Security swarms for edtech.
Agents sign in as students, parents, teachers, and district admins and try to cross every line between them. Each flaw comes back with the exploit that proves it and a pull request that fixes it.
- to verified findings
- <8 hrs
- of agents in parallel
- 1,000s
- false positives
- <1%
Why swarms for edtech.
Signs in as every role
Store a test account for each role, from student to district admin. Agents sign in with passwords, magic links, or MFA codes and test what each role can reach.
District-to-district testing
Dual credential mode uses accounts in two districts and tests whether one can reach the other's students, classes, and reports.
Scheduled and unattended
Schedule assessments before the summer release and before term starts. Findings arrive proven, and Patching opens a pull request for each one.
Evidence for procurement
Coverage shows which scenarios were tested and when. Reports and an attestation letter go straight into HECVAT and district reviews.
MindFort is built for your team.
Deploy swarms on your application
Agents attack learning platforms, rostering integrations, and parent and teacher apps in the live environment. Connect the repo and they trace each finding back to the code that caused it.
Results in hours
The first verified findings land the same day you start.
- to verified findings
- < 8 hrs
- to first deployment
- < 10 min
Traditional pentests: 2-6 weeks
Agent swarms that scale
Thousands of agents run in parallel, so adding targets doesn't mean adding headcount.
Full MCP & integrations
Start tests from CI/CD, push findings to your tracker, and drive agents through our API and MCP.
- GitHub
- Linear
- Jira
- Slack
Validated findings
Agents validate every finding with a working exploit.
- false positives
- < 1%
- with proof of exploit
- 100%
Every finding ships with steps to reproduce
Audit-ready from the first run
MindFort is SOC 2 Type II compliant, and every run produces evidence for your SOC 2 and ISO 27001 reviews.
Guardrails on every target
Include and exclude the domains, IPs, and routes agents can reach, set rate limits and rules for each target, and review every patch before it merges.
Validated patches
Every confirmed finding can end in a fix, whether it lives in code or cloud infrastructure, and a retest confirms the fix worked.
Code patching via GitHub
Agents generate validated patches and open PRs directly in your codebase, each with a threat model explaining the vulnerability and how it was fixed.
Jira & Linear integration
Findings are automatically filed as tickets in Jira or Linear with full context, so engineers get the evidence where they already work.
Cloud config remediation
Agents remediate misconfigured cloud infrastructure directly, patching IAM policies, security groups, and resource configs across AWS, Azure, and GCP.
Retesting
After a fix deploys, agents rerun the original attack against the live target, and can do it automatically when a patch merges. A finding resolves only when the retest confirms the fix.
Frequently asked questions.
Common questions about MindFort for education technology.
FERPA doesn't name specific tests. It requires schools to protect education records, and schools pass that duty to vendors through contracts and data privacy agreements. State laws such as New York's Education Law 2-d and California's SOPIPA add their own security requirements. A current pen test report is a direct way to show the work.
Yes. Run against a demo district or a staging tenant with test accounts, and add rules such as "Do not change real grades or message students." Scope, exclusions, and rate limits are set per target.
Run before the summer release and again before the term starts, then on a schedule. Agents work unattended, so a small team can test during the weeks when everyone is shipping.
Yes. Agents follow SSO redirect flows and complete authenticator app, SMS, and email MFA with the test accounts you provide.
Agents write a patch for each verified finding and open a pull request in GitHub with a threat model explaining the vulnerability and the fix. Findings can also be filed as tickets in Jira or Linear with full context. After the fix ships, agents rerun the original attack to confirm it no longer works.