KrishaLabs
KrishaStudio
KrishaStore
AI-Generated Code Fails Security Tests More Often Than You Think
AI coding tools are fast, but they learned from the open web, shortcuts, outdated patterns, and vulnerabilities included. Independent research has found that a large share of AI-generated code contains security flaws from the OWASP Top 10: SQL injection, cross-site scripting, exposed secrets, and weak authentication. The code often runs fine in a demo and fails the moment real users and real data arrive.
Worse, AI-generated code creates a false sense of security. It looks polished, it passes a quick test, and teams ship it assuming it is sound. The flaws surface later, in production, where they are expensive and dangerous. An audit before you ship is far cheaper than an incident after.
AI Code Security Challenges We Solve
A pre-production review catches the security and quality weaknesses that automated scanners miss, then fixes them before release.
- AI code reaches production with no security gate We add a proper review stage that checks AI-generated code for security and quality issues and prioritizes what to fix before launch.
- AI output is arriving faster than your team can review it Every AI-built codebase gets a dedicated assessment and remediation, without stretching your in-house team.
- Limited in-house AI-code security expertise Experienced engineers validate the security-critical parts and fix confirmed issues across any web stack.
- Security review is missing from your delivery workflow We add a validation stage before client handoff or production, so nothing ships unchecked.
Our AI Code Security Audit & Remediation Services
An independent security and quality assessment of AI-generated code, plus the engineering to fix what it finds, in one engagement.
-
An engineering-led review of your AI-generated code to find security and implementation issues before deployment.
- Security and quality review across any web stack
- Findings prioritized by severity and confidence
- Overall risk assessment for the reviewed scope
- A prioritized remediation roadmap
-
We turn validated findings into fixes and production hardening.
- Secrets and sensitive-data handling fixed
- Authentication and authorization hardened
- Injection and insecure-implementation issues remediated
- Framework security configuration corrected
-
A re-check that confirms the fixes hold.
- Confirmation of completed fixes
- A clear before-and-after comparison
- Any remaining observations, documented
-
Everything written up so your team can maintain it.
- Review and remediation summary
- Engineering notes for future development
- Maintenance recommendations
What the Review Covers
We focus on the areas where AI-generated web applications most often introduce production risk.
Secrets and sensitive data
How credentials, API keys, and tokens are stored and shared, including anything sent to third-party AI services.
Authentication and access control
Login flows, permission boundaries, and session handling, so users reach only what they should.
Injection and database security
How untrusted input moves through the app and any patterns that invite injection attacks.
Framework safeguards
Whether built-in framework protections are used properly, or accidentally bypassed by custom code.
Cross-site scripting and output handling
How output is generated and displayed, and any XSS exposure.
Security configuration and fail-safes
Whether protections hold up during errors and unexpected conditions.
Dependencies
How third-party packages are used, flagging risky patterns (deep CVE scanning is a separate audit).
AI and LLM integration risks
How AI features handle prompts, trust boundaries, and user or sensitive data, following OWASP’s LLM guidance.
Audit Plus Remediation, Not Just a Report
Some services hand you a list of problems and leave. We fix them, in one engagement.
We scope each review to your codebase and give you a firm price and timeline after a free initial look, rather than a generic package. If remediation is needed, we estimate it from the actual findings.
A Clear Findings Report
What is wrong, how serious it is, and what it means for you in plain language.
Prioritized Remediation
We fix the issues, starting with the ones that matter most.
Hardening for Production
Security controls, proper error handling, and the operational basics real software needs.
A Re-check
We validate the fixes, so you know the software is genuinely ready.
Real Projects, Confidential Clients
Every one of these builds looked finished. A proper review found what the demo hid, exposed credentials, injection risks, broken access, and we fixed it before real users ever hit the code. Client details are protected under NDA.
Securing an AI-built customer portal before launch
Securing an AI-Built Customer Portal Before Launch
An agency’s AI-generated customer portal was days from going live with no security review. We audited it and found gaps in authorization, secrets handling, and the password-reset flow, then remediated all three and hardened the app before release. The portal launched on schedule, secured.
Catching exposed credentials before investor due diligence
AI-assisted code facing investor due diligence, unreviewed.
Ahead of a funding round, a startup needed its AI-assisted codebase reviewed before technical due diligence. Our audit surfaced hard-coded API keys and a weak session-handling pattern that a reviewer would have flagged immediately. We fixed both and documented the remediation, so the code held up under scrutiny.
Injection risk found and fixed in an AI-generated storefront
Injection Risk Found and Fixed in an AI-Generated Storefront
An AI-built storefront looked finished but had never been security-reviewed. Our audit traced untrusted input through to an unsafe database query, an injection risk that would have exposed customer data in production. We remediated it, hardened input handling across the app, and re-validated the fixes.
Client Feedback
What Our Clients Say
KrishaWeb delivered a site that met all our expectations. Their friendly attitude and speedy work stood out, even while working remotely under tight deadlines. They accommodated our needs seamlessly, making the entire engagement a success.
The collaborative projects with Krishaweb Technologies have garnered several compliments and positive feedback. The team takes the initiative and manages projects well. Excellent work quality, timeliness, and reasonable price structures are key to their success.
KrishaWeb’s web development has positively impacted our business, saving us 4–5 hours of manual work every month. Their technical expertise and creativity result in exceptional outcomes. This trustworthy and hard-working team is a true asset to any project.
KrishaWeb has consistently delivered on their development tasks. The collaboration has always been characterized by their insanely quick turnaround time and incredible customer support. They listen to your challenges and needs and return with a viable solution, every time.
Why Choose KrishaWeb for AI Code Auditing
Plenty of tools can scan your code. Far fewer teams can tell you what the results actually mean and fix them. Here is what sets our review apart.
17 years of engineering
We know what secure, production-grade code looks like because we have been writing it since 2008.
We fix, not just flag
Audit and remediation together, so you end with safe software, not homework.
Reasoning-based review, not just scanners
We evaluate how the application actually behaves, catching implementation risks automated tools miss.
Built for agencies too
We can run this white-label inside your delivery workflow, so your team adds security capability without changing how you work, and your client sees only you.
You own everything
Clean, documented, hardened code with no lock-in.
A track record you can check
2,400+ projects, 4.9/5 on Clutch.
AI Code Security Audit FAQ
We hope these questions and answers help you find the best development partner for your business.
-
An AI code security audit is a professional review of AI-generated code to find security vulnerabilities and quality issues before the software reaches production. It checks for OWASP Top 10 flaws, risky dependencies, poor data handling, and the shortcuts AI tools commonly introduce, then remediates them.
-
Because a large share of AI-generated code contains security vulnerabilities. AI tools learned from public code that includes insecure patterns, and they reproduce them. The code often looks finished and passes a quick test while hiding flaws that surface in production. An audit catches them first.
-
We fix them. The audit produces a clear findings report, and then we remediate the issues, hardening the code for production and re-checking the fixes. You end with safe software, not a to-do list.
-
It depends on the size of the codebase, but a focused audit is usually days rather than weeks. We scope it after a quick look at your application and tell you the timeline up front.
-
Yes. We audit code generated by any AI tool, Cursor, Claude Code, Copilot, v0, Lovable, Bolt, Replit, and others, across web applications, CMS, front-end, and eCommerce.
-
We remediate and harden the code, validate the fixes, and hand over clean, documented, production-ready software that you own. If you want, we can also support it after launch.
-
No. This is a reasoning-based review of your source code, we evaluate how the application is built, rather than attacking a running system. Runtime penetration testing is a separate exercise. Our review finds the implementation and design flaws that a pen test on a live system often cannot see.
-
Yes. We work with agencies as a behind-the-scenes engineering partner, reviewing and hardening AI-generated code inside your workflow and under your brand. Your client sees your agency; we stay invisible, under NDA.
Not Sure If Your AI-Built Code Is Safe?
Send us the application. We will review it for security and quality, tell you honestly what we find, and give you a clear path to production-ready. A free initial review, no obligation, NDA before you share anything.
