autofix-cve-resolve

autofix-cve-resolve is a skill for Claude Code from opendatahub-io/autofix-skills. It costs 59 tokens per session (1,652 once invoked), scanned C, original, Apache-2.0.

An automated workflow for handling a Jira ticket about a software vulnerability known as a CVE. It routes each affected repository through scanning, fixing, verification, review, and pull-request steps using a state machine.

In plain words
What is it for?
Use it to process CVE details, map affected components to repositories, run the appropriate remediation agents, handle exceptions such as VEX decisions, and produce the final verdict.
Why use it?
It helps coordinate vulnerability remediation consistently across repositories while keeping the routing and status transitions deterministic.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions subagents.

Part of the autofix-skills plugin — 5 skills, 1 hook shipped together

Good fit Use it to process CVE details, map affected components to repositories, run the appropriate remediation agents, handle exceptions such as VEX decisions, and produce the final verdict.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opendatahub-io/autofix-skills/autofix-cve-resolve
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add opendatahub-io/autofix-skills --skill autofix-cve-resolve
Clone the repo
git clone --depth 1 https://github.com/opendatahub-io/autofix-skills

Made for: Claude Code.

Or install autofix-skills, the plugin that ships this one along with the rest of its 5 skills, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for autofix-cve-resolve

README.md
[![agentmods](https://agentmods.dev/badge/skills/opendatahub-io/autofix-skills/autofix-cve-resolve/github.svg)](https://agentmods.dev/skills/opendatahub-io/autofix-skills/autofix-cve-resolve)
Your own site
<a href="https://agentmods.dev/skills/opendatahub-io/autofix-skills/autofix-cve-resolve"><img src="https://agentmods.dev/badge/skills/opendatahub-io/autofix-skills/autofix-cve-resolve/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for autofix-cve-resolve

Your own site · 80×15
<a href="https://agentmods.dev/skills/opendatahub-io/autofix-skills/autofix-cve-resolve"><img src="https://agentmods.dev/badge/skills/opendatahub-io/autofix-skills/autofix-cve-resolve.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,652 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00059 $0.01652
Opus 5 $0.00030 $0.00826
Sonnet 5 $0.00012 $0.00330
Haiku 4.5 $0.00006 $0.00165

Measured 12d ago against content hash d014e855c91b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade C, and why

autofix-cve-resolve scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/check-existing-prs.sh, scripts/cve_pipeline.py, scripts/scan.sh, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

- NEVER run `rm -rf` on paths outside `/tmp`
skills/autofix-cve-resolve/SKILL.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: CVE Resolve Orchestrator

Orchestrate CVE remediation using a Python state machine for deterministic routing. You call specialized agent prompts in sequence for each affected repository and branch. You NEVER write fix code yourself — you only parse context, resolve repos, route to agents, create PRs, and write the verdict.

Initialize pipeline

python3 ${CLAUDE_SKILL_DIR}/scripts/cve_pipeline.py init tmp/cve-state.yaml

Loop: State machine dispatch

Repeat until the state machine reaches finalize:

# Get next action
python3 ${CLAUDE_SKILL_DIR}/scripts/cve_pipeline.py next tmp/cve-state.yaml

This returns a JSON object with:

  • action: what to do
  • prompt_file: which prompt file to read (null for orchestrator-only actions)
  • args: context for the action
  • phase: current phase

Execute the action

Based on the current phase:

parse — Extract CVE details from .autofix-context/ticket.json:

  • CVE ID, container, package, component, severity, Jira key
  • Resolve repositories via component-repository-mappings.json
  • Check for automation-ignore comments
  • Write repos to state:
    python3 ${CLAUDE_SKILL_DIR}/scripts/state.py set tmp/cve-state.yaml repos '[{"name":"org/repo","branches":["main","release-1.0"],"type":"upstream"}]'
    
  • Verify the CVE is publicly known before proceeding:
    python3 ${CLAUDE_SKILL_DIR}/scripts/cve_pipeline.py check-cve tmp/cve-state.yaml
    
    If this returns non-zero, the CVE is not found in public vulnerability databases and may be embargoed. Transition with embargoed instead of parsed.
  • Transition: parsed (or ignore if automation-ignore found, or embargoed if CVE is not publicly known)

scan — Read prompts/scan-agent.md and execute for the repo/branch from args. Read ONLY the verdict from autofix-output/cve-scan-result.json.

  • Transition: present or absent

route — Based on scan verdict:

  • present / present_by_version → transition: fix
  • absent / informational → transition: vex
  • in_base_image with no newer tag → transition: skip
  • scan_failed → transition: skip

Read the full file on GitHub · 157 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 157 lines · 59 tokens per session scan C d014e855c91b

Subscribe to this mod's changes

autofix-cve-resolve is a skill published in the GitHub repository opendatahub-io/autofix-skills (2 stars, last pushed 12d ago), licensed Apache-2.0. It adds 59 tokens to every session and 1,652 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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