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ContrastAPI

by com.contrastcyber

CVE Lookup

cve_lookup
Read-onlyIdempotent

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cwes, date_removed when in_kev=true), NVD vulnerability_status (Analyzed/Modified/Awaiting Analysis/Deferred/Rejected/Withdrawn), cve_tags ('disputed' triggers [DISPUTED] summary prefix), affected products (CPE), references, patch availability, related CVEs.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_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_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_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_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

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly and idempotent hints, and the description adds rich behavioral context: default truncation of affected_products/references with 'honest count', behavior of include_* flags, tag-first patch detection, severity consensus logic, and rate limits. It also notes the 'disputed' tag effect on summary prefix.

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 long but information-dense, using semicolons and lists to pack many details. Every sentence adds value—no redundancy or fluff. It is front-loaded with the core purpose and then expands into optional behaviors, making it easy to scan.

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?

For a tool with 5 parameters, an output schema, and complex behaviors, the description covers the key use cases, return shape highlights, defaults, rate limits, and chaining opportunities. It fully supports an agent in deciding when and how to invoke the tool, even without seeing the output schema.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds valuable context beyond the schema: e.g., 'By default affected_products is truncated to the first 20 entries', 'total_reports the honest count', and 'tag-first patch detection'. It clarifies the purpose and side effects of the boolean parameters without repeating their full schema descriptions.

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 opens with 'Retrieve detailed CVE data by ID', giving a specific verb, resource, and lookup key. It also explicitly distinguishes itself from cve_search: 'Use for single-CVE details; use cve_search for queries by product/severity.'

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?

It clearly states when to use this tool ('single-CVE details') and when to use an alternative ('use cve_search for queries by product/severity'). It also explains when to pass optional flags (e.g., include_affected_products for bulk audits) and how to chain next_calls with kev_detail, cwe_lookup, and exploit_lookup.

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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TDQS

A4.5/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with differences between lookup/search/scan/audit for each domain. However, some overlap exists (e.g., email_mx vs email_security_posture, scan_headers vs contrast_scan) which could cause occasional confusion. Overall, boundaries are well-defined.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern (e.g., cve_lookup, check_headers, bulk_cve_lookup) with all lowercase underscores. Variations like kev_detail or ssl_check are minor and still predictable. No chaotic mixing of conventions.

Tool Count4/5

54 tools is high but justified by the broad cybersecurity scope (CVE, ATLAS, D3FEND, Sigma, domain, email, IOC, scanning). Some redundancy exists (e.g., three email-related tools), but the count is not excessive given the API's comprehensive feature set.

Completeness5/5

The tool set thoroughly covers the threat intelligence and domain investigation lifecycle: CVE/KEV/exploit/CWE, ATLAS/D3FEND/Sigma, DNS/WHOIS/SSL/subdomains, email security, IOC enrichment, and active scanning. No significant gaps are apparent for the stated cybersecurity purpose.

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