ZEN SecDB

linux_audit

Read-onlyIdempotent

Perform a Linux package vulnerability audit using SecDB.

What this tool does

Analyzes the installed packages of a Linux system-identified by OS and OS version-and returns vulnerability information plus a Markdown summary. The audit results are based exclusively on the package list provided by the user.

When to use this tool

Use this tool when the user wants to determine:

whether installed packages contain known vulnerabilities
whether a host, VM, container, or base image is affected by security advisories
which packages require patching or upgrading

If the user does not know the valid values for os or version, first call the linux_os tool to retrieve the exact supported combinations.

Inputs

os: Linux distribution identifier supported by SecDB (use linux_os to obtain allowed values).
version: OS version or codename corresponding to the selected distribution.
packages: list of installed packages, one per line, generated using the appropriate system command:

For RPM-based distributions (RHEL, CentOS, Rocky, Alma, SUSE)

rpm -qa --qf '%{NAME}-%{VERSION}-%{RELEASE}.%{ARCH}\n'

For DEB-based distributions (Ubuntu, Debian)

dpkg-query -W -f='${Package} ${Version} ${Architecture}\n'

For Alpine Linux

apk list -I

The raw output of these commands can be passed directly as the packages input (one package per line).

...
python3 3.12.3-0ubuntu2.1 amd64
systemd 255.4-1ubuntu8.10 amd64
tmux 3.4-1ubuntu0.1 amd64
...

Outputs

report: structured objects describing the advisories affecting the audited packages.
summary: Markdown summary including total vulnerabilities, severity breakdown, and key findings.

LLM usage guidelines

Never guess whether a package is vulnerable-always call this tool for Linux audits.
If os or version is unclear or missing, call linux_os and ask the user to choose a valid combination.
Normalize the package list to “one entry per line” if the user provides unstructured output.
The summary is already Markdown and can be shown directly.
Use report when deeper technical analysis is required.

Input Schema

TableJSON Schema

Name	Required	Description
`os`	Yes	Linux distribution identifier supported by SecDB (use `linux_os` to obtain allowed values)
`version`	Yes	OS version or codename corresponding to the selected distribution
`packages`	Yes	list of installed packages, one per line, generated using the appropriate system command

Output Schema

TableJSON Schema

Name	Required	Description	Default
`report`	No
`summary`	No	Markdown summary including total vulnerabilities, severity breakdown, and key findings

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 2, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely new behavioral context: results are based exclusively on the user-supplied package list, the summary is pre-rendered Markdown safe to show directly, and the agent is warned never to guess vulnerability status. It stops short of stating failure modes (e.g., unsupported os/version handling) or limits.

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?

Heavily structured with front-loaded headers and zero wasted sentences; the command snippets and example output directly serve the tool's strict input format requirement. Minor restatement of schema field text is offset by the otherwise high signal density.

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?

An output schema exists, yet the description still labels the two return fields (`report`, `summary`) and their intended use cases. Combined with input format guidance and prerequisite routing to `linux_os`, an agent has everything needed to invoke this tool correctly.

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%, so the baseline is 3. The description goes beyond the schema by giving the exact generation commands per distro family (rpm -qa, dpkg-query, apk list) and a sample package list, which is real added meaning for the `packages` parameter that the schema does not supply.

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?

States a specific verb (audit), a specific resource (installed Linux packages), and the backing data source (SecDB). It is clearly distinguishable from the sibling `purl_audit` (which would audit by package URL) and from `linux_os` (which only enumerates supported OS/version pairs).

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?

Contains an explicit 'When to use this tool' section with three concrete triggering conditions, plus an explicit routing rule: if `os`/`version` are unknown, call `linux_os` first. This is a direct when/when-not/alternative disclosure.

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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