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AI code security audit and remediation services

AI code security audit and remediation services

AI-generated web application review for security and code quality. Engineering-led validation, with remediation and hardening to get it ready for production.
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AI-generated code security challenges we solve

A pre-production manual review stage catches security and code quality weaknesses that automated scanners miss, then remediates the findings for production.
01
AI output reaches production without a security gate
A reasoning-based review checks AI-generated code for quality and security issues, then identifies and prioritizes validated findings for fixing before release
02
AI delivery volume outpaces internal capacity
Every AI-built codebase receives a dedicated assessment, with remediation when needed without stretching in-house teams
03
Limited AI code security expertise
Experienced application security engineers validate security-critical implementation and fix confirmed findings across any web stack
04
Security review missing from the delivery workflow
A structured engagement adds a validation stage to the delivery process before client handoff or production deployment
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AI code security audit services for web applications

Independent quality and security assessment of AI-generated and AI-assisted code, combined with the engineering expertise needed to remediate validated findings.

AI code security & quality review

Engineering-led assessment of AI-generated source code to identify implementation and security issues before deployment
  • Code quality & security review across any web stack
  • Security findings prioritized by severity/confidence
  • Overall application risk assessment within the reviewed scope
  • Prioritized remediation roadmap
  • Engineering-ready documentation

Security remediation & AI code hardening

Validated findings turned into targeted remediation and production hardening based on the review results
  • Secrets /sensitive data handling improvements
  • Authentication & authorization hardening
  • Injection & insecure implementation remediation
  • Framework security configuration review
  • Security-focused code hardening

Post-remediation validation

A post-remediation quality checkup confirming completed fixes and documenting the results
  • Confirmation of completed fixes
  • Clear before-and-after findings comparison
  • Remaining observations within the reviewed scope
  • Updated application security posture

Documentation & engineering handoff

Detailed technical documentation with findings, completed fixes, and remaining observations
  • Review and remediation summary
  • Engineering notes for future development
  • Outstanding observations within the reviewed scope
  • Maintenance recommendations for continued development
Need more than a security report?
Review, validate, and fix AI-generated code before launch.
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Focus areas of the AI code security review services

The review covers the implementation areas where AI-generated web applications are most likely to introduce production risk.
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Reviews how credentials, API keys, tokens, and other sensitive data are stored, accessed, and shared, including any data sent to third-party AI services
Checks login flows, permission boundaries, session handling, and access rules to confirm that users can only reach what they're supposed to
Traces how untrusted input moves through the application and flags patterns that could lead to injection attacks or unsafe database access
Checks whether built-in framework protections are properly used, or accidentally bypassed by custom code in ways that create risk
Reviews how the app generates and displays output, and identifies weaknesses that could expose users to cross-site scripting (XSS) attacks.
Analyzes app settings and error handling to confirm that security protections still hold up during failures or unexpected situations
Validates how third-party packages are used to catch risky implementation patterns. Scanning for known vulnerabilities (CVEs) in dependencies requires a separate audit
Assesses how AI integrations handle prompts, trust boundaries, and user input or sensitive data, following OWASP's security guidance for LLM applications

Why GetDevDone for AI code security audit services

When AI-generated code approaches production, the clients need more than a security review; they need the engineering expertise to fix what it finds.
Review, remediation & validation in one engagement
From independent assessment to completed fixes and post-remediation validation, the entire process stays within one structured engagement
Built for agency delivery
White-label execution integrates into existing agency workflows, allowing teams to expand application security capability without changing how they work with clients
Engineering judgment beyond automated scanning
Reasoning-based code review evaluates how the application actually behaves, uncovering implementation risks that automated scanners alone may not detect
See what's really inside your AI-generated code before your client does
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AI code security audit across your delivery workflow

A structured engagement takes AI-generated web code from initial assessment through remediation, validation, and technical handoff before client delivery or production release.
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Defines the review scope, codebase boundaries, and project objectives before the assessment begins.
Reviews AI-generated source code to identify implementation quality issues and security risks that require engineering judgment.
Organizes validated findings by severity, confidence, and business impact to guide remediation priorities.
Resolves approved findings and strengthens security-critical implementation while preserving existing application behavior.
Confirms completed fixes, documents what changed, and records any remaining observations within the reviewed scope.
Delivers the documentation and implementation guidance needed to support future development, ongoing maintenance, and a smooth transition to the agency or client team.

Our work in client stories

How we turn complexity into real-world solutions for our clients.
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B2B digital agency
Securing an AI-built customer portal before launch
An AI-generated customer portal required a pre-launch engineering review. GetDevDone identified security gaps in authorization, secret handling, and password reset logic, then resolved them before release.
Read full case
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Digital agency
AI-broken payments to revenue recovery
When AI-generated changes disrupted the client's live payment system, GetDevDone diagnosed the failure, rebuilt the payment architecture, and recovered revenue before returning the platform to production.
Read full case
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Full-service digital agency
AI website rescue and rebuild
After a thorough audit of a Lovable-generated website, the GetDevDone AI engineering team diagnosed production-critical issues and rebuilt the underlying codebase for a stable, secure launch.
Read full case

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Find the risks. Fix the quality.

One engineering engagement from AI code security review to remediation

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    Our insights

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    FAQs

    GetDevDone’s experience shows that AI code security audit services are the right fit when an AI-generated or AI-assisted web application is approaching client handoff, production deployment, investor due diligence, or enterprise review, and the agency needs an independent assessment of the application's security before release.
    A general AI code review may focus on maintainability, architecture, or coding quality. At GetDevDone, the AI code security audit focuses specifically on application security and code quality, reviewing how the code handles authentication, authorization, sensitive data, framework protections, and other security-critical implementation decisions.
    AI code security audit services with GetDevDone identify and remediate security risks and code quality gaps within an otherwise functional web application.

    AI build rescue & rebuild is intended for projects with broader engineering problems, such as unstable architecture, incomplete implementation, poor maintainability, or applications that require partial rebuilding before production.
    Yes. After the vibe coding security audit, security remediation is available after the review. The implementation scope is based on validated findings, allowing agencies to move directly from assessment to production AI code hardening services without coordinating a separate engineering partner.
    No. The AI-generated code security audit services are reasoning-based source-code reviews. It evaluates how the application has been implemented instead of attempting to exploit a running system. Runtime penetration testing is outside the scope of this engagement.
    No. The methodology focuses on reasoning over the application's source code to identify issues that require understanding how the software behaves. Automated scanners and linters are not the primary review mechanism.
    The AI-generated code security audit supports web-facing applications, including full-stack web applications, backend APIs, headless APIs, browser-based front ends, and single-page applications, regardless of programming language or framework.
    The security review is scoped according to the application's size, architecture, and agreed review boundaries. If AI code remediation is required, implementation is estimated from the validated findings produced during the review rather than through predefined packages.
    Timeline depends on codebase size, scope, access readiness, and whether it's review-only or includes hardening. Our AI-generated code security audit engagements are scoped at kickoff, so you get a firm timeline based on your actual codebase, not a generic estimate that doesn't hold up. Full AI code security review services engagements typically take longer than a single-app audit.
    The report isn't the finish line. GetDevDone scopes and implements fixes through our AI code hardening services, then runs a post-remediation re-review to confirm the fixes hold. Our AI-generated code security audit services are built to close the loop, so the clients are left with a report and a production-ready code the team can act on.