The Autonomous
AI Red Team.
Private AI models that autonomously discover, validate, and report real-world security weaknesses — continuously.
From reconnaissance to validation. Autonomous.
A single continuous cycle. Each stage feeds the next — and every result sharpens the next operation.
Observe
Map infrastructure, applications, APIs, services, and attack surfaces.
Reason
Private security models analyze vulnerabilities, configurations, relationships, and potential attack paths.
Plan
AI agents construct controlled testing strategies within scope.
Execute
Authorized security actions run inside predefined scope and policy boundaries.
Validate
Determine whether a weakness is theoretical or practically exploitable.
Learn
Results feed back into the agent's reasoning context.
Report
Generate evidence-backed findings, attack paths, severity, and remediation.
Watch the AI think like an attacker.
One autonomous system. Multiple offensive capabilities.
Private Security Models
Security-focused models deployed inside controlled private infrastructure. Data and security context remain within your environment.
Autonomous Pentesting
AI agents continuously explore authorized systems and reason about potential security weaknesses.
Vulnerability Research
Analyze applications, code, dependencies, configurations, and system relationships to identify vulnerabilities.
Exploit Validation
Safely determine whether identified vulnerabilities represent practically exploitable risk inside controlled environments.
Attack Path Discovery
Understand how multiple small weaknesses could combine into a larger security compromise.
Continuous Red Teaming
Move from annual penetration tests toward continuous adversarial security validation.
Security testing shouldn't happen once a year.
- Manual
- Periodic
- Tool-driven
- Limited testing window
- Static report
- Point-in-time assessment
- Autonomous
- Continuous
- Reasoning-driven
- Persistent validation
- Live attack graph
- Continuous security intelligence
A red team made of machines.
Specialized AI agents collaborate under a shared security model — with intelligence on top and strict operational control underneath.
Recon Agent
Discovers assets and attack surfaces.
Analysis Agent
Understands applications, services, and security boundaries.
Attack Path Agent
Constructs possible compromise paths.
Validation Agent
Performs controlled verification.
Research Agent
Analyzes vulnerabilities and technical context.
Report Agent
Transforms findings into actionable intelligence.
Finding a vulnerability isn't enough.
Can it actually be exploited?
Traditional scanners generate thousands of alerts. RecodeX.red focuses on validation — AI agents analyze whether weaknesses form meaningful attack paths and perform controlled verification inside authorized environments.
Every weakness, mapped to real impact.
Autonomous. Not uncontrolled.
Autonomous security agents operate inside strict policy boundaries — every action passes through defined control.
Scope Control
Agents can interact only with explicitly authorized assets.
Action Policies
Security teams define permitted and prohibited operations.
Sandboxed Execution
High-risk validation occurs inside isolated execution environments.
Human Oversight
Sensitive actions can require explicit human approval.
Every action scoped. Every decision logged. Every operation auditable.
Your infrastructure. Your models. Your data.
Security telemetry and proprietary infrastructure information never need to leave your controlled environment. Deploy RecodeX.red where your security posture demands.
No security data leaves the perimeter
RecodeX.red Research
Researching autonomous security agents, vulnerability intelligence, adversarial reasoning, and AI-native offensive security.
Built for systems that cannot afford to be wrong.
Your next red team
may not be human.
Deploy autonomous AI security agents against your own infrastructure before real attackers do.