Practical baseline safeguards for ChatGPT-powered services
When building an application using the OpenAI API, it is tempting to ship as soon as “it works.”
However, insufficient safeguards often lead to API key leakage, unexpected traffic spikes, and ultimately serious billing incidents.
This article summarizes practical, lightweight protections that are especially relevant for:
- personal projects
- internal tools
- early-stage prototypes
These are not universal requirements.
What counts as a “baseline” depends heavily on your threat model, user anonymity, billing model, and scale.
- A common but underestimated risk
One frequently overlooked risk is direct access to your backend API endpoints, bypassing the UI entirely.
In practice, incidents may also be caused by:
- abuse by authenticated users
- bugs or retry loops
- misconfigured proxies or shared environments
However, direct scripted access to your backend is a very common failure mode, especially when no safeguards exist.
If an attacker can replay the exact same request your frontend sends, they can often exhaust your usage limits in minutes.
This article therefore focuses primarily on protecting your backend (Workers / server) rather than the UI.
- Never call the OpenAI API directly from the client
Your frontend should never call the OpenAI API directly.
- API keys embedded in browsers or apps will leak
- DevTools, network inspection, and modified requests make this trivial
Recommended architecture
Client → Your backend (Workers / server)
Backend → OpenAI API
The client receives only the processed result.
This allows you to:
- keep API keys secret
- validate and throttle requests
- support streaming safely
OpenAI explicitly recommends this approach in its official documentation.
- Always implement rate limiting
Rate limiting is essential, even for small projects.
Typical limits include:
- per 5 minutes
- per hour
- per day
Implementation can be simple:
- store a counter
- store the start time of the window
Cloudflare Workers with KV, Durable Objects, or D1 make this straightforward using IPs, user IDs, or session identifiers.
- Lightweight one-time tokens (with clear limitations)
To discourage trivial scripted abuse, you may introduce short-lived request tokens.
For example:
- embed an encrypted timestamp
- validate that it was generated recently (e.g., within 10 seconds)
⚠️ Important limitations
- This is not cryptographically strong authentication
- This does not fully prevent replay within the valid window
- This must never replace proper authentication
Think of this as friction, not security.
It is useful against:
- naive replay scripts
- casual scraping
- low-effort abuse
It is not sufficient against a determined attacker.
- Review auto-recharge and billing assumptions carefully
Billing incidents are often underestimated.
There are real-world reports of:
- usage continuing briefly after limits were reached
- negative balances appearing despite prepaid setups
Budget limits should be treated as operational safeguards, not hard guarantees.
For small projects, consider:
- disabling auto-recharge
- keeping balances low
- adding monitoring and alerts
Using a dedicated debit card with a low limit can further cap worst-case damage.
- Production services require real authentication
The measures above are suitable for:
- prototypes
- internal tools
- anonymous experiments
For real services, you will need:
- OAuth or equivalent authentication
- session and token management
- per-user quotas and permissions
IP-based checks alone are insufficient, as client-side values can be forged.
Defense must be layered: authentication, rate limits, quotas, and monitoring.
- Never let the client choose the model
Model selection directly affects cost.
Best practice:
- fix allowed models on the server
- reject anything outside a strict allowlist
Do not rely on obscurity or “confusion” tactics.
Clear validation and rejection are safer, simpler, and easier to operate.
Conclusion
For small-scale ChatGPT-powered services, the following baseline practices already eliminate many real-world incidents:
- keep API keys on the server
- enforce rate limits
- treat billing controls realistically
These measures will not make your system unbreakable — but they raise the cost of abuse enough that most attackers move on to easier targets.
Security is not about perfect defenses, but about making misuse inconvenient and uneconomical.
Original Japanese article (source of revision): https://qiita.com/uni928/items/061432019b316e418902
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