → sink → trigger → preconditions, de-anchored from the product it was filed against. The premise: a vulnerability is a transferable mechanism, not a property of one product — so a move that paid on one stack is a checklist item on the next.

find_attack_approaches(query="ssrf reaching cloud metadata") — the human moves that transferred, novelty-ranked, each tagged with live program-actionability:

Reddit         SSRF   preview_url fetches an unfiltered URL → returns metadata    program_active, pays

U.S. DoD SSRF /download-url?url= fetches AWS instance metadata program_active Concrete CMS SSRF DNS-rebind bypass → AWS IAM creds from the metadata svc program_active

• find_continuations(position=...) — matches your *accumulated attacker position* mid-hunt to the next moves real reports played from a similar spot. Every move is status: UNVERIFIED with a decisive_check to run on the target — a legal move, never a confirmed bug.
• assist_submission(finding=...) — a grounded submission brief from the closest paid precedents (validity, what's novel, an escalation playbook), with every cited report validated against the corpus (citations_grounded) so it can't smuggle a fabricated precedent.
• program_outcome_prior("hackerone:gitlab") — the bug classes that historically *landed* on a program, with lift over base rate (GitLab: SSRF 3.4×, SQLi ~never).

Honest about what this is: it primes and grounds a human hunter — it surfaces the move and the precedent. It does not find the bug for you; the target decides whether the move survives, and that's a step you still run.

The whole point: a memory of mechanics to borrow and run — not a CVE lookup

The moat is three things a stateless model cannot self-generate, and this corpus holds all three:

• Watched over time — priors, temporal drift (Log4Shell's affected set kept growing +1,200 days after publish), score stability. Your model has a training-cutoff snapshot; this has the *trajectory*.
• Seen many — every disclosed mechanic and CVE mechanism, embedded, so the *same bug class* transfers across products a model would never connect: Log4Shell's JNDI lookup → Apache Karaf, Flume; an SSRF that paid on Reddit → the move to try on the next target.
• Live-fused recon — observe recovers a host's real backend from its JS bundles and joins it to the corpus on the spot.

The cardinal sin is treating it as a severity-number checker. The job is to transfer a proven mechanic onto your target and run it — or read a fix to *falsify* an option before you spend a probe on it.

Force your agent to reach for it — it won't on its own

Left alone, an agent answers from training data: stale, and it *invents* CVE ids under pressure. Paste this operating loop into your agent's rules (CLAUDE.md, Cursor/Windsurf, a system prompt):

You have the vulntel MCP. Your own CVE knowledge is a guess to be verified — prefer the corpus.

Operating loop, in order:

1. Choosing / scoping a bounty program → new_in_scope (what just entered a program's scope, re-adds filtered) and program_outcome_prior (which bug classes have actually PAID here).
2. A live host → observe (a cache miss returns status="scanning"; call again with the same host until "ready"). Mine endpoints[], recurring_loci, the CVE join, not just two fields.
3. A product + version → check_technology / hunt_plan (dig-order + the recurring CWE loci).
4. Before asserting ANY CVE / "affects X" / "severity Y" / "exploited" → verify_cve_claim. Never cite from memory.
5. Feasibility of one CVE → enrich_cve; read the MECHANISM (POST vs GET, auth-required) to judge whether it chains. How it was fixed in the wild, or who vendored the vulnerable line → search_public_code (raw hits; read them).
6. Hunting a class → find_attack_approaches for the transferable move; RUN it on the target, don't cite it. Loop with a growing tried=.
7. Stuck / messy position → find_continuations(position) for the by-step move; then search_vulns that class to see whether it recurs in this stack.
8. Submitting → assist_submission; EXECUTE the techniques it transfers (referrer differential, key-reuse breadth), then file.
9. Before trusting a "nothing found" → corpus_stats (corpus size and