Continuous threat modeling keeps the threat model current as the system evolves, instead of producing it once at design time. Reykur runs that loop from the user story to the merged pull request, and verifies that every control was actually built.
The diagram is accurate the day it is drawn. Updating means starting over, so teams don't, and the model drifts further from the running system with every deploy.
Most tools stop at enumerating threats. Nobody confirms the recommended control was actually built, so “we did a threat model” says little about real risk.
Security shows up after the code is written, in a separate tool, owned by someone else. That means rework, rollbacks and broken developer flow.
A handful of security people support hundreds of engineers shipping every day. They cannot re-model every service and every change by hand.
Follow a single feature around the loop: ingested from the story, modeled, embedded in the ticket, built, and verified at the PR.
The moment a story is created in Jira or Linear, Reykur picks it up. Nobody has to remember to start a threat model.
As a user, I want to sign in with my existing Google or Okta account, so I never have to manage another password.
Components, data flows, trust boundaries and data assets are mapped on a real-time, collaborative canvas, and kept live instead of redrawn for the annual review.
Reykur writes the threats, recommended controls and security requirements straight into the issue developers already work in.
Security is specified before code is written, so developers build the controls in as part of the story, without needing to be security experts.
At the pull request, Reykur verifies the recommended control was actually implemented. It is the question every threat modeling framework ends on, and the one almost nobody answers: did we do a good job?
Jira
Linear
GitHub
GitLabInside the continuous loop, PR-time verification closes a gap no review can close on its own: one traceable line from threat to verified implementation. Bring a manual deep dive to your most critical components and Reykur proves those controls shipped too.
Automated threat modeling generates a model from what already exists. Continuous threat modeling keeps that model current from the first user story and verifies the controls it calls for.
The same mechanism pays off differently for every role: guidance for devs, coverage for AppSec, assurance for leadership, predictability for product.
From Autodesk's Continuous Threat Modeling methodology, written by Izar Tarandach and published as an open handbook. It was designed so that development teams could threat model their own work inside agile sprints, with less dependence on security specialists.
Automated threat modeling is the tooling: generating a model from code and infrastructure, proposing threats and controls, and checking pull requests against them. Continuous threat modeling is the practice of keeping that model current from the first user story onwards. Reykur does both. The model updates automatically on every story, and each control is verified at the pull request.
A new user story in Jira or Linear, a change to the design on the canvas, a plan from a coding agent, or a pull request. Each event updates the parts of the model it touches. Nothing is redrawn from scratch.
The controls that were written into the ticket. Reykur reads the change, checks each control against it and reports which are met, partly met or missing. The result can gate the merge or simply inform the reviewer.
No. High-risk components still deserve a deliberate review. Reykur runs those on a live canvas as a traditional threat modeling session, and the continuous loop keeps the resulting model current afterwards.
Scanners look for known bug patterns in code that already exists. Continuous threat modeling works at the design level, before code is written, and catches flaws a scanner cannot see, such as a missing authorization check between two services or an unencrypted data flow.
Reykur listens for new stories, writes the threats and controls back into the ticket, and updates the ticket when the pull request is verified. Engineers keep working in the tracker and the repository they already use.
A traceable record for each change: the threat, the control it called for, the ticket the control was written into and the pull request where it was verified. That record is the evidence for secure design and change management controls in SOC 2, ISO 27001, PCI DSS and DORA.
Updated 6 October 2026
Watch the loop close end to end in a 20 minute walkthrough: design, ticket and PR.
Agent plans reviewed against your threat model, before any code is written.
ExploreRun a design review on a collaborative canvas, without it dying on a whiteboard.
ExploreBe among the first to try Reykur and help shape continuous product security.
No spam. We'll only email you about Reykur.