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ZEN SecDB

by cloud.nttzen.secdb

ssvc_calculator

Compute CISA SSVC (Stakeholder-Specific Vulnerability Categorization) for a CVE.

What this tool does

Calculates the SSVC decision (Track, Track*, Attend, Act) using:

  • exploitation status

  • technical impact

  • automatable exploitation

  • mission prevalence (user-provided)

  • public well-being impact (user-provided)

This reflects CISA's official SSVC prioritization model.

When to use this tool

Use this tool when the user asks about:

  • how urgently a CVE should be remediated

  • CISA SSVC priority or risk category

  • a structured decision model for remediation

Inputs

  • cve_id: the vulnerability to evaluate (CVE-YYYY-NNNNN)

  • mission_prevalence: M, S, or E (must be provided by the user)

  • public_well_being_impact: M, A, or I (must be provided by the user)

Outputs

  • decision: one of Track, Track*, Attend, Act

  • exploitation

  • technical_impact

  • automatable

  • mission_prevalence

  • public_well_being_impact

  • mission_and_well_being_impact_value

  • vector_string

  • summary: Markdown explanation of the outcome

LLM usage guidelines

  • Always ask the user for mission_prevalence (M/S/E) and public_well_being_impact (M/A/I) before calling.

  • Never guess these values—SSVC depends on user context.

  • Use the summary to explain clearly why the decision was returned.

  • Combine with vulnerability_score or sightings_search if the user needs additional context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cve_idYesCVE ID
mission_prevalenceYes# Mission Prevalence A mission essential function (MEF) is a function directly related to accomplishing the organization's mission as set forth in its statutory or executive charter. Identifying MEFs is part of business continuity planning or crisis planning. In contrast to non-essential functions, an organization must perform a [MEF] during a disruption to normal operations. The mission is the reason an organization exists, and MEFs are how that mission is realized. Non- essential functions support the smooth delivery or success of MEFs rather than directly supporting the mission. ## Possible values - "M" or "Minimal" Neither support nor essential apply. The vulnerable component may be used within the entities, but it is not used as a mission-essential component, nor does it provide impactful support to mission-essential functions. - "S" or "Support" The vulnerable component only supports MEFs for two or more entities. - "E" or "Essential" The vulnerable component directly provides capabilities that constitute at least one MEF for at least one entity; component failure may (but does not necessarily) lead to overall mission failure. ## Instructions for LLM Ask the user for the "Mission Prevalence" value before calling the tool.
public_well_being_impactYes# Public Well-being Impact ## Possible values - "M" or "Minimal" **Type of Harm -> All**, The effect is below the threshold for all aspects described in material. - "A" or "Material" **Type of Harm -> Physical harm**, Does one or more of the following: - Causes physical distress or injury to system users. - Introduces occupational safety hazards. - Reduces and/or results in failure of cyber-physical system safety margins. **Type of Harm -> Environment**, Major externalities (property damage, environmental damage, etc.) are imposed on other parties. **Type of Harm -> Financial**, Financial losses likely lead to bankruptcy of multiple persons. **Type of Harm -> Psychological**, Widespread emotional or psychological harm, sufficient to necessitate counseling or therapy, impact populations of people. - "I" or "Irreversible" **Type of Harm -> Physical harm**, One or both of the following are true: - Multiple fatalities are likely. - The cyber-physical system, of which the vulnerable component is a part, isl ikely lost or destroyed. **Type of Harm -> Environment**, Extreme or serious externalities (immediate public health threat, environmental damage leading to small ecosystem collapse, etc.) are imposed on other parties. **Type of Harm -> Financial**, Social systems (elections, financial grid, etc.) supported by the software are destabilized and potentially collapse. **Type of Harm -> Psychological N/A ## Instructions for LLM Ask the user for the "Public Well-being Impact" value before calling the tool.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
summaryNoSummary
decisionYesDecision
automatableYesAutomatable
exploitationYesState of Exploitation (Evidence of Active Exploitation of a Vulnerability)
vector_stringYesSSVC Vector String
technical_impactYesTechnical Impact (Technical Impact of Exploiting the Vulnerability)
mission_prevalenceYesMission Prevalence (Impact on Mission Essential Functions of Relevant Entities)
public_well_being_impactYesPublic Well-being Impact
mission_and_well_being_impact_valueYesMission and Well-Being Impact Value

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool depends on user-provided context values, warns against guessing them, and explains the output includes a summary for interpretation. It doesn't cover potential errors, network behavior, or rate limits, but those are less critical for a calculation tool; the provided guidance is strong.

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

Conciseness5/5

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

The description is organized with clear headings (What, When, Inputs, Outputs, LLM usage guidelines) and is front-loaded with the main purpose. Each section is purposeful—no wasted words. Length is justified by the complexity of SSVC inputs and the need for LLM-specific instructions.

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?

The description covers the full context: what the tool does, when to use it, all three required parameters with requirements, output fields (including summary), and usage guidance. It even suggests combinations with sibling tools. The presence of an output schema lowers the need to explain return types, but the description still furnishes them, making it complete.

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% and both mission_prevalence and public_well_being_impact already have exhaustive descriptions with allowed values. The tool description reinforces these with concise 'M/S/E' and 'M/A/I' notation and adds the critical semantic that these must be user-provided. This adds value beyond the schema by operationalizing the parameters.

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 a specific verb+resource: 'Compute CISA SSVC for a CVE.' It clearly states the decision outputs (Track, Track*, Attend, Act) and distinguishes this tool from siblings like epss_timeseries or vulnerability_score by focusing on the SSVC prioritization model.

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 'When to use this tool' section explicitly lists user intents (urgency of remediation, CISA SSVC priority, structured decision model). It also provides exclusions/prerequisites by insisting the user must supply mission_prevalence and public_well_being_impact, and names alternative/complementary tools (vulnerability_score, sightings_search).

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

A4.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (e.g., vulnerability_search for discovery, vulnerability_info for full details, vulnerability_score for CVSS/EPSS, epss_timeseries for history). However, pairs like vulnerability_info vs. vulnerability_score and linux_audit vs. purl_audit have overlapping functionality, though detailed descriptions help differentiate them.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case pattern with a descriptor and an operation noun (e.g., vulnerability_info, linux_audit, sightings_search, ssvc_calculator). No mixed conventions or stylistic deviations are present.

Tool Count5/5

The 11 tools are well-scoped for a vulnerability intelligence server, covering search, details, scoring, trends, audits, reports, and prioritization. The count is within the expected 3-15 range and each tool contributes a distinct capability.

Completeness5/5

The tool surface covers the full vulnerability intelligence lifecycle: discovery (vulnerability_search), detailed lookup (vulnerability_info), risk scoring (vulnerability_score), EPSS history, real-world sightings, SSVC prioritization, audits for both OS packages and application dependencies, and aggregated reports. No obvious dead-end or missing critical operation is apparent.

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