Autonomous agents that find vulnerabilities and fix them

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April 29, 2026

MindFort

Pentesting

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Autonomous agents that find vulnerabilities and fix them

Agent Automated Remediation Vulnerability Detection Adaptive Security Autonomous Agents Self Learning AgentsFree + from $199/mo

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Overview

MindFort is an AI-powered platform intended for penetration testing, vulnerability exploit validation, and automated remediation. Its core products involve autonomous agents capable of identifying vulnerabilities across a users operations then automatically applying code patches, creating tickets for issues and re-testing to ensure they have been addressed.

MindFort's services include AI Pentests and AI Red Team. AI Pentests deliver a point-in-time assessment by mapping your attack surface, chaining exploits, and delivering compliant, exportable reports.

AI Red Team continuously probes your environment, adapts to new attack methods, remembers past attempts, and scales up for broader coverage. The system works by deploying agents which learn about your specific context and adapt over time to the environment.

Remediation involves patching code through tools like GitHub PRs, filing tickets in Jira and Linear with automatic re-testing, and amending cloud and infrastructure configurations.

This software also takes charge of patching misconfigured cloud infrastructure and making corrections to network-level configurations. MindForts Agentic Control System tracks changes made by agents, versioning, approval workflows and maintains a complete audit log for compliance.

The platform utilizes a mix of dynamic application security analysis, vulnerability management, software composition analysis, and threat intelligence.

MindFort's unique self-learning method means agents evolve based on your defenses, get sharper with every cycle and become more efficient at scale. The agents accumulate knowledge about organizational tech stack, configuration patterns, and security posture, thereby enhancing their testing and remediation effectiveness over time.

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Initial release

May 20, 2025

Initial release of MindFort.

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Pros and Cons

Pros

Autonomous vulnerability identification

Automated code patches

Automatic ticket creation

Continuous vulnerability re-testing

Attack surface mapping

Exploit chaining

Compliant exportable reports

Adapts to new attack methods

Remembers past attack attempts

Scalable security coverage

Context-specific learning

GitHub PRs for patching

Jira, Linear ticket integration

Cloud infrastructure patching

Network configuration corrections

Agent-driven changes tracking

Versioning of changes

Approval workflows

Compliance-friendly audit logs

Combines dynamic application security analysis

In-built vulnerability management

Software composition analysis

Real-time threat intelligence

Self-learning security agents

Knowledge accumulation about tech stack

Adaptive testing efficiency

Remediation effectiveness over time

Persistent adversarial agents

CI/CD triggering

Assessment scheduling options

Software, cloud, network remediations

Direct cloud config remediation

Network & infrastructure remediation

Agent control with versioning

Real-time threat data utilization

Continuous asset discovery

Environment-aware testing

Adaptive attack strategies

Efficient scaling

Vulnerability research-based model

Real-world attack data training

Privacy-focused

Continuous model improvement

View 38 more pros

Cons

Needs specific system integrations

Potential compliance issues

Agentic control complexity

Adapts slow to environment

Dependent on continuous updates

Heavily reliant on agents

Lack of multi-language support

Could overwhelm existing workflows

Requires initial configuration

Lack of real-time support

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Q&A

What is MindFort used for?

MindFort is an AI-powered platform intended for penetration testing, vulnerability exploit validation and automated remediation. It can identify vulnerabilities across your operations and automatically apply code patches, create tickets for issues and re-test to ensure they have been addressed.

How do MindFort's autonomous agents identify vulnerabilities?

MindFort's autonomous agents identify vulnerabilities by probing your environment, adapting to new attack methods, remembering past attempts, and scaling up for broader coverage. They continually learn about your specific context and adapt over time to the environment.

What is MindFort's Automated Remediation?

MindFort's Automated Remediation involves patching code through tools like GitHub PRs, filing tickets in Jira and Linear with automatic re-testing, and making corrections to cloud and infrastructure configurations. It can also patch misconfigured cloud infrastructure and make corrections to network-level configurations.

How does MindFort apply patches through GitHub PRs?

MindFort applies patches through GitHub PRs in the remediation process. The agents generate validated patches and open PRs directly in the codebase. Each patch comes with a threat model that explains the vulnerability and how it was fixed.

What services are included in MindFort's AI Pentests?

In MindFort's AI Pentests, autonomous agents deliver a point-in-time assessment by mapping your attack surface, chaining exploits, and delivering compliant, exportable reports. This service can be scheduled on demand, weekly, or monthly.

Can you explain how MindFort's AI Red Team operates?

MindFort's AI Red Team operates on a continuous basis, probing your environment, trying new attack methods, remembering past attempts, and adapting over time. The Red Team agents scale up for broader coverage and become sharper with each cycle, learning from past attempts to be more effective in identifying vulnerabilities.

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What cloud infrastructures does MindFort patch?

MindFort can patch misconfigured cloud infrastructure directly, working with platforms such as AWS, Azure, and GCP. The remediation process includes patching IAM policies, security groups, and resource configurations.

How does MindFort make corrections to network-level configurations?

MindFort makes corrections to network-level configurations during the remediation process. The AI extends remediation to firewall rules, routing policies, and access controls that agents discover and fix.

What is MindFort's Agentic Control System?

MindFort's Agentic Control System (ACS) is a feature that tracks changes made by agents and manages versioning and approval workflows. The ACS also maintains a complete audit log for compliance and every change made by agents is versioned with full before/after state.

What advantage does MindFort's self-learning method bring?

MindFort's self-learning method allows the autonomous agents to evolve based on your defenses. By getting sharper with every cycle and learning about your organisational tech stack, configuration patterns, and security posture, the agents enhance their testing and remediation effectiveness over time.

How do MindFort's agents become more efficient at scale?

MindFort's agents become more efficient at scale through the process of self-learning. As they continue to learn and adapt based on specific defenses, they spend less time re-discovering known information. This results in more targeted testing, faster remediation, and better coverage across your entire stack.

How do MindFort agents accumulate knowledge about my tech stack?

MindFort agents accumulate knowledge about your tech stack through continuous probing, adapting and building context about your unique environment with every operation. They use this knowledge to tailor their testing and remediation efforts to your specific stack and conventions.

What is the core product of MindFort?

The core product of MindFort involves its autonomous agents capable of identifying vulnerabilities across a user's operations then automatically applying code patches, creating tickets for issues and re-testing to ensure they have been addressed.

What is the difference between MindFort's AI Pentest and AI Red Team?

AI Pentests service performs a point-in-time assessment. Agents map your attack surface and deliver compliant, exportable reports. On the other hand, AI Red Team is a continuous service where the agents are always on, probing your environment and adjusting their strategies based on their findings. They remember past attempts, and adapt over time for more extensive coverage.

What kind of security does MindFort dynamically analyze?

MindFort dynamically analyses security by utilizing a mix of dynamic application security analysis, vulnerability management, software composition analysis, and threat intelligence. This allows for continuous discovery and monitoring of exposed assets across your organization.

Does MindFort have integrations with Jira and Linear?

Yes, MindFort has integrations with Jira and Linear. 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.

In what ways does MindFort manage vulnerabilities?

MindFort manages vulnerabilities through dynamic application security analysis and vulnerability management. Findings are validated, deduplicated, risk-scored, and tracked over time. They also identify vulnerable dependencies and open-source risks.

Can MindFort adapt to my specific environment?

MindFort can adapt to your specific environment through a continuous learning process. The agents map how your teams build, deploy, and configure systems and tailor their testing and remediation to your specific stack and conventions.

Does MindFort provide an approval workflow for changes made?

Yes, MindFort does provide an approval workflow for changes made. This is managed through the Agentic Control System, where changes can be routed through your existing approval process. Agents propose, your team approves and agents apply.

How can MindFort enhance my security posture?

MindFort can enhance your security posture by continuously probing your environment and adapting to new attack methods. With every cycle, the agents get sharper and more efficient, and they accumulate knowledge about your tech stack, configuration patterns, and security posture, thereby enhancing their testing and remediation effectiveness over time.

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