Threat Modeling Tools Compared: Which Ones Change What You Fix?

Threat modeling tools fall into three groups. Platforms such as IriusRisk, ThreatModeler, SD Elements, Microsoft Threat Modeling Tool and OWASP Threat Dragon start from a diagram or a questionnaire, and both now add AI: ThreatModeler to draft and update the model, IriusRisk to draft it. Threagile and OWASP pytm keep the model as code. AI-first tools such as Seezo, DevArmor and Pixee read designs or source.

Pick by how the model gets built, whether it stays current, and whether it changes which findings your team fixes.

If you have been asked to pick a threat modeling tool this quarter, you have probably read the same buyer's guides everyone else has. They compare how models get drawn, which methodologies each tool supports and what the free tier allows. Few of them ask what happens after the model exists.

That question decides whether the tool earns its renewal. A threat model that never touches the finding list or the pull request stays a document. This guide compares ten tools on the usual criteria and then on that one.

Pixee makes one of the ten tools. We describe every other tool's capabilities only from its own website (read November 5, 2026), describe Pixee from its own public pages and release notes, and hold it to the same columns.

How we compared these tools

We read each vendor's own pages and documentation on November 5, 2026. Where a vendor's site does not claim a capability, the tables say "Not stated." It means the site doesn't say it; the product may still do it. Ask in your proof of concept.

We did not run hands-on tests or use third-party reviews to describe any product's capabilities. News coverage and other buyer's guides appear only where we cite them for context.

We compared each tool on eight criteria that buyers use:

1. How the model is built. A diagram you draw, a questionnaire you answer, a file you write, or something the tool reads.

2. AI assistance. What the AI does, in the vendor's words.

3. How the model stays current. The stated mechanism. "Continuous" with no trigger counts as not stated.

4. Design-doc review. Whether the tool reads PRDs, specs or tickets before code exists.

5. Checking shipped code against the design. Whether it notices when the implementation drifts from what the design promised.

6. Ranking real findings. Whether the threat model changes the order of the scanner findings your team already has.

7. Turning findings into fixes. Whether anything leaves the tool as a code change, a ticket or guidance.

8. Deployment and price. What the vendor publishes.

Threat modeling tools at a glance

The first table covers how each tool builds and maintains the model. The second covers what the model changes downstream.

Building and maintaining the model

What the model changes downstream

Most tools are strong on building the model and say little about what happens to it afterward. The right-hand columns are nearly empty, and that is where your backlog lives.

What are the best AI threat modeling tools?

Five tools in this comparison use AI to build or maintain the model. They do different jobs, so "best" depends on which job you are hiring for.

IriusRisk (Jeff and Bex AI)

IriusRisk says Jeff generates threat model diagrams from text prompts, image uploads, user stories, documentation, meeting transcripts or code, and Bex AI assesses the security of your software inside Jira. The core product stays diagram-led, and there is a free Community Edition with three threat models.

Best fit. Teams that want a structured, diagram-led practice with AI to speed up drawing.

Test in a proof of concept. Give Jeff a real architecture description and count how much of the diagram your reviewer has to redraw.

ThreatModeler Nexus

ThreatModeler calls Nexus "the agentic platform for secure design." Its site says NexusAI creates and analyzes threat models, identifies architecture changes and proposes updates for review. The Secure Design Graph links architecture, threats, controls and security decisions.

Best fit. Enterprises standardizing threat modeling across many teams who want agents to do the first pass.

Test in a proof of concept. Change an architecture and watch what Nexus proposes, and how a reviewer accepts or rejects it.

Seezo

Seezo describes "Automated Threat Modeling and Security Design Reviews." It reads feature descriptions where teams already write them (Confluence, Google Docs, SharePoint, Jira, Slack and Notion) and maps each threat model to security requirements.

Best fit. Teams whose biggest gap is design review before code, at the pace product teams write features.

Test in a proof of concept. Feed it a real, messy PRD and check whether the requirements it writes are ones your engineers would accept.

DevArmor

DevArmor pitches "a living security context" for developers and coding agents. It pulls design specs through integrations, can rebuild context from code when documentation is missing, and enforces Policy-as-Code on every pull request.

Best fit. Teams that want design decisions enforced at merge time.

Test in a proof of concept. Take one approved design decision and see whether a pull request that breaks it gets caught, and how the reason is shown.

Pixee

Pixee reads each repository's source and generates a threat model in five to ten minutes. The model covers entry points, trust boundaries, sensitive assets and dependency risk. Pixee then uses that model to re-rank the findings it has already triaged, and opens merge-ready fixes that match your code conventions. Foresight adds design-doc review and drift checks on pull requests.

Best fit. Teams with more repositories than they can model by hand, who want the model to change which findings get fixed.

Test in a proof of concept. Run it on one of your own repositories and compare the re-ranked finding list against what your team would have picked.

What AI can and can't do here

Every tool in this group, Pixee included, produces a generated starting point. A security reviewer still checks it. Generated models are fast at breadth and can miss business context that lives in someone's head. Ask each vendor how a reviewer corrects the model, and whether that correction survives the next refresh.

What are the alternatives to IriusRisk and ThreatModeler?

ThreatModeler announced on January 8, 2026 that it had acquired IriusRisk (SiliconANGLE). IriusRisk's own site now says "IriusRisk is now part of ThreatModeler," and both companies still run their own sites.

An acquisition on its own doesn't require a switch. Before renewal, ask your account team three things:

• Which product line gets the roadmap, and what happens to the other.

• Whether your models, libraries and integrations carry over if the products merge.

• Whether pricing or contract terms change at renewal.

If the answers push you to look elsewhere, pick the alternative by the job you need done.

• Free and diagram-first. OWASP Threat Dragon runs as a desktop app or self-hosted web app under Apache 2.0. Microsoft Threat Modeling Tool is free for Windows and built around STRIDE per element.

• Threat modeling as code. Threagile keeps the model in YAML and runs as a CLI, Docker image or REST server. OWASP pytm keeps it in Python.

• Requirements-led. SD Elements starts from a project survey and produces security requirements and countermeasures for your issue tracker.

• Design-review-led. Seezo and DevArmor read design documents and tickets. DevArmor also enforces policy on pull requests.

• Code-grounded and finding-ranking. Pixee reads each repository's source, re-ranks your triaged SAST findings against the model and opens merge-ready fixes.

How does Pixee compare to IriusRisk?

They are different shapes. If the job is diagram-led threat modeling with a free entry point, technical and compliance reporting, and AI help drawing the diagram, IriusRisk fits.

If the job is a current model for every repository that also decides which findings get fixed, Pixee fits. Pixee reads the repository's source instead of a diagram. It re-ranks triaged findings against the model with a 0 to 100 priority, a tier and a rationale. Then it opens merge-ready fixes.

Foresight adds design-doc review and drift checks on pull requests. One context graph feeds both the design-stage review and the triage and fix work.

Some teams will run both. A security architect can keep modeling new systems in a diagram tool while Pixee keeps a code-grounded model on every existing repository.

The column the listicles skip: does the model change what gets fixed?

Most buyer's guides for this search compare how models get drawn and maintained. One of them, VerSprite's comparison (updated October 12, 2026), lists "weakness and vulnerability correlation" as a criterion. It asks whether scanner findings "can be connected to the threat model instead of remaining separate evidence sources." It does not describe a named tool that re-ranks scanner findings against the model.

That matters because your scanners already tell you what is vulnerable. They can't tell you what is dangerous in your system. That depends on where the code sits, what it is exposed to and what it can reach, which is exactly what a threat model records. If the model and the finding list never meet, your team still works the list by scanner severity.

Here is how Pixee connects them. Finding Overlays take the SAST findings Pixee has already triaged for exploitability and score each one against the repository's threat model. Each finding gets a 0 to 100 priority, a tier and a rationale that names the threat-model element that moved it. Findings also cluster on threat-model axes:

• Entry point

• Actor

• Trust boundary

• Sensitive asset

• Vulnerability class

A long list resolves into a handful of real problems.

Take two SQL injection findings with the same scanner severity. One sits behind an internet-facing entry point and reaches customer records. The other sits in an internal admin script with no network exposure.

Overlays rank the first above the second and cite the entry point and the sensitive asset in the rationale. Pixee then opens a merge-ready fix for the first, written in the repository's own conventions.

The same context works earlier in the lifecycle. Say a design promises that every data export writes an audit log entry, and the pull request ships the export endpoint with no logging. Foresight flags the drift with the design line and the diff side by side, before the feature ships.

How to choose a threat modeling tool

1. Define the job. Decide whether you need a diagramming practice, design review before code, a model per repository, or a model that changes what gets fixed. Most teams need more than one.

2. Count the repositories. A hand-drawn model per application works for a dozen systems. It breaks at hundreds.

3. Decide who maintains the model. If the answer is "the architect, when there is time," expect the model to age. Prefer a tool with a stated refresh trigger, and ask whether it ships today. Pixee's event-driven refresh is rolling out; on-demand regeneration ships now.

4. Test staying current on a real change. Merge a meaningful change during the trial and see what the tool does without being asked.

5. Test whether findings re-rank. Load your real scanner findings and check whether the order changes, and whether the tool explains why.

6. Check deployment and data handling. Ask where your code or designs go, which models process them and what the vendor keeps.

7. Run the proof of concept on your own repository. A vendor's sample model shows the interface. Your repository shows whether the tool understands your system.

Frequently asked questions

Are IriusRisk and ThreatModeler the same product now?

They are one company with two products so far. ThreatModeler announced on January 8, 2026 that it had acquired IriusRisk, and IriusRisk's site says it "is now part of ThreatModeler." Both products still have their own sites, so ask your account team which roadmap your product sits on.

Can AI generate a threat model from source code?

Yes. Pixee reads a repository's source and generates a threat model covering entry points, trust boundaries, sensitive assets and dependency risk, typically in five to ten minutes. DevArmor says it can reconstruct security context from code, IriusRisk says its Jeff assistant can draft a threat model diagram from text prompts, image uploads, user stories, documentation, meeting transcripts or code, and SD Elements can answer survey questions by scanning a Git repository. Treat any generated model as a starting point that a reviewer checks.

Which threat modeling tools are free or open source?

OWASP Threat Dragon (Apache 2.0), Threagile (MIT) and OWASP pytm are open source. Microsoft Threat Modeling Tool is a free download for Windows 10 or later. IriusRisk offers a free Community Edition limited to three threat models, and Seezo offers a free start.

How do you keep a threat model up to date?

Tie the model to an event, not a calendar. As-code tools such as Threagile and pytm update when someone edits the model file. ThreatModeler says NexusAI identifies architecture changes and proposes updates for review. Pixee's event-driven refresh, rolling out now, re-checks the model on default-branch pushes and records why it did or didn't revise it.

Do threat modeling tools replace a security review?

No. They make the review faster and wider. A generated model gets a reviewer oriented in an unfamiliar application quickly, with entry points and attack surface laid out up front. The reviewer still decides what matters and corrects what the tool got wrong.

So which tool changes what your team fixes?

Most of the tools here help you build a better model, and that has value. Every cell in our tables, Pixee's included, reflects what each vendor says about its own product. If you also need the model to change what your team fixes this sprint, test for it directly. Load your own findings, merge a real change, and see whether the order of the work moves.

Pixee reads each repository you turn it on for, re-ranks the findings it has already triaged against that model, and opens merge-ready fixes. Foresight brings the same context to design review and to drift checks on pull requests. Managing more repositories than you can threat-model by hand? Let's talk.

Related reading: Living threat models · Foresight · Triage automation