AI Code Health Check — Enterprise Singapore

Built with AI.
Is it Safe
to Ship? // Free scan. Results in 30 minutes.

Your enterprise team used Claude, Cursor, or ChatGPT to build internal tools, automate workflows, or prototype new systems. That code is running in production — or about to be. Get an objective Code Health Score before a security incident does it for you.

Free auto scan
Results in 30 min
A–F health score
Repo deleted after scan
No obligation
LLL // Code Health Scanner
Running scan…
D
Code Health Score
Needs Attention
enterprise-workflow-tool/
0
Critical
0
High
0
Medium
>[CRITICAL] SQL injection — /api/reports.js:87
>[CRITICAL] Auth bypass risk — /middleware/auth.js:23
>[HIGH] Hardcoded API key — /config/env.js:14
>[HIGH] No rate limiting on /api/upload
>[INFO] Scan complete. Repo will be deleted in 1h.
Scan your enterprise code — free →
Three enterprise-specific fears

Your team shipped AI-generated code.
These are the risks they don’t see.

AI tools like Claude, Cursor, and ChatGPT write functional code fast. But enterprise systems have security requirements, compliance obligations, and scale expectations that AI tools don’t automatically satisfy.

01
🔒
Security Risk
“The AI-built internal tool accesses employee data and finance systems. We have no idea if the auth layer is secure.”
→ What we find
AI-generated auth code frequently skips edge-case validation, introduces privilege escalation paths, and mishandles session tokens. In 60%+ of enterprise AI code we scan, we find at least one critical auth issue.
02
📊
Scale Risk
“The tool works fine for 10 users. We’re rolling it out to 300 staff next month. Will it hold?”
→ What we find
AI models optimise for “working code” not “scalable code.” N+1 query patterns, missing connection pooling, and unindexed database queries are the three most common issues that destroy performance at enterprise scale.
03
📋
Compliance Risk
“Our system handles personal data. We need to be confident it meets PDPA requirements before the board presentation.”
→ What we find
PDPA-relevant issues: unencrypted PII at rest, missing consent logging, no data retention enforcement. These are architecture decisions, not bugs — the AI didn’t know your compliance context when it wrote the code.
Four steps — 30 minutes

Free scan. Results in your inbox.

The entire process is automated. No sales call required. No waiting for a quote. Your Code Health Score arrives by email before you finish your next meeting.

// AI Rescue — Auto Scan Flow
Step 01
🔗

Submit Your Repo

5 fields, 30 seconds. GitHub URL, AI tool used, current status, production status, and email. That’s it.

Step 02
🤖

AI Scans Automatically

LLL’s AI engine runs security analysis, architecture review, and performance assessment. No human required at this stage.

Step 03
📧

Score Arrives by Email

Code Health Score A–F. Critical / High / Medium issue counts. Top concern identified. Next steps recommended. In 10–30 minutes.

Step 04
🚪

Repo Deleted. You Decide.

Your repository is deleted from our systems after scanning. Zero obligation to proceed. The score and findings are yours regardless.

Code Health Score

A–F. Simple.
Objective. Actionable.

Every enterprise codebase gets graded on security, architecture, and scalability. No vague “recommendations” — a letter grade you can present to your CTO or board.

A
Production-ready
B
Minor issues only
C
Improvements needed
D
Attention required
Most AI builds land here
E
High risk in prod
F
Do not deploy

Most enterprise AI-generated systems score D or E without independent review

What happens after your scan

Free entry. Fix only
what you need to fix.

The free scan tells you what’s wrong. Everything after that is your choice. You can stop after the free scan, get a detailed report, or fix the issues entirely. No obligation at any step.

$0
Auto Scan
AI-powered automated scan. Code Health Score A–F. Critical / High / Medium issue counts. Top concern identified. Results by email in 10–30 minutes. Repo deleted after scan.
Free — Start Here
$500
Diagnostic Report
Human engineer + AI deep analysis. Full vulnerability breakdown with attack scenarios. Architecture assessment. Fix plan with effort estimates. DIY guide included. Delivered in 6 hours.
$5K
Hotfix
Critical issues fixed only. Minimum viable secure state. 2 weeks. Your code, your repo — we fix, you own. Right for: “it works but has Critical vulnerabilities.”
$10K
Stabilize
Critical + High issues fixed. Test suite added (50%+ coverage). Stable production-ready state. 1 month. Right for: “rolling out to 300+ enterprise users.”
$15–20K
Rebuild
Architecture redesign. Scalable to 10,000+ users. Full migration plan. 1–2 months. Right for: “this needs to become a production enterprise system.”

Every step is optional. Stop at any point. All code and findings are yours at every stage.

Why not a traditional security audit?

Traditional audits take weeks
and cost $5K–$20K to start.

Enterprise security audits are designed for large, stable systems — not for AI-generated code that needs a quick health check before rollout. LLL AI Rescue is designed specifically for this gap.

Traditional approach
Enterprise Security Audit
$5K–$20K entry
Time to first result
1–4 weeks
Entry cost
$5,000–$20,000
AI-code specialised
No — generic
Fix plan included
Report only
Enterprise-appropriate
Yes, but heavyweight
▲ LLL AI Rescue
AI Code Health Check
$0 entry
Time to first result
10–30 minutes
Entry cost
Free
AI-code specialised
Yes — Claude / Cursor / GPT patterns
Fix plan included
Score + issues + fix roadmap
Enterprise-appropriate
Yes — PDPA, scale, auth focus
Why trust LLL’s scan

We build AI-powered SaaS.
We know what breaks.

LLL isn’t a security consultancy that learned about AI tools last year. We run production SaaS products built with AI — and we’ve catalogued every failure pattern that causes enterprise incidents.

🏗

We run Fortrain — AI security SaaS in production

Fortrain (AI-powered security training for enterprise) is built and operated by the same team. We identify AI-generated code failure patterns because we’ve encountered them in our own codebase first. This is operational knowledge, not theoretical.

Self-enforcing quality standard
🤖

AI-augmented diagnosis at 1/10th the cost

80% of the diagnostic work is automated by AI — which is how we can offer a free scan and a $500 detailed report while a traditional security audit starts at $5K. Lower cost does not mean lower quality. It means lower overhead.

80% AI-automated — 100% engineer-reviewed
🛡

Enterprise context built in — PDPA, auth, scale

Enterprise AI-generated code fails in specific, predictable patterns: auth shortcuts, missing rate limiting, unindexed queries, PDPA-relevant data handling gaps. Our scanner is tuned for exactly these enterprise failure modes — not generic open-source CVEs.

Enterprise-pattern scanner
🔒

Data deleted. NDA available. No risk.

Your repository is deleted from LLL systems after scanning. For enterprise teams with sensitive codebases: NDA available before any scan, read-only access only, and results shared only with you. If your IT policy requires it, we work within your governance requirements.

Repo deleted after scan
Start your free scan

Submit your repo.
Score in 30 min.

5 fields. 30 seconds to fill. Code Health Score A–F arrives by email in 10–30 minutes. Your repository is deleted after scanning. No sales call. No obligation.

Free — no credit card, no commitment
Results in 10–30 minutes by email
Repository deleted after scan
Code Health Score A–F
Critical / High / Medium issue breakdown
NDA available on request before scan
⚠ Enterprise note
If your codebase contains sensitive data or your IT policy restricts third-party code access, email us first and we’ll sign an NDA before you share the repository link.

// Scan My Code — Free

Results in 10–30 min · No sales call · Repo deleted after scan

// Scan submitted

Your Code Health Score will arrive by email in 10–30 minutes. Your repository will be deleted from our systems after scanning.

Results arrive by email. Repo deleted after scan. NDA available on request.
Questions

FAQ

LLL uses read-only repository access. Your code is cloned for analysis and deleted from our systems after the scan is complete. We never store, share, or use your code for any other purpose. For enterprise teams with additional governance requirements, we can sign an NDA before you share the repository link — email us first at the address in the scan results.
GitHub’s Dependabot and CodeQL scan for known CVEs in dependencies and common vulnerability patterns. LLL AI Rescue specifically looks for patterns that emerge from AI-generated code: auth shortcuts, missing rate limiting, PDPA-relevant data handling, architecture decisions that fail at enterprise scale. These are not CVE-database issues — they’re design patterns that AI tools introduce that require an engineer to identify.
The free Auto Scan delivers: Code Health Score (A–F), Critical / High / Medium issue counts, identification of the single most urgent issue, and a recommended next step. It does not include the full detailed breakdown, attack scenario descriptions, fix code, or the complete prioritised issue list — those are in the $500 Diagnostic Report. But the free score is enough to know whether action is needed and how urgent it is.
No. You can stop after the free scan — the score and findings are yours regardless. The $500 Diagnostic Report, Hotfix, Stabilize, and Rebuild services are all optional next steps. We earn continued engagement by demonstrating value in the free scan, not by locking you in. Many enterprise teams use the free scan as a recurring health check with no obligation to proceed to paid services.
Yes. LLL clones the repository for scanning and deletes it from our systems after the scan is complete (within 1 hour). We do not retain code, copy business logic, or reference your repository after the scan report is generated. If you require written confirmation of deletion or a formal NDA before proceeding, email us and we will accommodate your governance requirements before any code is shared.
Yes. LLL’s AI scanner is specifically tuned to the failure patterns that emerge from Claude, Cursor, ChatGPT, and GitHub Copilot codegen — because we use these tools ourselves to build Fortrain and our client products. Each AI tool has characteristic patterns: Claude tends toward over-abstraction, Cursor tends toward missing error boundaries, GPT tends toward simplified auth logic. We look for all of them.
The free scan gives you a grade, counts, and the top issue. The $500 Diagnostic Report gives you: detailed breakdown of every issue with attack scenarios (for Critical/High), complete architecture assessment, performance analysis, a prioritised fix list, fix code samples for Critical issues, a comparison of Hotfix / Stabilize / Rebuild options with estimated effort, and a DIY guide if you want to fix it yourself. Delivered in 6 hours by a senior LLL engineer augmented by AI analysis.

Your AI-built code.
Scanned. Graded.
In 30 minutes.

Free. No sales call. No commitment. Results by email in 10–30 minutes. Your repository deleted after scanning.

$0 entry · A–F health score · Repo deleted · Results in 30 min

Free auto scan
Results in 30 min
GMT+8 Singapore timezone
NDA available on request
No obligation ever