At GX2, we closely follow how different organizations manage the security of their application code. In practice, the most sensitive challenge tends to be translating technical analyses into a clear picture of which vulnerabilities genuinely require immediate attention and which ones can be addressed within the normal flow of application development.

That reality is what led us to build the GX2 AI Code Security Diagnosis.

The service combines automated code analysis with specialized technical validation, enabling teams to identify vulnerabilities in the source code and organize those findings into an actionable plan for the engineering team. The diagnostic delivers context, prioritization, and practical remediation recommendations, giving leadership the information needed to make well-informed governance decisions.

Detection Methodology: Combining AI Analysis With Expert Validation

In most cases, security issues in applications develop from code patterns, vulnerable dependencies, or implementation decisions that remain in the system for extended periods without being detected.

By analyzing source code in a structured and systematic way, the GX2 AI Code Security Diagnosis identifies these patterns before they escalate into security incidents or exploitable failures in production.

Automated analysis flags potential vulnerabilities and insecure dependencies. The results are then reviewed by specialists to identify possible risk vectors and map those findings against widely recognized application security standards, such as the OWASP Top 10 recommendations.

The goal is to understand the context in which vulnerabilities appear and the potential impact on the application.

Below are the steps that make up the diagnostic process.

1. Secure Code Submission

The process begins with access to the application source code. The client may provide repository access or securely submit files for analysis.

We work with a wide range of programming languages and frameworks, allowing us to evaluate applications built on varied architectures without requiring any prior adjustments to the environment.

2. Automated Analysis With AI Agents

Once the code is received, AI agents perform a comprehensive scan in search of vulnerabilities, security flaws, sensitive data exposure, and implementation patterns that may pose risks to the application.

This step surfaces everything from critical issues to improvement opportunities related to secure development practices.

3. Specialized Technical Validation

The findings identified by the Agents go through a review conducted by GX2 security specialists.

This validation step eliminates false positives and allows vulnerabilities to be prioritized based on the application context, taking into account factors such as system criticality, data exposure, and potential business impact.

4. Detailed Technical Report

From this consolidated analysis, we produce a structured report presenting all identified vulnerabilities, classified by severity level.

Each item includes a description of the issue, its potential impact on the application, and the technical context your engineering team needs to fully understand the risk.

5. Action Plan and Technical Support

Beyond identifying vulnerabilities, the diagnostic includes practical remediation recommendations grounded in widely adopted industry references, such as the OWASP Top 10.

We also put together a prioritized action plan to guide the team through the implementation of fixes.

Technical Governance: Analysis at Scale With Human Oversight

In security diagnostics, AI expands analytical capacity, but it does not replace technical judgment.

That is why we operate under the Human-in-the-Loop model. AI agents perform a full scan of the codebase, identifying vulnerability patterns, insecure dependencies, and implementation practices that may pose risk to the application.

Final validation remains with GX2 specialists, who review the findings, eliminate false positives, and assess impact within the context of the architecture.

The Next Step for Your Operation

Having clear visibility into application code vulnerabilities allows security decisions to be made with greater precision and the right level of priority.

The GX2 AI Code Security Diagnosis was built to support that process, combining large-scale automated analysis with specialized technical validation and organizing findings into a clear remediation plan.

We are available to walk through the feasibility of this diagnostic against your current stack and discuss integration flows with your software development lifecycle. Reach out to schedule a technical conversation.