Pay by bank, with settlement webhooks
Threat modeling for every story, not once a year
Secure before it's built.
Every Jira story is threat-modeled before a line of code exists. AI does the exhaustive analysis, your security leads make every call, and every finding cites a published standard. Approved threats ship to your teams as security tests, and CI proves each fix. Sprint after sprint, across every project.
Set up within one business day. Cancel any time. SecureSprints cloud; on-premises by arrangement.
D1Threat model
Before buildPAY-142As a business customer, I can pay an invoice straight from my bank account, and the merchant's system is told by webhook when it settles.
FullAPIIdentityThird-party bankWebhooks
- 0Triage
- 1Business objectives
- 2Technical scope
- 3Decomposition
- 4Threat analysis
- 5Weakness analysis
- 6Attack modeling
- 7Risk
All 8 stages confirmed by a person
Stage 4 · Threats found1 critical · 4 high · 1 medium · 1 low
- SA forged settlement webhook marks an unpaid invoice paidCriticalCWE-345
- TA replayed webhook settles the same invoice twiceHighCWE-294
- SThe consent redirect hands the bank's code to an attackerHighCWE-601
- EChanging the invoice ID pays or reads another tenant's invoiceHighCWE-639
- EA merchant's webhook URL can reach internal servicesHighCWE-918
- IBank account numbers land in application logsMediumCWE-532
- SThe bank's consent page can be framed to trick a clickLowCWE-1021
Independent reviewClean
Stage 3 · Data flow3 trust boundaries
CustomerBank consentPayments APILedgerMerchant webhook
Stage 6 · Attack paths
Stage 7 · Security testsGiven / When / Then
- An unsigned or stale webhook is rejectedCI test
- The same event ID settles onceCI test
- Only registered return URLs are acceptedCI test
- Another tenant's invoice returns 404CI test
- Webhooks to private addresses are refusedCI test
- Account numbers are masked in logsLead review
Accepted riskTH-7 · bank-hosted page · R. Iyer · review 15 Jan
ApprovedR. Iyer · ready for build
In progress 1
Team invite links
Implemented 0
Verified 2
Login rate limits
The search space
We explore13.6 trillionways to discover security threats.
Only possible with AI. That's how you SecureSprints.
A workshop covers the threats people remember. SecureSprints covers the threats the method demands, for every story, in every project, every sprint.
- Every storytakes the path its change needs: full, delta or checklist
- Every elementof the design is checked against each framework that applies
- Every checkends in a finding or a recorded reason, never a silent skip
How we count
- Entry
How a story enters
The kinds of change it combines, such as API, mobile, AI, cloud and CI/CD, the lens packs that apply to them, and how deep to go: full, delta or checklist.
- Design
What each part of the design is checked against
Every actor, data flow, data store, process and AI component is checked against the framework categories for its kind. AI and autonomous AI components get the most. A typical story runs 60 to 160 checks.
- Gates
How the work moves through the gates
Autopilot settings, independent review rounds on the reviewed stages, and the final decision: approve, or send back to a stage.
With required packs only, it is about 294 billion paths. This counts method routes only. Each story's own components, flows and data multiply it again.
The gap
Pentests check what shipped, once or twice a year. SecureSprints covers every story, from planning to production.
Model · before build
Verify · in the sprint
Watch · every change
Pentest and scans · once or twice a year
- PlanStory triaged and threat-modeled, stages 0 to 7
- DesignModel approved by a named lead; developer brief issued
- BuildTasks claimed from the inventory; PR check on every pull request
- TestCI results verify each task; failures reopen
- ReleaseShips with every threat verified or risk accepted
- RunA removed control reopens; touched stories are re-modeled
Every story, not a sample. Workshops reach a few epics a quarter. SecureSprints models every story your teams commit to.
Design flaws, caught at their cheapest. At planning a fix is a decision. After a pentest it is a sprint of rework.
Evidence that stands up to audit. Every threat, decision and fix traces to a person, a standard and a CI run.
Inside a SecureSprinted story
What one story carries into the build
This story gives an AI support assistant the power to issue refunds. Before anyone writes code, SecureSprints has mapped it, found the threats a design review would likely miss, and turned each one into a test. Jira is read, never written.
1Story and triage Stage 0
Refunds from the support assistant
As a support lead, I want the chat assistant to issue refunds up to $200, so customers get answers without waiting for an agent.
- 0Triage
- 1Goals
- 2Scope
- 3Flow
- 4Threats
- 5Weakness
- 6Attack
- 7Risk
2Data flow and trust boundaries Stage 3
3Threats, with evidence Stages 4–6
4Coverage Every check accounted for
- Checks run
- 142
- Findings
- 9
- Closed with a reason
- 133
- Skipped
- 0
5Security tests, review, approval Stage 7
- 1
Triage reads the story, not a form
AI proposes the depth and every kind of change involved: here, an autonomous AI agent calling a payments API. A triage that misses something the story says is challenged before anyone confirms it.
- 2
The design, mapped
Stage three maps every actor, flow, store and AI component, and where trust changes. Each element is checked against the frameworks for its kind. AI and autonomous components get the deepest checks.
- 3
Threats with evidence and a standard
Each finding quotes the story or is marked as an inference, and cites OWASP or MITRE from a version-pinned library. Threats proposed by built-in rules must each be answered.
- 4
Coverage you can show an auditor
Every check ends in a finding or a recorded reason. Nothing is skipped silently, so "we looked at it" is provable.
- 5
Tests, a challenge, a named sign-off
Stage seven writes each threat as a Given / When / Then test with a severity. A separate AI reviewer challenges the model, and your approver signs off the exact version your team builds.
One sprint, ten working days
How a team SecureSprints
D1Model
Every story, modeled
Each committed story is triaged and taken through seven stages. AI drafts; your modeller confirms.
PAY-140 · Saved cardsDeltaPAY-218 · Refund assistantFullPAY-145 · Invoice exportChecklistPAY-147 · Copy changeNot relevantD2Approve
Challenged, then signed
An independent AI reviewer tests the model. A named approver signs off the exact version.
PAY-218 · v3
Independent reviewCleanR. IyerApprovedDeveloper briefIssuedD5Build
Built from the inventory
Developers and their coding agents claim the tasks. The PR check flags any open threat a change touches.
TH-1 · coding agentIn progressPR #511 · PR checkPassedD8Verify
Proven by CI
CI results close each task. Nobody verifies their own work. A failing test reopens it.
TH-1 · build 1186VerifiedTH-2 · build 1186VerifiedTH-3 · build 1186ReopenedTH-3 · build 1187VerifiedD10Close
Closed, and learned
Every task verified or formally accepted. The baseline grows, so the next story starts ahead.
Tasks verified41 / 41Accepted risks1Project baselineUpdated
The Closure Loop · once SecureSprinted, always checked
Every fix comes back to be checked.
Approved threats land in the threat inventory as tasks: open, planned, in progress, implemented, then verified. Verification comes from CI test results, or from a lead who isn't the implementer. Nobody verifies their own work.
The loop keeps watching. A verified control whose code is removed is reopened, and a story whose threats a later change touches is suggested for a delta re-model.
- Verified
- Proven by CI, or by a lead who didn't build it
- Reopened
- A failing test or a removed control sends it back
- Accepted
- Risk accepted by an approver, with a reason, an owner and a review date
Grounded AI
Eight controls on every finding
No finding reaches your inventory until it has passed all eight. Each control leaves a record your auditors can read.
- 1
Redaction first
Personal and secret data is removed before any AI sees the story.
- 2
Pinned standards library
References come only from a version-pinned library. Recalled ones are refused.
- 3
Evidence on every finding
Each finding quotes the story or profile, or is marked as an inference.
- 4
Full coverage
Every element is checked against each framework that applies. Skips need a reason.
- 5
Independent AI review
A second AI challenges the first. Its findings block until fixed or overridden in writing.
- 6
Named human decision
A person confirms every stage, approval and accepted risk.
- 7
Tamper-evident log
Every action is hash-chained. A later edit is detectable.
- 8
Measured accuracy
Each release is scored on labelled reference designs. Regressions can't pass unnoticed.
A chat message instructs the assistant to refund an order
Six AI roles, and what each one never does
| Role | Does | Never |
|---|---|---|
| Author | Drafts the project profile and each modeling stage | Confirms, approves, exports or writes to Jira |
| Independent reviewer | Challenges each reviewed stage, apart from the author | Edits the model |
| Misuse-case analyst | Works out how a feature could be abused or fail | Changes any stage |
| Fix proposer | Suggests fixes and pre-checks a change | Marks anything verified |
| Code mapper | Links threats to the code they concern | Reads secrets or follows instructions found in code |
| Guide | Answers how-to questions in the app | Acts on your behalf |
Tools and standards
17 published standards. One pinned library.
Every threat, weakness and attack pattern SecureSprints cites comes from this library, pinned to a version. Any finding can be traced to its source, in any audit, years later.
03Methods
How each model is built
- PASTASeven stages
- STRIDEThreat types
- LINDDUNPrivacy threats
05OWASP · Applications
What to require of web, API and mobile code
- Top 10 (2025)Web risks
- API Security Top 10API risks
- ASVS 5.0Requirements
- MASVSMobile
- Risk RatingSeverity
02OWASP · AI
For LLM and agentic features
- Top 10 for LLM Applications (2025)LLM risks
- Top 10 for Agentic Applications (2026)Agent risks
02OWASP · Platform
For pipelines and clusters
- CI/CD Top 10Pipelines
- Kubernetes Top 10 (2025)Clusters
05MITRE
What attackers exploit, and how to stop it
- CWEWeaknesses
- CAPECAttack patterns
- ATT&CKTechniques
- ATLASAI attacks
- D3FENDCountermeasures
Connects and maps to
Jira is read, never written
- JiraStories
- Your code hostPR check
- Your CIVerification
- Teams · SlackCheckpoints
Named for reference. SecureSprints is not certified or endorsed by OWASP or MITRE. Azure DevOps, GitHub Issues and GitLab boards are planned. Confirm at launch
By role
Everyone SecureSprints, from their own seat.
Each role has its own home in SecureSprints and sees the part of the work it owns.
Security champion · architect
Model stories fast, without missing anything.
- Pick the sprint's stories, one at a time or as a batch.
- Confirm the triage, then each stage. Answer open questions, or send a stage back.
- Let autopilot confirm the low-risk stages. It still stops for every real decision.
- Send the finished model for approval.
Security lead · CISO's team
Sign off models you can trust.
- Read the assembled model, with every reference already checked against the library.
- Approve the exact content, or send it back to any stage.
- Accept a risk with a reason, an owner and a review date, or mark a threat not applicable.
- Verify tasks that you didn't implement.
Engineer
Know exactly what to build, and see it marked done.
- Pick up tasks from the threat inventory, the developer brief, or your coding agent.
- Build to a security test written as Given / When / Then.
- See the PR check on your pull request before review.
- Push. CI test results verify the task.
Platform · pipelines Coming soon
Wire it into repositories, pipelines and coding agents.
- Propose the repository connection. An approver confirms it.
- Send CI test results to verify tasks.
- Set the PR check to inform, warn or block.
- See the integration's traffic when something misbehaves.
Auditor · product owner
See a project's security posture, without editing it.
- Read threat model reports and developer briefs.
- Follow every threat from open to verified.
- Check who decided what, and when, in the audit trail.
Workspace owner
Run SecureSprints for your organisation.
- Invite people and give them roles.
- Set workspace defaults and Checkpoints notifications, in the app or in Teams and Slack.
- Review Activity: every transaction and its cost, in one tamper-evident view.
From model to merged code
What a SecureSprinted project hands your team
Threat inventory
Every approved threat and its tasks, for every project, with owner, status and history.
PR check
Each pull request is compared with the open threats it touches: inform, warn or block, by your policy.
Threat report and developer brief
The report is for reviewers and auditors. The brief turns the model into tasks a team, or its coding agent, can pick up.
Walkthrough · 2:20
From Jira story to verified fix, in under three minutes.
Finding 3: settlement webhooks accepted without a signature
A project profile, confirmed by people
Every story triaged before it's modeled
Personal and secret data redacted before any AI sees it
One stage at a time, each confirmed
- 0Triage
- 1Goals
- 2Scope
- 3Flow
- 4Threats
- 5Weak
- 6Attack
- 7Risk
A second AI challenges the first
Approved, then exported
The team builds from the inventory
Nothing is verified by its author
Model your first story this sprint
Most security problems are found after the code ships. By then, fixing the design means rework.
Hosting
SecureSprints cloud, or on-premises
Cloud · all plans
Live at yourcompany.securesprints.ai within one business day
We run it, update it and back it up. Pick the region your data lives in. Personal and secret data is redacted before any AI sees it.
On-premises · enterprise
Deployed on-premises, by arrangement
For enterprise customers who need SecureSprints in their own environment. We agree the deployment with you. Write to hello@securesprints.ai.
Plans · USD
One price per plan. Unlimited members.
In plain words
What is SecureSprints?
SecureSprints is AI threat modeling for every Jira story: grounded in published standards, decided by people, and verified in CI before a fix counts as done.
It takes each story through triage and the seven stages of PASTA, a published threat modeling method. AI drafts each stage and a separate AI reviewer challenges it. A named person confirms every stage, and an approver signs off the model before anyone writes code. Approved threats become security acceptance tests in a threat inventory. Developers, their coding agents and CI work through it until each task is verified, and the PR check keeps watching the code after that. SecureSprints reads Jira and never writes to it.
Questions
Asked before buying
What does SecureSprints do?
It threat-models each Jira story before it is built. AI drafts triage and seven modeling stages, a separate AI reviewer challenges them, and named people confirm each stage and approve the model. Approved threats become security tests in a threat inventory that your team, its coding agents and CI work through until each fix is verified.
What does "13.6 trillion paths" mean?
It is how many distinct routes a story can take through the SecureSprints method, from how it enters, through every design check, to every review and approval gate. Each story takes the one path it needs, and every part of its design is checked against it. How we count
When does the threat model happen?
Before the build, usually at sprint planning. A story is ready for build once its model is approved. The security tests and the developer brief are in your team's hands before anyone writes code. Pentests and scanners still run later.
What does the AI do, and what does it never do?
It drafts the project profile and each stage, reviews the drafts independently, imagines misuse cases, suggests fixes and maps threats to code. It never confirms a stage, approves a model, marks a task verified or writes to Jira. Those are always a person's decisions, or CI's.
How do you stop the AI making things up?
Every reference must come from a built-in, version-pinned library of published standards. References from an AI's memory are refused, even correct ones. Each finding quotes the story or is marked as an inference. A separate reviewer can block confirmation, and every action is recorded in a hash-chained audit log.
Is SecureSprints a threat modeling tool?
Yes. It follows PASTA, a published seven-stage method, and checks designs against STRIDE, LINDDUN, the OWASP Top 10 lists and MITRE CWE, CAPEC, ATT&CK and ATLAS. You don't draw diagrams from scratch or run workshops: you confirm what the AI drafts, one story at a time.
Does SecureSprints write to Jira?
No. It reads Jira and never writes to it. Developers work from the threat inventory, the developer brief or their coding agent. Personal and secret data is redacted before any AI sees a story.
Where is my data stored, and is it used to train models?
Cloud workspaces stay in the region you choose. For on-premises deployments, where data is kept is agreed with you. Our full statement on data use is on the Security page.
Can we run SecureSprints on-premises?
SecureSprints runs as a cloud service. Enterprise customers can have it deployed on-premises by arrangement. Write to hello@securesprints.ai, or read more.
Can we cancel or change plans at any time?
Yes. Change or cancel from billing settings. When you cancel, you keep access until the end of the paid period, and you can export your data for 30 days after.
Sprint 43 planning starts Monday
SecureSprint your next release.
Threat modeling for every story, not once a year
From Jira story to verified fix
Follow one SecureSprinted story from triage to a fix that CI has verified. AI drafts each step, a named person decides at every one, and every finding traces to a published standard. Every story in every team takes the same governed path, so security review keeps pace with your backlog instead of your headcount. Swipe the stage or use the arrows to step through it.
How you SecureSprint · eight steps
Who acts, what the AI does, and what you see
Steps one to six finish before anyone writes code. Steps seven and eight follow the code until every fix is verified, and keep watching after release.
01Set up the project
A project profile, confirmed by people
Upload a short intake document covering business goals, systems, data and users, or build the profile by conversation. A person confirms the draft. Any later change to a confirmed profile needs a second person (four eyes). You can also connect the project's code repository: DevOps or a lead proposes it, and an Approver confirms.
02Pick stories
Start from the Jira stories in the sprint
Find stories by search, saved presets or sprint, and start one or a batch. SecureSprints reads Jira and never writes to it. Personal and secret data is redacted before any AI sees it.
03Triage
Stage 0: how deep, and what kind of change
The AI proposes a depth (full, delta, checklist or not relevant) and the kinds of change involved, such as API, mobile, AI or LLM, cloud and CI/CD. SecureSprints checks that choice against the story itself. If the story mentions an API or an AI feature the triage left out, the choice is challenged and must be fixed or explained.
04Model
Seven stages, one at a time
The model follows PASTA, a published threat modeling method. SecureSprints drafts one stage, then stops for a person to confirm it, answer an open question, or send it back with a change request. From stage four, an independent reviewer challenges the work before anyone can confirm.
05Autopilot · optional
Skip the routine confirmations, never the real decisions
A modeller can let SecureSprints confirm the low-risk stages for them. Every real decision still stops for a person. Autopilot actions are recorded under the modeller's name and marked as autopilot.
06Approve and export
A person signs off the exact content
An Approver reads the assembled model and approves it, bound to the exact content, or sends it back to any stage. The export is a threat model report (HTML or Markdown) and a developer brief: the security work as tasks a team or a coding agent can pick up. What the story taught joins the project baseline, so the next story starts from it.
07Fix and verify
The threat inventory, worked to verified
Every approved threat lands in the project's threat inventory with its tasks: the security acceptance tests. Tasks move from Open to Planned, In progress and Implemented, with evidence, then to Verified, or back to Reopened. Verification comes from CI test results or a lead who is not the implementer. Nobody verifies their own work. An Approver can accept a risk, with a reason, an owner and a review date.
08Keep modeling
The model follows the code
The PR check compares each pull request with the open threats it touches, then informs, warns or blocks according to your policy. A verified control whose code is removed is reopened. A story whose threats are touched is suggested for a delta re-model.
Step four, in full
The seven modeling stages
Each stage answers one question. A person confirms each answer before the next stage starts.
- 0Triage
- 1Objectives
- 2Scope
- 3Decomposition
- 4Threats
- 5Weaknesses
- 6Attacks
- 7Risk
Stage states: done, current, waiting for you, or blocked.
| Stage | Question it answers | What you see |
|---|---|---|
| 1 · Business objectives | What matters to the business here? | Objectives, and why the story matters |
| 2 · Technical scope | Which components, services and AI parts are involved? | Components, with flags such as "uses AI" or "acts autonomously" |
| 3 · Decomposition | How does data move, and where are the trust boundaries? | Data-flow diagram, assets, entry points, open questions |
| 4 · Threat analysis | What can go wrong, element by element? | Findings with evidence, a completeness matrix, rule-proposed threats and how each was answered |
| 5 · Weakness analysis | Which known weaknesses are these? | Each finding tied to CWE and the OWASP lists |
| 6 · Attack modeling | How would an attacker do it? | CAPEC, ATT&CK and ATLAS patterns, with attack trees for serious threats |
| 7 · Risk | How likely, how bad, and how do we prove it's fixed? | Severity, scored factors, and security acceptance tests in Given / When / Then |
Independent review · stages 4 to 7
A second AI checks the first
From stage four, an independent reviewer works apart from the AI that drafted the stage and challenges it before a person can confirm. It can only report findings. It never edits the model.
A wrong threat category, a wrong standard mapping or a gap in coverage is a blocking finding. Confirmation stays blocked until the work is fixed and reviewed again. A person can override a blocking finding with a written reason, and the override is recorded.
Autopilot · optional
What autopilot may confirm, and where it always stops
| Autopilot may confirm | Always stops for a person |
|---|---|
| Business objectives | Triage, scope and decomposition |
| Weakness analysis | Threat analysis and risk |
| Attack modeling | Any warning, question or blocking finding |
| Approval, which is always a person's |
That's how you SecureSprints
13.6 trillion ways a threat model can unfold
Each story takes the one path it needs, and every part of its design is checked against it. No workshop, checklist or spreadsheet can hold that many routes, so SecureSprints checks completeness mechanically, on every story, in every team. Only possible with AI.
How we count
- Entry
How a story enters
The kinds of change it combines (API, mobile, AI, cloud, CI/CD and more), the lens packs that apply, and the depth: full, delta or checklist.
- Design
What each part of the design is checked against
Every actor, data flow, data store, process and AI component is checked against the framework categories for its kind. AI and autonomous AI components get the most checks. A typical story has 60 to 160 checks, and each is answered by a finding or closed with a specific reason.
- Gates
How the work moves through the gates
Autopilot settings, independent review rounds on the reviewed stages, and the final approval or send-back to any stage.
With required packs only, about 294 billion paths. This counts routes through the method only. Each story's own components, flows and data multiply it again, which is why completeness is checked mechanically rather than left to memory.
Transcript
Every word of the walkthrough
The problem 0:00
Most security problems are found after the code ships. A pentest report arrives six weeks after release and names a flaw in the design: settlement webhooks are accepted without a signature, so a forged one can mark an unpaid invoice as paid. By then, fixing the design means two sprints of rework.
Set up the project 0:15
Upload a short intake document for project PAY: its goals, systems, data and users. SecureSprints drafts the project profile, and A. Rao, the security champion, confirms it. Any later change to the profile needs a second person to confirm it too. Jira is connected read-only. SecureSprints never writes to it.
Triage the sprint 0:30
Pick the Jira stories in Sprint 42. Each one is triaged as full, delta, checklist or not relevant, with the kinds of change it involves. PAY-142, pay an invoice by bank with settlement webhooks, is triaged as full: API, identity, a third-party bank and webhooks. A person confirms every triage.
Seven stages, confirmed 0:50
AI drafts each modeling stage, from business objectives through decomposition to threat analysis. It stops at every stage for a person to confirm, answer an open question or send it back. For PAY-142 the data flow crosses three trust boundaries: customer to bank, bank to payments API, and payments API out to the merchant's webhook. Threat analysis finds a forged settlement webhook that marks an unpaid invoice paid, a replayed webhook that settles twice, a consent redirect that hands the bank's code to an attacker, an invoice ID that can be swapped for another tenant's, bank account numbers in logs, and a consent page that can be framed. Each finding quotes the story or the profile and cites its weakness, such as CWE-345.
Independent review 1:05
From stage four, a separate AI reviewer challenges the work. Here it raises two blocking findings: the invoice-ID threat cites CWE-284, which is too broad, and no threat covers the merchant's webhook URL. A. Rao corrects the mapping to CWE-639 and adds a server-side request forgery threat. The reviewer runs again and comes back clean. Only then can the stage be confirmed.
Approve and export 1:20
Weakness analysis ties each threat to CWE, and attack modeling maps the paths to CAPEC and MITRE ATT&CK. R. Iyer, the security lead, reads the assembled model and approves it: seven threats, six security acceptance tests written as Given, When, Then, and one accepted risk, the framing of the bank's own page, with an owner and a review date. It exports as a threat model report and a developer brief. All of this happens before anyone writes code.
Build from the inventory 1:45
The approved threats land in the threat inventory. M. Okafor and their coding agent claim the tasks and read the brief over a secure connection. When the pull request opens, the PR check compares it with the open threats it touches.
Verified by CI 2:00
CI test results verify each task. In build 1186 four pass, but the replay test fails: the same event ID settled the invoice twice, so that task reopens. After the fix, build 1187 passes all five automated tests. The log-masking task is verified by R. Iyer, who did not implement it. Nobody verifies their own work.
Start 2:15
Start with one project from $99 a month. SecureSprints cloud; on-premises by arrangement. SecureSprint your next release.
Pricing · USD
One price per plan. No seat counting.
Every plan SecureSprints every Jira story: triage, seven confirmed stages, an independent review, the threat inventory, and the threat report and developer brief. Plans differ only by projects, automation, hosting and identity. Unlimited members on all of them, so the whole team works from one governed model.
Prices in USD. Pay in US dollars or Indian rupees, through Razorpay. Taxes are added where required. Need a purchase order, invoice or security review first? Talk to us.
Billing
Billing questions
Can I change plans later?
Yes. Upgrades apply straight away and are charged pro rata. Downgrades apply at the next billing date.
What happens to projects over the limit when I downgrade?
Extra projects become read-only. Their threat models and inventory are kept, nothing is deleted, and they become editable again if you upgrade.
Is there a limit on stories modeled?
Plans are priced by project, not by story or seat. Owner to confirm any fair-use limit on AI usage
What happens when I cancel?
You keep access until the end of the paid period. After that, your threat models, reports and inventory stay available for export for 30 days, then they are deleted. We email you before deletion.
Which payment methods do you accept?
Payment is handled by Razorpay, in US dollars or Indian rupees, whichever you choose. Card details never touch SecureSprints. Program customers can also pay by invoice on annual billing.
Do you send invoices and receipts?
Yes. Every payment produces a tax invoice with your company details, available in billing settings.
Paying with an Indian card?
Indian banks ask you to approve every recurring card payment above ₹15,000. On the Release and Program plans, annual billing or invoice payment avoids a monthly approval step.
Enterprise · by arrangement
On-premises, by arrangement.
SecureSprints runs as a cloud service. Enterprise customers can have it deployed on-premises by arrangement.
Contact
Ask about on-premises
Write to hello@securesprints.ai.
Tell us about your organisation and the environment you have in mind, and we'll come back to you. A person reads every message.
Trust center
AI drafts. People decide. Standards verify.
The controls behind every SecureSprinted model, and how we protect your stories, threat models and inventory. Items marked for confirmation will be completed by the SecureSprints team before launch.
- Jira
- Read, never written
- Before any AI
- Personal and secret data redacted
- Audit log
- Hash-chained, tamper-evident
- Hosting
- SecureSprints cloud; on-premises by arrangement
Grounded AI
Eight controls on every SecureSprinted model
The same controls apply to every story, in every team and project. AI drafts; named people decide; every reference is traceable.
- 1
Named human decisions
Every stage, approval and accepted risk is recorded against a named person.
- 2
Pinned standards library
Every reference comes from a built-in, version-pinned library of published standards. References from an AI's memory are refused, even correct ones.
- 3
Evidence on every finding
Each finding quotes the story or the project profile, or is marked as an inference.
- 4
Complete coverage
Every part of the design is checked against each relevant framework. "Not applicable" needs a specific reason. Threats proposed by built-in rules must each be answered.
- 5
Independent AI review
A reviewer working apart from the author can block confirmation until the work is fixed, or a person overrides it in writing.
- 6
Redaction before AI
Personal and secret data is removed before any AI sees it. Jira is read, never written.
- 7
Tamper-evident audit log
Every action is written to a hash-chained log, so edits after the fact are detectable.
- 8
Measured accuracy
Scored against a labelled set of reference designs. Changes to the AI or the rules can't lower the score unnoticed. Figures will be published once an independent expert has reviewed the reference set.
Where AI helps
What the AI does, and what it never does
| AI role | What it does | What it never does |
|---|---|---|
| Author | Drafts the project profile and each modeling stage | Confirm, approve, export, or write to Jira |
| Independent reviewer | Challenges each reviewed stage, separately from the author | Edit the model. It can only report findings. |
| Misuse-case analyst | Imagines how the feature could be abused or fail | Change any stage |
| Fix proposer | Suggests how to fix a task, and checks a change looks complete | Mark anything verified |
| Code mapper | Links threats to the places in the code they concern | Read secrets, or follow instructions found in code |
| Guide | Answers how-to questions from the user guide and the page you're on | Take actions on your behalf |
Certifications
- SOC 2 Type II
- Status to confirm
- ISO 27001
- Status to confirm
We show a badge only once a certificate is issued. We name OWASP, MITRE and other published standards for reference. SecureSprints is not certified or endorsed by OWASP or MITRE.
Data handling
- Regions
- Chosen at sign-up
- Encryption in transit
- TLS 1.2 or later
- Encryption at rest
- AES-256
- Backups
- Daily, encrypted, kept in the same region
- Deletion after cancel
- 30 days
Confirm with engineering
Customer data and AI models
- Personal and secret information in your stories and profile is redacted before any AI sees it.
- The AI drafts and reviews. It never confirms a stage, approves a model, exports, or writes to Jira.
- Every reference it cites is checked against the built-in standards library. Anything it can't ground is refused or marked as an inference.
- Customer data is not used to train models. Owner to confirm wording and provider terms
- The AI model provider is listed with the other subprocessors and in the data processing agreement.
Privacy by design
- Redaction of personal and secret data before any AI call.
- Jira is connected read-only. SecureSprints never writes to it.
- The code mapper never reads secrets and ignores instructions found in code.
- Every action, including autopilot confirmations and overrides, is written to a hash-chained audit log.
Access and identity
- Multi-factor sign-in on every plan.
- Single sign-on with SAML or OIDC, and SCIM provisioning, on the Program plan.
- Roles for Modellers, Approvers, Developers, Viewers and workspace admins, with read-only access for auditors.
- Four eyes: a change to a confirmed project profile needs a second person, and repository connections are confirmed by an Approver.
- Nobody verifies their own work. Verification comes from CI or a lead who is not the implementer.
- Administrators see every transaction and its cost in the Activity view.
How we build SecureSprints
We SecureSprint SecureSprints. Every story in our own sprints is threat-modeled and approved before build, and every task in our threat inventory is verified by CI. Our own threat reports are available to customers under NDA.
Penetration testing
- Frequency
- Yearly and after major releases
- Tester
- Independent third party
- Latest test
- Date to confirm
Summary letter available on request under NDA.
On-premises
SecureSprints runs as a cloud service. Enterprise customers can have it deployed on-premises by arrangement, and the security arrangements are agreed with you. Write to hello@securesprints.ai. About on-premises
Subprocessors Example rows
| Name | Purpose | Location |
|---|---|---|
| Cloud host | Hosting | Region you choose |
| AI model provider | Drafting and review, on redacted data | To confirm |
| Razorpay | Payments | India |
| Email provider | Account emails | To confirm |
We email workspace admins 30 days before adding a subprocessor.
Documents on request
- Security questionnaire
- CAIQ or SIG Lite To confirm
- Pentest summary
- Under NDA
- Data processing agreement
- Read the outline
- Our own threat reports
- Under NDA
Vulnerability disclosure
Report a security issue to hello@securesprints.ai. We reply within 2 business days and won't take legal action against good-faith research.
Also published at /.well-known/security.txt.
Frameworks
Where SecureSprints fits in your standards
Every SecureSprinted story leaves audit-ready evidence: findings traced to published standards, decisions traced to named people, fixes verified by CI. These mappings show which secure development practices that evidence supports, across every team and project. Using SecureSprints does not by itself make you certified or compliant.
Grounding
The standards every finding traces to
Every reference in a threat model comes from a built-in, version-pinned library of these published standards. A reference an AI recalls from memory is refused, even when it is correct.
- OWASP Top 10 (2025)
- OWASP Top 10 for LLM Applications (2025)
- OWASP Top 10 for Agentic Applications (2026)
- OWASP API Security Top 10
- OWASP ASVS 5.0
- OWASP MASVS
- OWASP CI/CD Top 10
- OWASP Kubernetes Top 10 (2025)
- OWASP Risk Rating
- MITRE CWE
- MITRE CAPEC
- MITRE ATT&CK
- MITRE ATLAS
- MITRE D3FEND
- STRIDE
- LINDDUN
- PASTA
Named for reference. SecureSprints is not certified or endorsed by OWASP or MITRE.
- NIST SP 800-218Secure Software Development Framework5 practices mapped
- OWASP SAMM 2Software Assurance Maturity Model4 practices mapped
- ISO/IEC 27001:2022Annex A secure development4 controls mapped
- AICPA SOC 2Trust Services Criteria4 criteria mapped
- EU 2024/2847Cyber Resilience Act4 requirements mapped
NIST SP 800-218 · Version 1.1
NIST Secure Software Development Framework
US federal guidance for secure software development, referenced by the CISA secure software attestation form.
OWASP SAMM · Version 2
OWASP Software Assurance Maturity Model
An open model for measuring and improving a software security program, business function by business function.
ISO/IEC 27001:2022 · Annex A
ISO 27001 secure development controls
The controls an auditor checks for secure engineering inside an ISO 27001 management system.
AICPA · Trust Services Criteria
SOC 2 change management and risk
The common criteria an auditor tests when your SOC 2 scope includes how software changes are designed, tested and approved.
Regulation (EU) 2024/2847
EU Cyber Resilience Act
Applies to products with digital elements sold in the EU. Reporting duties apply from 11 September 2026 and most other obligations from 11 December 2027.
Mappings reviewed 27 October 2026. Owner to have mappings reviewed by an auditor before launch
Glossary · 48 terms
Secure development, in plain words
Short definitions of the terms that come up in threat models, security reviews, audits and sprint planning.
A
- Abuse case
- A description of how someone could misuse a feature, written like a user story from the attacker's side. For example: as an attacker, I resend a captured settlement webhook so an invoice is credited twice. See also misuse case.
- Acceptance criteria, security
- Conditions a user story must meet to be secure. SecureSprints writes them as security acceptance tests in Given / When / Then form, so each one says how it will be proven.
- Attack surface
- Every place an attacker can send input to or read output from your system: pages, APIs, file uploads, webhooks, admin tools and AI features. Each new story can grow it.
- ASVS
- The OWASP Application Security Verification Standard. A catalogue of testable security requirements, grouped into three levels. Version 5.0 is part of the standards library SecureSprints references.
- Autopilot
- An optional SecureSprints setting that confirms only the low-risk modeling stages (business objectives, weaknesses and attack modeling) on the modeller's behalf. It always stops for a person at triage, scope, decomposition, threat analysis, risk, any warning or blocking finding, and approval. Its actions are recorded under the person's name and marked autopilot.
B
- Broken access control
- When users can act outside their permissions, such as reading another customer's records by changing an ID in a URL. It tops the OWASP Top 10 and usually starts as a design gap.
- Business logic flaw
- A weakness in how a feature's rules work, not in the code's syntax. Applying a discount twice or skipping a payment step are examples. Scanners rarely find them.
C
- CAPEC
- MITRE's Common Attack Pattern Enumeration and Classification. A catalogue of the ways attackers exploit weaknesses, used at the attack modeling stage to describe how a threat would be carried out.
- CWE
- MITRE's Common Weakness Enumeration. A numbered list of software and hardware weakness types, such as CWE-345, insufficient verification of data authenticity. SecureSprints ties each finding to its CWE entries at the weakness analysis stage.
D
- Data flow diagram
- A drawing of how data moves between users, services and stores, with trust boundaries marked. SecureSprints drafts one for each story at the decomposition stage for a person to confirm.
- Defense in depth
- Using several independent controls so that one failure does not expose the system. For example, validating input in the API and also restricting the database account.
- Delta re-model
- Modeling only what changed in a story against what the project already knows, instead of starting over. SecureSprints suggests one when a code change touches threats from an earlier model.
- Design flaw
- A security weakness built into how a feature is meant to work, as opposed to a coding mistake. Fixing one after release usually means rework, which is why SecureSprints models each story before it is built.
- Developer brief
- An export of an approved threat model as security tasks that a team or a coding agent can pick up, each with the test that proves it.
F
- Four-eyes confirmation
- A rule that a sensitive change needs a second person to confirm it. In SecureSprints, an update to a confirmed project profile, or a repository connection, needs a second person.
G
- Given / When / Then
- A plain format for a test: the starting situation, the action, and the expected result. For example: given a settlement webhook whose event ID was already processed, when it arrives again, then the invoice is not credited a second time.
I
- Independent reviewer
- In SecureSprints, a separate AI that works apart from the one drafting the model and challenges each stage from threat analysis onward. It can only report findings. A blocking finding, such as a wrong category or a coverage hole, stops confirmation until it is fixed or a person overrides it in writing.
L
- Least privilege
- Giving each user, service and key only the access it needs, and no more. SecureSprints follows it by reading Jira without writing to it.
- LINDDUN
- A privacy threat modeling method that sorts threats into linking, identifying, non-repudiation, detecting, data disclosure, unawareness and non-compliance. It complements STRIDE for features that handle personal data.
M
- Misuse case
- A way a feature could be abused or could fail in a harmful way. SecureSprints imagines misuse cases for each story so the model covers what users shouldn't do, not only what they should.
- MITRE ATLAS
- A knowledge base of real attack techniques against AI and machine-learning systems, such as prompt injection and model evasion. Used to model stories that add AI features.
- MITRE ATT&CK
- A knowledge base of attacker tactics and techniques observed in real intrusions. Used at the attack modeling stage alongside CAPEC.
O
- OWASP Top 10
- A widely used list of the ten most critical web application security risks, published by the OWASP Foundation. The 2025 edition sits alongside separate lists for APIs, LLM applications and agentic applications.
P
- PASTA
- Process for Attack Simulation and Threat Analysis. A published, risk-centric threat modeling method in seven stages: business objectives, technical scope, decomposition, threat analysis, weakness analysis, attack modeling, and risk. SecureSprints runs it one stage at a time, with a person confirming each.
- Penetration test
- An authorised attack on a running system by skilled testers, to find weaknesses a real attacker could exploit. It tests what has been built, usually close to or after release.
- PR check
- A SecureSprints check on each pull request against the open threats it touches. By policy it informs, warns or blocks. A verified control whose code is removed is reopened.
- Project baseline
- What earlier approved stories taught SecureSprints about a project. Each new story starts from it, so known components and threats aren't rediscovered every time.
- Project profile
- A short description of a project's business goals, systems, data and users. SecureSprints drafts it from an intake document or a conversation, a person confirms it, and later changes need a second person.
R
- Remediation verification
- Checking that a fix actually removed the risk. In SecureSprints a task is verified by CI test results or by a lead who isn't the implementer. Nobody verifies their own work.
- Residual risk
- The risk that remains after controls are in place. It should be known, small and owned by someone.
- Risk acceptance
- A recorded decision to live with a risk for now. In SecureSprints only an Approver can accept a risk, and it needs a reason, a named owner and a review date.
- Risk burndown
- A chart of open security risks across sprints. A healthy line falls toward zero. A flat or rising line shows where risk is building up.
S
- SAST
- Static application security testing. Tools that read source code to find insecure patterns without running it.
- DAST
- Dynamic application security testing. Tools that probe a running application from the outside, the way an attacker would.
- SCA
- Software composition analysis. Tools that list the open-source packages you use and flag known vulnerabilities and licence issues in them.
- Secure Definition of Done
- A team rule that a story is not done until its security work is finished. With SecureSprints, that means every task is verified or its risk is accepted by an Approver.
- Secure Definition of Ready
- A team rule that a story cannot enter the build until its security work is defined. With SecureSprints, the approval of the story's threat model is the security part of Definition of Ready.
- Secure SDLC
- A software development life cycle with security activities in every phase: requirements, design, build, test, release and operation.
- Security acceptance test
- A test, written in Given / When / Then form, that proves a threat has been dealt with. SecureSprints writes them at the risk stage, and they become the tasks in the threat inventory.
- Security champion
- A developer on a product team who takes on security as part of their role. Champions are often the modellers in SecureSprints.
- Security debt
- Known security weaknesses left unfixed, often for speed. Like technical debt, it grows harder to pay down the longer it stays.
- Shift left
- Moving security work earlier in delivery, toward planning and design, where problems cost less to fix.
- STRIDE
- A way to sort threats into six classes: spoofing, tampering, repudiation, information disclosure, denial of service and elevation of privilege. Created at Microsoft and widely taught.
T
- Threat inventory
- A project's list of every approved threat and its tasks, with owner and status: open, planned, in progress, implemented, verified or reopened. Developers, their coding agents and CI work through it.
- Threat modeling
- A structured look at a design to find how it could be attacked or misused, before it is built. Teams ask what they are building, what can go wrong, what they will do about it, and whether they did a good job. SecureSprints does it for every Jira story, so it happens every sprint instead of once a year.
- Triage
- The first step of a SecureSprints threat model, stage 0. It proposes how deep to go (full, delta, checklist or not relevant) and what kind of change the story is, such as an API, mobile or AI feature. A person confirms it.
- Trust boundary
- A line where data passes between parts of a system with different levels of trust, such as from the internet into your API. Most threats appear where data crosses one.
V
- VAPT
- Vulnerability assessment and penetration testing. A common term, especially in India and the Middle East, for a combined scan and manual test of a running system.
Compare · Reviewed 27 October 2026
Where SecureSprints fits, and where it doesn't
Most teams need more than one approach. These comparisons say plainly what each does better, and where teams that SecureSprint still run pentests and scanners.
| Approach | When it runs | What it finds best | Proves the fix holds |
|---|---|---|---|
| SecureSprints | On every story, before build | Design gaps, missing controls, logic flaws, risks in AI features | Yes, in CI |
| Pentest | Once or twice a year | Exploitable issues in the running system | At the retest |
| Scanners | Every build | Known patterns in code and packages | For that pattern |
| General AI assistant | When someone asks | A plausible list of threats, quickly | No |
| Spreadsheet reviews | When someone has time | Whatever the reviewer spots | No |
| Enterprise design review tools | Per application or release | Deep architecture risk at scale | Varies by tool |
SecureSprints and pentest-only programs
Where SecureSprints is stronger
- Approves the security tests for a story before the code exists.
- Runs on every story, every sprint, not once or twice a year.
- Verifies each fix in CI and reopens it if it breaks.
Where a pentest is stronger
- Finds exploitable issues in the running system.
- Chains small weaknesses the way a real attacker would.
- Gives customers independent third-party assurance.
Use both. A pentest checks what was built. SecureSprints makes sure the design it tests already had its threats modeled and its fixes verified.
SecureSprints and scanners only
Where SecureSprints is stronger
- Finds missing controls and business-logic gaps that no code pattern reveals.
- Sets the security tests before code is written.
- Watches pull requests against the threats they touch, not just known patterns.
Where scanners are stronger
- Find known vulnerability patterns across large codebases fast.
- Check dependencies and containers on every build.
Use both. Scanners check code patterns. SecureSprints checks the design, and your CI test results verify its tasks.
SecureSprints and asking a general AI assistant
Where SecureSprints is stronger
- Every reference comes from a version-pinned library of published standards. References from an AI's memory are refused, even correct ones.
- A separate reviewer challenges the work, and its blocking findings stop progress until fixed.
- Every stage, approval and accepted risk belongs to a named person, in a tamper-evident log.
- Approved threats become tasks in an inventory that CI verifies.
- Personal and secret data is redacted before any AI sees it.
Where a general assistant is stronger
- Free, or already paid for.
- Quick for brainstorming a single idea.
- No set-up.
Generating a threat list is cheap now. Grounding it, deciding on it and proving each fix holds is the work SecureSprints does.
SecureSprints and spreadsheet reviews
Where SecureSprints is stronger
- Every part of the design is checked against each relevant framework. "Not applicable" needs a specific reason.
- Fixes are verified, not just marked done.
- Every decision has a named person, and history is kept automatically.
Where spreadsheets are stronger
- Free and flexible.
- Fine for a single small project with one reviewer.
SecureSprints and enterprise design review tools
Where SecureSprints is stronger
- Works per Jira story, inside the sprint. The data-flow diagram is drafted for you to confirm.
- A threat inventory verified in CI, every sprint.
- From $99 a month, set up within one business day.
Where enterprise tools are stronger
- Detailed architecture diagrams and large threat libraries.
- Governance across hundreds of applications and business units.
- Established in regulated sectors, with long procurement records.
Pick by team size and pace. Teams that ship every two weeks and want threat modeling in the sprint start here. Central security teams modeling whole systems may need both.
Docs
Documentation
SecureSprints is AI threat modeling for every Jira story: grounded in published standards, decided by people, and verified in CI before a fix counts as done. These guides show modellers, approvers, developers and admins how to SecureSprint a project, from the first intake document to CI verification.
Get started · 20 minutes
Model your first story
- Request your workspace. Choose a plan, name your workspace and give the admin's details. We set it up within one business day, and the admin gets an email to set a password and turn on multi-factor sign-in.
- Set up the project. Upload a short intake document. SecureSprints drafts the project profile, and you confirm it.
- Connect Jira. SecureSprints asks for read access only.
- Start a story. Find a story in the sprint and start it. Triage proposes how deep to go, and you confirm.
- Work through the stages. At each stage, confirm, answer an open question, or send it back with a change request.
- Ask for approval. An Approver approves the model. Export the threat model report and the developer brief before anyone writes code.
SecureSprints never writes to Jira. Developers get their security tasks from the developer brief, the threat inventory or their coding agent.
Get started · once per project
Set up a project
A project profile tells SecureSprints what matters before it models any story. An owner or modeller creates it.
- Intake document
- A short description of business goals, systems, data and users. Upload it, or build the profile by conversation instead.
- Project profile
- Drafted by SecureSprints from the intake, then confirmed by a person. Any later change to a confirmed profile needs a second person to confirm it.
- Code repository
- Optional. A DevOps person or a lead proposes the connection, and an Approver confirms it. It is needed for the PR check and to link threats to code.
Get started
Connect Jira
SecureSprints reads stories from Jira and never writes to it. Personal and secret information is redacted from each story before any AI sees it.
| Board | Access requested | Status |
|---|---|---|
| Jira Cloud | Read issues in chosen projects | Live |
| Azure DevOps | Read work items | Planned |
| GitHub Issues | Read issues in chosen repositories | Planned |
| GitLab | Read issues in chosen projects | Planned |
Confirm integrations and scopes at launch
Model a story
Triage and the seven stages
Start one story or a batch. Each runs through triage, then the seven stages of PASTA, a published threat modeling method. SecureSprints stops for a person at every stage.
- Full
- A complete model, for new or high-risk work.
- Delta
- Only what changed, against what the project already knows.
- Checklist
- A shorter check for routine changes.
- Not relevant
- No model needed. Allowed only for low-risk kinds of change.
Triage also proposes what kind of change the story is, such as API, mobile, AI or LLM, cloud, or CI/CD. SecureSprints cross-checks the choice against the story. If the story mentions an API or an AI feature that triage left out, the choice must be fixed or explained.
| Stage | Question | What you see |
|---|---|---|
| 1 · Business objectives | What matters to the business here? | Objectives, and why the story is relevant |
| 2 · Technical scope | Which components, services and AI parts are involved? | Components, with flags such as "uses AI" or "acts autonomously" |
| 3 · Decomposition | How does data move, and where are the trust boundaries? | Data-flow diagram, assets, entry points, open questions |
| 4 · Threat analysis | What can go wrong, element by element? | Findings with evidence, a completeness matrix, and rule-proposed threats with how each was answered |
| 5 · Weakness analysis | Which known weaknesses are these? | Each finding tied to CWE and the OWASP lists |
| 6 · Attack modeling | How would an attacker do it? | CAPEC, ATT&CK and ATLAS patterns, and attack trees for serious threats |
| 7 · Risk | How likely, how bad, and how do we prove it's fixed? | Severity, scored factors, and security acceptance tests in Given / When / Then |
At each stage you can confirm it, answer an open question, or send it back with a change request.
Model a story
Independent review and blocking findings
From stage 4 onward, an independent reviewer challenges the work before you can confirm it. It is a separate AI that works apart from the one drafting the model, and it can only report findings. It never edits the model.
A blocking finding, such as a wrong threat category, a wrong standard mapping or a gap in coverage, stops confirmation until the stage is fixed and reviewed again. A person can override it with a written reason. The override is recorded.
- Verified
- A reference checked against SecureSprints' built-in library of published standards.
- Unlinked
- A finding without a reference. It needs a reason.
- AI-derived
- An inference, stated as one, rather than something quoted from the story or the profile.
- Invalid
- A reference that isn't in the library. It is refused, even if it is correct.
Model a story · optional
Autopilot
A modeller can let SecureSprints confirm the low-risk stages on their behalf: business objectives, weakness analysis and attack modeling.
- It always stops for a person at triage, technical scope, decomposition, threat analysis and risk.
- It stops at any warning, open question or blocking review finding.
- Approval is always a person's.
- Every autopilot action is recorded under your name and marked autopilot.
Model a story
Approve and export
An Approver reads the assembled model and approves it, or sends it back to any stage. The approval is bound to the exact content, so a later edit needs a new approval.
- Threat model report, in HTML or Markdown, for reviewers and auditors.
- Developer brief: the security work as tasks a team or a coding agent can pick up, each with its test.
What the story taught joins the project baseline, so the next story starts from it.
Build and verify
The threat inventory and task statuses
Every approved threat lands in the project's threat inventory with its tasks. Each task is one security acceptance test.
- Open
- Approved, not yet scheduled.
- Planned
- Scheduled into a sprint.
- In progress
- Claimed by a developer or their coding agent.
- Implemented
- Done, with evidence attached, waiting to be verified.
- Verified
- Confirmed by CI test results, or by a lead who isn't the implementer.
- Reopened
- A test failed, or the code behind a verified control was removed.
Nobody verifies their own work. An Approver can accept a risk, with a reason, an owner and a review date, or mark a threat not applicable.
Build and verify · API on request
Send CI test results
Post test results from your pipeline. SecureSprints matches each result to the task whose test it names, and verifies the task when it passes.
curl -X POST https://acme.securesprints.ai/api/v1/test-results \
-H "Authorization: Bearer $SECURESPRINTS_CI_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"commit": "9f2c4e1",
"build": "1187",
"test": "test_same_settlement_event_id_settles_once",
"result": "pass"
}'
The API is available to workspace admins on request: email hello@securesprints.ai. The request above is illustrative. CI tokens can only post test results. They can't read or change anything else.
Build and verify
PR check policies
With a repository connected, SecureSprints checks each pull request against the open threats it touches. Choose a policy per project.
- Inform
- A comment on the pull request lists the threats it touches.
- Warn
- The check is marked as a warning until the related tasks are addressed.
- Block
- The check fails until the related tasks are addressed, or an Approver accepts the risk.
If a pull request removes the code behind a verified control, the task reopens. A story whose threats are touched is suggested for a delta re-model.
Build and verify
Connect a coding agent
Developers can work through the threat inventory with their coding agent. The agent reads threats and developer briefs over a secure connection, set up from the project's Integrations page.
- It can claim a task and propose a fix.
- It can never mark a task verified. That comes from CI or a lead.
- Instructions found in code are never followed, and secrets are never read.
Confirm supported coding agents at launch
Administer · Program plan
Single sign-on and SCIM
Connect any SAML 2.0 or OpenID Connect identity provider, such as Microsoft Entra ID, Okta or Google Workspace. Turn on SCIM to create and remove members from your directory automatically.
- Open Settings, then Identity. Copy the sign-on URL and entity ID.
- Create the app in your identity provider. Paste the values and download the metadata.
- Upload the metadata. Test with one account before you enforce single sign-on for everyone.
Changelog
What changed
Release notes are posted here as SecureSprints changes.
- Launch
New
SecureSprints launches
AI threat modeling for every Jira story, ready before the build.
- Project setup from a short intake document, with the profile confirmed by a person.
- Triage and seven modeling stages for each Jira story, each confirmed by a person. SecureSprints reads Jira and never writes to it.
- An independent reviewer that challenges the work from stage four. Blocking findings stop confirmation until fixed.
- Optional autopilot for the low-risk stages, recorded under the modeller's name.
- Approval by a named Approver, with a threat model report and a developer brief to export.
- The threat inventory, with tasks verified by CI test results or by a lead who isn't the implementer.
- The PR check, with inform, warn or block policies per project.
About
Threat modeling for every story, not once a year.
We built SecureSprints so every team in an organisation can SecureSprint its work the same way: modeled before build, decided by named people, verified in CI.
We built SecureSprints because threat models were happening too late and too rarely, and because a fix marked done was too often not done at all.
SecureSprints is AI threat modeling for every Jira story: grounded in published standards, decided by people, and verified in CI before a fix counts as done.
AI drafts. People decide. Standards verify. AI drafts each stage; named people confirm, approve and accept risk. Every reference it cites must come from a version-pinned library of published standards, and a separate reviewer challenges its work before anyone confirms it.
How we run the company
- Prices are on the website. Anyone can start without a sales call.
- We read your Jira and never write to it.
- Personal and secret data is redacted before any AI sees it.
- We never ask customers for cloud keys.
- We publish accuracy figures only once an expert has reviewed the reference set they are measured against.
- We say what the product does today, not what it might do.
Company details
- Registered name
- Owner to add
- Registered office
- Owner to add
- Founded
- Owner to add
Contact
Talk to us
For purchase orders, invoices, security reviews, a walkthrough or anything else. A person reads every message.
- Sales, support, security reviews, on-premises, vulnerability reports and careers
- hello@securesprints.ai
Careers
No open roles yet
We'll list roles here when we're hiring. We expect to hire first for application security engineering, threat modeling research and developer experience.
How we hire
- A conversation. Thirty minutes about the work and what you want next.
- A paid exercise. A small, real task, scoped to a few hours.
- Meet the team. Talk to the people you'd work with.
Want to hear when we open a role? Write to hello@securesprints.ai.
Legal
Terms and policies
Outlines of each document, so a reviewer can see what it covers. Final text by counsel before launch
Draft outline
Terms of service
- Who the agreement is between, and how payments are taken through Razorpay.
- Plans, billing, renewals and cancellation.
- Your data stays yours. Our licence to process it only to run the service.
- AI drafts and reviews; your people make every decision. Threat models support, but don't replace, your own security judgement.
- Service availability and support by plan.
- Self-hosted instances: licence, updates and your responsibilities in your own account.
- Liability, warranties and governing law.
Draft outline
Privacy policy
- What we collect on this website and in the product.
- Why we collect it and the legal basis.
- How personal and secret data in stories is redacted before any AI model processes it.
- Who we share it with, listed by subprocessor, including AI model providers.
- Where it is stored and how long we keep it.
- Your rights under GDPR, the UK GDPR, India's DPDP Act and US state laws, and how to use them.
Draft outline
Data processing agreement
- Roles: you are the controller, we are the processor.
- Security measures, listed in an annex, including redaction and the tamper-evident audit log.
- Subprocessors and 30 days' notice of changes.
- International transfers and standard contractual clauses.
- Breach notification, audits and deletion at the end of service.
Draft outline
Acceptable use policy
- No testing of systems you don't own or have permission to test.
- No attempts to break tenant isolation, manipulate the AI, or overload the service.
- No payment card numbers or health records in stories, intake documents or test results. Redaction is a safeguard, not permission.
Status
All systems normal
This is where SecureSprints publishes its service status. When an incident affects your workspace, your workspace admins are emailed, and the notice is posted here until it is resolved.
- Incidents
- Emailed to workspace admins when one starts, with updates until it is resolved.
- Something not working?
- Email hello@securesprints.ai with your workspace name and what you see.
- Security issues
- Report them through vulnerability disclosure.
Sign in
Sign in to SecureSprints
SecureSprints runs at app.securesprints.ai. Sign in there with your work account.
Sign in at app.securesprints.ai
Your company's own workspace
If your company has its own workspace address, such as acme.securesprints.ai, enter it to go straight to that workspace.
Forgot your workspace address?
Sign in at app.securesprints.ai, or write to hello@securesprints.ai from your work email and we'll reply with your workspace addresses.
On-premises deployment? Use the address your administrator gave you. New here? Start a sprint.
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Start SecureSprinting
- Plan
- Workspace
- Admin
- Review
- Send
Choose your plan
Name your workspace
Who will be the admin?
When your workspace is set up, we send this person a link to set a password and turn on multi-factor sign-in. We never email passwords.
Review and request
Your email app opens with these details, addressed to hello@securesprints.ai. Nothing is charged today.
Payment is handled by Razorpay, in USD or INR, once your workspace is set up. Card details never touch SecureSprints.
Request ready to send
Your email app opened with the details. Send the email, and SecureSprints replies within one business day to set up your workspace and payment (Razorpay, USD or INR).
If nothing opened, write to hello@securesprints.ai with these details:
What happens next · your first SecureSprinted story
- Step 1Upload a short intake document about your goals, systems, data and users, or build it by conversation
- Step 2Confirm the project profile that SecureSprints drafts from it
- Step 3Connect Jira. SecureSprints reads your stories and never writes to Jira
- Step 4SecureSprint your first story: triage, then seven stages, each confirmed by you