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Infrastructure

Autonomous agents that find vulnerabilities and fix them

Deploy agents across your entire stack. They find vulnerabilities, adapt over time, and close the loop with automated remediation — code patches, tickets, and re-testing.

How MindFort works

01

Deploy

Launch a pen test, activate Red Team agents, or trigger from CI/CD. Agents deploy in minutes, operate your security tooling, and run continuously.

02

Learn

Agents red-team continuously — probing, adapting, and building context about your unique environment with every operation. They remember what worked and evolve their approach.

03

Remediate

Agents close the loop — patching code via GitHub PRs, filing tickets in Jira and Linear with automatic re-testing, and remediating cloud and infrastructure configs.

Two ways to deploy

Run point-in-time assessments or deploy agents that never stop. Most teams use both.

AI Pen Tests

Fully autonomous penetration tests that deliver a point-in-time assessment. Agents map your attack surface, chain exploits, and deliver compliant, exportable reports.

Schedule on demand, weekly, or monthly. Results in under an hour.

AI Red Team

Always-on adversarial agents that continuously probe your environment, try new attack methods, remember past attempts, and adapt over time. Scale up with more agents for broader coverage.

Persistent. Learns your defenses. Gets sharper every cycle.

Remediation that goes beyond code

Finding vulnerabilities is only half the problem. MindFort agents close the loop — remediating across code, cloud infrastructure, and network configurations. Detection without remediation is just noise.

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. When a fix is deployed, agents re-test to confirm the vulnerability is resolved.

Cloud config remediation

Coming Soon

Agents remediate misconfigured cloud infrastructure directly — patching IAM policies, security groups, and resource configs across AWS, Azure, and GCP.

Network & infrastructure

Coming Soon

Extend remediation to network-level configurations — firewall rules, routing policies, and access controls that agents discover and fix.

network remediation
$ mindfort remediate NET-0023
Scanning network configuration...
FW Rule: allow-all-outbound-443
Dest: 0.0.0.0/0:443 (any)
+ Dest: api.stripe.com, api.datadog.com:443
ACL Subnet: prod-private-subnet-a
Allow: all traffic (inbound)
+ Allow: TCP 443, 5432 from 10.0.0.0/16
Submitting for approval...
ACS change request #CR-48 created
$ _

Agentic Control System

In Development

As agents remediate beyond code — into cloud configs, network policies, and infrastructure — you need a system to track what they changed and why. The ACS is a git-like control plane for every change agents make across non-code surfaces.

Version control

Every agent-made change is versioned with full before/after state, so you always know what changed and can roll back.

Approval workflows

Route changes through your existing approval process. Agents propose, your team approves, agents apply.

Full audit trail

Complete history of every remediation action across every surface — who, what, when, and why. Built for compliance.

Driving down MTTR

Agents find and fix issues in minutes, not weeks. The ACS gives you the control to let them move fast without losing visibility.

Every security capability, one agent interface

Agents operate DAST, vulnerability management, SCA, and threat intelligence on your behalf. Each capability runs continuously as part of every agent operation — no separate tools to configure, maintain, or monitor.

Penetration testing

End-to-end pen tests against your live environment with compliant, exportable reports.

Dynamic application security

Agents perform deep DAST analysis natively — no separate scanner. Authenticated crawling, business logic testing, and API security in every run.

Vulnerability management

Findings are validated, deduplicated, risk-scored, and tracked over time. Agents triage so your team doesn't have to.

Software composition analysis

Agents identify vulnerable dependencies and open-source risks across your codebase as part of every operation.

Threat intelligence

Agents draw on real-time threat data to prioritize what matters — testing for actively exploited CVEs and emerging attack techniques.

Attack surface mapping

Continuous discovery and monitoring of every exposed asset across your organization — subdomains, APIs, cloud resources, and more.

Security that gets better the longer it runs

MindFort agents don't start from scratch every time. They accumulate knowledge about how your organization works — your tech stack, deployment cadence, configuration patterns, and defensive posture. Every cycle produces better results than the last.

Environment-aware testing

Agents map how your teams build, deploy, and configure systems — tailoring their testing and remediation to your specific stack and conventions.

Continuous context building

Every operation deepens an agent's understanding of your environment. Past findings, infrastructure changes, and deployment patterns all inform future runs.

Adaptive attack strategies

Agents remember what worked and what didn't. They evolve their approach based on your specific defenses, getting sharper with every cycle.

Efficient at scale

Self-learning means agents spend less time re-discovering what they already know — more targeted testing, faster remediation, better coverage across your entire stack.

MF-1

In Research

Our deep research investment into a purpose-built offensive security model. General-purpose models weren't built to chain exploits, navigate auth flows, or adapt attack strategies in real time. MF-1 is trained from the ground up on vulnerability research and real-world attack data — designed to bring best-in-class security capabilities at a fraction of the compute.

Purpose-built reasoning

Trained with reinforcement learning on offensive security environments — rewarded for finding real vulnerabilities, not generating text.

Efficiency at scale

Smaller, faster models that outperform general-purpose alternatives. Teams adopt within their budget and scale when they need to.

Privacy by default

All inference runs on our secure infrastructure. Your data is never used for training and never leaves your control.

Continuous improvement

As MF-1 advances through research, every agent gets smarter — better findings, faster remediation, deeper coverage.

Deploy your autonomous security team

MINDFORT