I'm currently architecting a centralized security and code quality workflow for a multi-repository environment and have been evaluating Semgrep as our primary static analysis engine. One of the key requirements from our AppSec and platform engineering teams is to automatically convert critical findings into actionable tickets within our existing Jira Cloud project. The goal is to move beyond simply generating reports in CI/CD logs or dashboards.
From my initial research into Semgrep's documentation and the `semgrep-agent` tool, I see references to webhook integrations and the `--jira-*` flags in the CLI, but the practical, production-grade implementation details seem sparse. I'm particularly interested in the end-to-end data flow and how to manage the following concerns:
* **Trigger Mechanism:** Are teams primarily using the `semgrep-agent` in a scheduled (e.g., nightly) context to generate findings and then trigger webhooks, or are they embedding this directly into CI pipelines on every merge request? The trade-off here is between immediacy and potential noise.
* **Payload Transformation & Filtering:** The Semgrep findings JSON schema is quite detailed. I'm looking for examples of how to filter findings (e.g., only create tickets for `HIGH` confidence `ERROR` severity rules from our custom security ruleset) and map the relevant data to Jira fields (summary, description, labels, custom fields like 'CVSS Score').
* A practical example of a webhook payload transformer (e.g., a small Python service or a Node.js middleware) would be invaluable.
* **De-duplication Strategy:** How are you handling duplicate ticket creation for the same finding across multiple scans? I'm considering using a hash of the `check_id`, `path`, and `start line` to generate a unique identifier for Jira, perhaps stored in a custom field for comparison.
* **State Synchronization:** If a finding is fixed in the codebase, what's the best practice to close the linked Jira ticket? Is this typically a manual process, or have you automated a callback when Semgrep no longer reports the issue?
My current prototype approach involves a dedicated orchestration service that:
1. Runs `semgrep scan` with `--json` output.
2. Processes the JSON, applying severity/confidence filters and our custom business logic.
3. Uses the Jira REST API (via something like the `jira` Python package) to create or update issues.
However, this feels like reinventing a wheel that might already exist. Has anyone built a robust integration, perhaps using tools like Zapier, or a dedicated workflow in GitHub Actions/GitLab CI that handles this elegantly? I'm especially keen to see any configuration snippets or architectural diagrams.
—N
Latency is the enemy.