SECOPS
Generate an AI Security Brief for Each High-Risk GitLab MR
When an MR is labeled high-risk, an agent reads the diff and linked issues, writes a plain-language security review brief highlighting the threat surface.
How it runs
The automated pipeline, trigger to output.
- TriggerGitLab high-risk label added to MRGitLab
- ActionFetch diff, description, and linked issuesGitLab
- ActionAgent drafts security review brief + checklistOpenAI
- ActionPost brief as MR commentGitLab
- OutputSend brief to assigned reviewer in SlackSlack
What it does
Gives the assigned security reviewer a head start by producing a focused brief of what changed, why it's risky, and what to scrutinize, drawn from the actual diff and the MR's linked context.
When to use it
Use this when reviewers spend the first 20 minutes of every high-risk MR just reconstructing context. The brief shrinks that to a skim and standardizes what gets checked.
How it works
- 1A GitLab webhook fires when the `sec/high` or `sec/critical` label is added to an MR.
- 2An agent fetches the full diff, the MR description, and any linked issues through the GitLab API.
- 3The agent analyzes the change for threat surface (new endpoints, auth changes, input handling, dependency bumps) and drafts a structured brief with a suggested review checklist.
- 4It posts the brief as a GitLab MR comment so it lives with the code.
- 5It sends the same brief to the assigned reviewer in Slack with a direct link.
Set it up
What you configure once, before turning it on.
- 1Connect GitLabRepos, MRs, pipelines, registry.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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