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cve_search

Read-onlyIdempotent

Search the CVE database using filters like product, vendor, severity, date range, EPSS score, CWE, CVSS, and CISA KEV status to discover vulnerabilities matching specific criteria.

Instructions

Search CVE database with filters: product/vendor, severity, published date range, EPSS score, CWE, CVSS range, CISA KEV status. Default response is SLIM per-result (cve_id, summary, severity, cvss_v3, cwe_id, epss, kev, total_products, published, modified, sources) — pass include='full' for description, cvss_breakdown, affected_products, references, first_seen_*. Verdict (sources_queried, falsifiable_fields, completeness, data_age) is at the response root — applies to the whole batch, not per-row. Product/vendor filters are EXACT NVD-canonical-token matches (not the common name — e.g. nginx is 'nginx_open_source'/'nginx_plus', vendor 'f5'); a low/zero count for a well-known product means the token differs, so for dependency/package lists use check_dependencies and for a domain's whole stack tech_stack_cve_audit (both auto-normalize tokens). Use for vulnerability discovery by criteria; pass cwe_id (e.g. CWE-79) to enumerate every CVE in our database mapped to a weakness — pair with cwe_lookup for the category description and mitigations. Use cve_lookup for single CVE by ID, kev_detail when kev=true filtering and the agent needs federal patch deadlines per result. Response carries a global hint pointing at cve_lookup — drill into any returned cve_id for full detail and chained pivots (exploit_lookup, kev_detail, cwe_lookup). Free: 30/hr, Pro: 500/hr. Returns {count, total, truncated, offset, summary, results, query_echo, next_offset, verdict, hint}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productNoProduct or vendor token to filter by. EXACT match (case-insensitive) against the NVD-canonical CPE product/vendor token — NOT substring/fuzzy, and NOT necessarily the common project name. Common names, vendor renames, and build-tool artifact ids often differ from the canonical token (e.g. modern nginx CVEs are under 'nginx_open_source'/'nginx_plus', vendor 'f5', not 'nginx'; Maven 'log4j-core' maps to 'log4j'). A low or zero count for a well-known product usually means the token differs — do NOT assume coverage is complete. For dependency/package lists prefer check_dependencies, and for a domain's whole tech stack tech_stack_cve_audit (both auto-normalize tokens). A product match means CVEs exist for that product, not that a specific running version is affected — verify the running version is within each CVE's affected range. Omit to search all products.
severityNoCVSS severity level. Must be one of: CRITICAL, HIGH, MEDIUM, LOW. Omit for all severities.
published_afterNoInclusive lower bound on publish date as YYYY-MM-DD (UTC). Pick this when the user names a starting point, e.g. 'since 2015' → '2015-01-01', 'after March 2024' → '2024-03-01'. Omit to not bound the lower edge. Combine with published_before for ranges.
published_beforeNoInclusive upper bound on publish date as YYYY-MM-DD (UTC). Pick this when the user names an ending point, e.g. 'before 2020' → '2019-12-31', 'up to 2023' → '2023-12-31'. Omit to not bound the upper edge. Combine with published_after for ranges.
kevNoIf true, return only CVEs in the CISA Known Exploited Vulnerabilities (KEV) catalog — these are actively exploited in the wild.
epss_minNoMinimum EPSS score filter (0.0-1.0). EPSS predicts exploitation probability. 0.5 = top ~5% most likely to be exploited. 0.0 = no filter.
sortNoSort order for results. Must be one of: published_desc (newest first), epss_desc (most exploitable first), cvss_desc (most severe first). Omit for newest first (default=published_desc).
limitNoMaximum results to return. Range: 1-200.
offsetNoSkip N results for pagination. Use with limit to page through results.
cwe_idNoFilter by CWE weakness ID. Exact match, case-insensitive. Common values: CWE-79 (XSS), CWE-89 (SQL injection), CWE-120 (buffer overflow), CWE-78 (command injection). Format: CWE-<number>. Omit to not filter by CWE.
cvss_minNoMinimum CVSS v3 base score (0.0-10.0). Default 0.0 = no filter (sentinel, not applied). Set > 0 to filter — CVEs with null CVSS are excluded when active. Use 7.0 for high+critical, 9.0 for critical only.
cvss_maxNoMaximum CVSS v3 base score (0.0-10.0). Default 10.0 = no filter (sentinel, not applied). Set < 10.0 to filter — CVEs with null CVSS are excluded when active. Combine with cvss_min for a range.
vendorNoFilter by vendor name (case-insensitive). When combined with product, both must match the same CPE row — prevents cross-row false matches. Example: vendor=apache, product=struts.
includeNoPer-result detail level. Default (omit) returns slim list items (cve_id, summary, severity, cvss_v3, cwe_id, epss, kev, total_products, published, modified, sources). Pass 'full' to also return description, cvss_breakdown, affected_products, references, first_seen_source, first_seen_at — only do this when the user explicitly wants drill-down on every result. Even with 'full', per-result affected_products and references may be truncated (the per-result total_products/total_references report the honest counts); use cve_lookup for the guaranteed-complete per-CVE lists. For single-CVE detail prefer cve_lookup; slim default keeps token cost ~70% lower on Log4j-class queries. Note: verdict is at the response root, not per-row (was deduplicated to save ~40% payload).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds: default slim response, verdict at root not per-row, exact token matching for product/vendor, EPSS interpretation, rate limits (30/hr free, 500/hr Pro), and response structure (count, total, truncated, etc.). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is relatively long but well-structured with clear sections: purpose, response details, guidelines, rates. Some redundancy with parameter descriptions in schema (e.g., product token explanation appears in description and param description). Could be slightly tighter, but overall effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 14 parameters, 100% schema coverage, output schema exists, and annotations present, the description adds crucial context: response shape (slim vs full, root verdict), pagination (offset, limit), sorting options, relationship to other tools, rate limits, and critical caveats about exact matching. Nothing missing for agent decision-making.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%. Description adds extra meaning beyond schema: explains product token normalization (e.g., nginx_open_source), published_after/before usage with examples, cwe_id common values (XSS, SQL injection), include='full' trade-offs, cvss_min/max sentinel handling. This significantly aids parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Search CVE database with filters' and lists filter types. It distinguishes from siblings like cve_lookup, cwe_lookup, check_dependencies, tech_stack_cve_audit, and kev_detail, providing a specific verb and resource.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises when to use this tool (vulnerability discovery by criteria) and when not to (single CVE → cve_lookup; KEV details → kev_detail; dependency lists → check_dependencies; domain stacks → tech_stack_cve_audit). Also guides on include='full' vs default slim, sorting, and pagination.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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