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cve_lookup

Read-onlyIdempotent

Get detailed CVE data by ID: severity scores, EPSS, KEV status, patch availability, affected products, and references.

Instructions

Retrieve detailed CVE data by ID: description, CVSS v3.1 + vector, CVSS v2 (always emitted), EPSS score + percentile, CISA KEV status (expanded: due_date, required_action, ransomware flag, vendor_project, product, vulnerability_name, short_description, notes, cwes, date_removed when in_kev=true), NVD vulnerability_status (Analyzed/Modified/Awaiting Analysis/Deferred/Rejected/Withdrawn), cve_tags ('disputed' triggers [DISPUTED] summary prefix), affected products (CPE), references, patch availability, related CVEs. By default affected_products is truncated to the first 20 entries (total_products reports the honest count) and references to the first 10 (total_references reports the honest count). Pass include_affected_products=true and/or include_full_references=true for the complete lists. Pass include_reference_tags=true to receive structured references_full=[{url, tags, source}] (NVD upstream tags + source provenance) — also activates tag-first patch detection. Pass include_severity_breakdown=true to receive severity_sources/consensus/disagreement (multi-source view of NVD/MITRE/GHSA/OSV severity assessments). Use for single-CVE details; use cve_search for queries by product/severity. Response carries next_calls — chain with kev_detail when kev.in_kev=true, with cwe_lookup on each CWE in cwes (up to 3 pivots), and with exploit_lookup for public PoC availability. Free: 30/hr, Pro: 500/hr. Returns {cve_id, summary, description, severity, cvss_v3, cvss_v2, cvss_v2_vector, cvss_breakdown, cwe_id, cwes, vulnerability_status, cve_tags, published, modified, sources, first_seen_source, first_seen_at, epss, kev (in_kev, date_added, due_date, required_action, known_ransomware_use, vendor_project, product, vulnerability_name, short_description, notes, cwes, date_removed), affected_products (first 20 by default), total_products, references (first 10 by default), total_references, total_references_unique, references_full (only when include_reference_tags=true), severity_sources/severity_consensus/severity_disagreement (only when include_severity_breakdown=true), patch_available, related_cves, verdict, next_calls}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cve_idYesCVE identifier in format CVE-YYYY-NNNNN (e.g. 'CVE-2024-3094', 'CVE-2023-44487')
include_affected_productsNoReturn the full affected_products list (default: False, returns first 20). Set True for bulk audits or dependency scanning of Log4j-class CVEs with 50+ products.
include_full_referencesNoReturn the full references list (default: True, returns all references). total_references is always emitted with the honest count; patch URL detection always runs against the full list, so patch_url/patch_available are unaffected. Set False to truncate to first 10 entries when bandwidth-bound.
include_reference_tagsNoReturn structured references_full field with [{url, tags, source}] objects (NVD reference tags + source provenance) (default: True). Inspects which references are vendor patches (tags=['Patch']) vs exploit PoCs (tags=['Exploit']) vs mailing list discussions. Patch URL detection is tag-first when refs_with_tags is populated; legacy cached rows fall back to regex. Set False to skip the structured shape for legacy clients.
include_severity_breakdownNoReturn severity_sources, severity_consensus, and severity_disagreement (multi-source severity breakdown) (default: True). Surfaces vendor disputes (e.g. CVE-2023-38545 NVD-CRITICAL vs GHSA-HIGH). cvss_v2 and cvss_v2_vector are always emitted (additive non-opt-in). Consensus uses majority-bucket vote with highest-severity tie-break (CRITICAL > HIGH > MEDIUM > LOW > NONE). Set False to skip if downstream cannot tolerate the extra fields.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds significant behavioral context: rate limits (30/hr free, 500/hr Pro), default truncation of affected_products and references, and how to override these defaults. It also explains the output structure and chaining via next_calls. No contradictions 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?

The description is verbose but well-structured, front-loading the core functionality and then expanding on optional parameters and edge cases. Every sentence adds value, though the length could be slightly trimmed without losing clarity. The structure is logical, with clear sections.

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 the tool's complexity (numerous fields, conditional outputs, multiple optional parameters, and rate limits), the description covers all necessary contextual information. It explains default behaviors, how to access full data, rate limits, and even hints at chaining with other tools via next_calls. The existence of an output schema reduces the burden, but the description still adds substantial context.

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 coverage is 100% with detailed descriptions. The description enriches parameter semantics by providing real-world usage examples (e.g., 'Set True for bulk audits of Log4j-class CVEs') and explaining defaults and trade-offs (e.g., bandwidth considerations for include_full_references).

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?

The description explicitly states the tool retrieves detailed CVE data by ID and lists the specific data elements. It distinguishes from the sibling cve_search tool, which is for queries by product/severity, making the purpose clear and differentiated.

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?

The description provides explicit guidance on when to use this tool ('single-CVE details') and when to use cve_search (queries by product/severity). It also advises on conditions for using optional parameters, such as setting include_affected_products=true for bulk audits.

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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