Building a ai wrapper / llm app with Django? Let us review it.
Expert code review for ai wrapper / llm apps built with Django. We fix Django-specific security gaps, optimize performance, and handle deployment. From $19.
Common Django issues we find
Real problems from Django codebases we've reviewed.
DEBUG=True in production
The most common Django security issue in AI-generated code. Debug mode exposes full stack traces, database queries, and installed apps to anyone who triggers an error.
Open Django admin panel
The admin panel is accessible at /admin/ without IP restriction, brute-force protection, or two-factor authentication — giving attackers a direct path to your database.
Missing permission classes on views
API views and endpoints without @login_required decorators or permission_classes, allowing unauthenticated users to access and modify data.
N+1 query patterns in ORM usage
AI-generated Django code accesses related objects in loops without select_related or prefetch_related, causing hundreds of database queries per page load.
AI Wrapper / LLM App challenges to solve
Key ai wrapper / llm app concerns that AI-generated code often misses.
API cost management
LLM API calls are expensive. A single unoptimized prompt can cost cents per request — which adds up fast with real users. You need token counting, cost tracking, usage limits per user, and prompt optimization to stay profitable.
Response time variability
LLM responses take 1-30 seconds depending on prompt complexity, model load, and output length. Your UI needs streaming responses, loading states, and timeout handling. Users abandon apps that feel slow.
Error handling for AI responses
The AI model might: return an error, time out, return malformed output, refuse to answer, or hallucinate. Each case needs specific handling. AI tools build the happy path but not the many failure modes.
Prompt injection and security
Users can manipulate your AI's behavior through carefully crafted inputs — making it ignore instructions, reveal system prompts, or produce harmful output. Input sanitization and output validation are essential.
What we check
Key areas we review for Django ai wrapper / llm app projects.
API key security — LLM API keys stored server-side, never exposed to client
Cost controls — per-user limits, token counting, usage monitoring
Streaming implementation — proper SSE/streaming for LLM responses
Error handling — timeouts, rate limits, model errors, malformed output
Not sure if your app passes? Our code audit ($19) checks all of these and more.
Start with a self-serve audit
Get a professional review of your Django ai wrapper / llm app project at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
How it works
Tell us about your app
Share your project details and what you need help with.
Expert + AI audit
A human expert assisted by AI reviews your code within 24 hours.
Launch with confidence
We fix what needs fixing and stick around to help.
Frequently asked questions
Can you review a ai wrapper / llm app built with Django?
Yes. We regularly audit Django ai wrapper / llm app projects and understand the specific patterns and pitfalls of this combination. Our review covers security, performance, and deployment readiness.
What issues do you find in Django ai wrapper / llm apps?
Common issues include debug=true in production and open django admin panel on the Django side, combined with ai wrapper / llm app-specific concerns like api cost management and response time variability. We check for all of these and more.
How do I make my Django ai wrapper / llm app production-ready?
Start with our code audit ($19) to get a prioritized list of issues. For Django ai wrapper / llm app projects, the typical path is: fix security gaps, address ai wrapper / llm app-specific requirements, optimize Django performance, then configure deployment. We provide a fixed quote after the audit.
How long does it take to audit a Django ai wrapper / llm app?
Our code audit delivers a full report within 24 hours. For Django ai wrapper / llm app projects, we check security, architecture, performance, and deployment readiness across all Django-specific patterns. Fixes are scoped separately with a fixed quote.
Related resources
Django by Use Case
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