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
Two Ways to Deploy
Run point-in-time assessments or deploy agents that never stop. Most teams use both.
AI Pentests
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
Agents remediate misconfigured cloud infrastructure directly — patching IAM policies, security groups, and resource configs across AWS, Azure, and GCP.
Network & infrastructure
Extend remediation to network-level configurations — firewall rules, routing policies, and access controls that agents discover and fix.
Agentic Control System
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 pentests 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
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.