llms.txt snapshot

# MindFort

> MindFort deploys autonomous security agents that continuously pen test web apps, APIs, and infrastructure, prove every finding with a working exploit, and open a validated patch, completely unattended.

- Agents run continuously on a cadence you set, at any scale, probing targets like an attacker would, rather than point-in-time scanning.
- Each finding is validated to cut false positives, and ships with a contextual patch and a threat model explaining the fix.
- Assessment modes trade speed for depth: Balanced (200 credits, ~4 hrs, frequent/daily use), Deep (400 credits, ~6 hrs, weekly/bi-weekly), and Ultra (800 credits, ~8 hrs, pre-release and release gates). Task agents (1 credit) handle smaller, directed work like validating findings or triaging bug bounty reports, drawing from the same credit pool.
- Remediation spans code (PRs in GitHub), cloud config (AWS/Azure/GCP IAM, security groups), and issue tracking (Jira, Linear).
- For full technical and API documentation, see the separate docs site and its own llms.txt.

## Core pages

- [Home](https://www.mindfort.ai/): Overview of the platform, continuous AI pen testing, exploit validation, and automated remediation.
- [Product](https://www.mindfort.ai/product): How agents detect, validate, and remediate across code, cloud infrastructure, and network configurations.
- [About](https://www.mindfort.ai/about): Company mission, the case for autonomous security, and the founding team.
- [Support](https://www.mindfort.ai/support): Contact, demo booking, and answers to common product, pricing, and technical questions.

## Product areas

- [AppSec](https://www.mindfort.ai/appsec): AI agents test the apps you ship on every push, finding exploitable flaws in your code and running app, then opening the pull request that fixes them.
- [OffSec](https://www.mindfort.ai/offsec): Autonomous offensive security across external and internal surfaces. Agents attack your live environment around the clock, proving each finding with an exploit.
- [Vulnerability Management](https://www.mindfort.ai/vulnerability-management): Agents confirm each finding with a working exploit, rank it by what an attacker could reach, then drive it to a fix.

## Use cases

- [Continuous Pen Testing](https://www.mindfort.ai/use-cases/continuous-pentesting): AI agents pen test live apps and APIs around the clock, confirming real exploits before attackers do.
- [Security Code Review](https://www.mindfort.ai/use-cases/code-analysis): Static and dynamic analysis to find exploitable flaws across source, dependencies, and the running app.
- [Business Logic Testing](https://www.mindfort.ai/use-cases/business-logic-testing): Agents chain legitimate app features into real abuse, like price manipulation, checkout bypass, and privilege escalation, that scanners can't find.
- [Attack Surface Management](https://www.mindfort.ai/use-cases/surface-management): Agents discover the domains, APIs, and forgotten environments you expose, then test them continuously as your surface changes.
- [Vulnerability Triage](https://www.mindfort.ai/use-cases/triaging): Agents validate, deduplicate, and risk-score every finding so teams only see what's real and what matters.
- [Remediation](https://www.mindfort.ai/use-cases/remediation): Agents generate, test, and open pull requests for confirmed vulnerabilities to speed up MTTR.
- [Security Reporting](https://www.mindfort.ai/use-cases/reporting): Pen test reports and audit evidence generated as agents work, exportable for SOC 2, ISO 27001, and customer security reviews.
- [Custom Security Tasks](https://www.mindfort.ai/use-cases/custom-tasks): Describe a security task in plain language and agents execute it: your playbooks, checks, and one-off investigations, on demand or on a schedule.
- [Agent Context](https://www.mindfort.ai/use-cases/context): Upload architecture docs, policies, and accepted risks, and agents apply them on the next run to cut findings you already knew about.
- [Coverage](https://www.mindfort.ai/use-cases/coverage): Agents track a security hypothesis for every part of your attack surface and re-test it each assessment, so you can prove what's been tested.

## Documentation

- [Docs home](https://docs.mindfort.ai): Setup, onboarding, assessments, findings, reporting, and integrations.
- [Docs index (llms.txt)](https://docs.mindfort.ai/llms.txt): Machine-readable index of all documentation, API reference, and MCP guides.
- [Quick Start](https://docs.mindfort.ai/quickstart): From account creation to your first completed assessment.
- [API Introduction](https://docs.mindfort.ai/api-reference/introduction): Programmatically trigger assessments, tasks, and findings via REST.
- [MCP Server](https://docs.mindfort.ai/guides/mcp): Connect Cursor, Claude Code, or Codex to MindFort findings.

## Optional

- [Y Combinator profile](https://www.ycombinator.com/companies/mindfort): Company background, team, and hiring (YC X25).