ThreatMind learns your product from requirements, architecture, tickets, and source code, then finds, proves, and fixes the issues generic scanners miss across code, web, APIs, cloud, and mobile.
Here is how your product security posture is changing.
An authenticated user can access another account's records by modifying the object ID.
Bring context in. Send action out.
Replace disconnected point checks with one view of product, code, application, cloud, and mobile security.
ThreatMind AI reasons over requirements, user flows, and architecture to surface the abuse paths that matter — whether the system is planned, in build, or already live. It asks clarifying questions, and the model updates as you answer.
Explore threat modellingReview every pull request with SAST, SCA, IaC, secret, CI/CD pipeline, and malware scanning. ThreatMind AI then triages each signal in product context, reviews the business logic scanners can't see, and drafts the fix.
Explore code securityThreatMind AI plans and runs authorized assessments across web apps, REST, GraphQL, and WebSocket APIs, probing the authorization and business-logic flaws only product context reveals.
Explore web & api pentestingAssess identity, storage, network exposure, compute, secrets, and Kubernetes across AWS, Azure, GCP, Cloudflare, DigitalOcean, and more. Explore your asset inventory and identity blast radius, map findings to compliance frameworks, and keep posture current with continuous scans.
Explore cloud securityAnalyze Android, iOS, and cross-platform packages. ThreatMind AI triages the static evidence, builds the attack paths that matter, and drafts the code fix.
Explore mobile securityOne place to understand the product, review what changes, validate real exposure, and move supported findings into fixes.
36 capabilitiesacross 5 product surfaces
We know what it feels like to be the security engineer trying to understand what every team is designing, coding, deploying, and changing, while the product keeps moving.
The challenge is not a lack of effort. It is that the context needed to make a good security decision is scattered across the entire software lifecycle.
Product decisions live in documents and boards. Code moves across repositories. Infrastructure changes in cloud consoles. Security is expected to connect it all.
Specialist dashboards, isolated findings, and unfamiliar workflows make it difficult, even for security engineers, to quickly see what matters and why.
By the time a finding reaches the right engineer, its evidence, ownership, product context, and business impact are often separated.
One continuous workspace helps lean security teams understand change, focus on real risk, and support delivery without becoming the bottleneck.
ThreatMind pairs every finding with proof and plain-language impact, so the people who build the product can also secure it.
Findings arrive with evidence, business impact, and a suggested fix in plain language, so product engineers can triage, fix, and close risk without waiting for a specialist to translate.
Whether you're the first security hire or a five-person AppSec team supporting hundreds of engineers, keep evidence, ownership, and risk decisions in one place instead of five tools.
ThreatMind keeps context, evidence, remediation, and risk decisions connected as your product changes.
Add product docs, source, architecture, targets, or packages.
Connect business context to the product's real attack surface.
Scanner signals and AI reasoning produce evidence-led findings.
Focus the team on reachable, high-impact risk first.
Use AI AutoFix to turn a confirmed finding into a reviewable pull request.
Carry remediation and risk decisions into the next release.
ThreatMind reads the context scattered across product documents, architecture boards, issue trackers, files, and source code. That means findings reflect your users, trust boundaries, and business logic, not a generic checklist.
Deterministic scanners and controlled testing produce the signals. ThreatMind AI triages every one against product context, cutting noise and running the business-logic review generic tools can't. Each finding connects technical proof to the security and business impact your team needs to make a decision.
The invoice endpoint does not verify that the requested invoice belongs to the authenticated tenant.
ThreatMind AI can turn supported findings from code review, web and API pentesting, and mobile analysis into reviewable code fixes in under 10 minutes. Inspect the diff, open a pull request, or send the work to Jira, Asana, or Linear.
GitHub
GitLab
Bitbucket
Azure Repos
AWS CodeCommit
Jira
Asana
Linear
Slack
Notion
Miro
draw.io
const invoice = await db.invoice.find(id);- return Response.json(invoice);+ if (invoice.tenantId !== session.tenantId) {+ return new Response("Not found", { status: 404 });+ }+ return Response.json(invoice);Use the context you already maintain and deliver remediation into the tools your engineering and product teams already check every day. Repositories connect from GitHub, GitHub Enterprise, GitLab, Bitbucket Cloud and Data Center, Azure Repos, and AWS CodeCommit; tickets flow to Jira, Asana, or Linear; and Slack and email alerts land when results are ready.
Connect your workspaceSource & pull requests
Source & merge requests
Source & pull requests
Source & pull requests
Source & pull requests
Issues & context
Tasks & remediation
Issues & remediation
Workspace notifications
Product documents
Architecture boards
Architecture diagrams
Security tooling should help teams move with confidence. ThreatMind is built around explicit authorization, scoped targets, non-destructive evidence, and read-only cloud assessment.
Read common questionsTesting begins with explicit targets, constraints, and authorization.
Evidence is gathered without destructive payloads or load testing.
Cloud assessment focuses on configuration rather than application data.
Owners, tickets, fixes, closures, and accepted risks remain connected.
What teams usually want to know before bringing their first project into ThreatMind.
ThreatMind supports contextual threat modelling for planned, in-build, and live systems, automatic pull-request review with SAST, SCA, IaC, secret, CI/CD pipeline, and malware scanning, authorized web and API pentesting, multi-cloud security assessments with asset inventory, Kubernetes posture, and compliance views, and mobile application analysis across Android, iOS, and cross-platform apps.
No. Findings pair technical evidence with plain-language security and business impact so product and engineering teams can act. Security teams can also use ThreatMind to scale repeatable reviews across projects.
You can bring context from files, Notion, Jira, Asana, and Miro; connect repositories from GitHub, GitHub Enterprise, GitLab, Bitbucket Cloud and Data Center, Azure Repos, or AWS CodeCommit; and send findings back to Jira, Asana, Linear, or your pull requests, with Slack and email notifications when results are ready.
Assessments require an approved scope and authorization confirmation. The testing workflow is designed for controlled request volumes, non-destructive proof, and explicit safety constraints.
For supported high-confidence findings from code review, web and API pentesting, and mobile analysis, ThreatMind AI can generate a reviewable code fix and prepare the pull-request workflow in less than 10 minutes.
Use ThreatMind AI to turn supported code, web, API, and mobile findings into reviewable fixes.