Vibe Coding Under Pressure: When Speed Kills Security
AI-assisted development accelerates shipping but introduces predictable security gaps under deadline pressure. A practical guide for CTOs managing vibe-coded teams.
Vibe Coding Under Pressure: When Speed Kills Security
A startup raised its seed round in February. By April, the CTO has promised a live product to investors. The team is small, the timeline is brutal, and every engineer is using Cursor or Copilot to write code at three times their previous velocity.
This is the vibe-coding scenario that security teams now face regularly. The output is real software that ships, and the security debt it carries is just as real.
The Three Shortcuts That Always Appear
After reviewing dozens of AI-assisted codebases built under deadline pressure, three categories of shortcut appear almost universally:
1. Authentication deferred to "later"
Early-stage vibe-coded projects almost always start with a placeholder authentication model. An AI assistant asked to "build a user dashboard" will generate a working UI backed by an endpoint that trusts the user ID sent in the request body, because the prompt did not specify session management.
# What the AI generates when auth isn't specified
@app.get("/dashboard")
def get_dashboard(user_id: int):
return db.query(UserData).filter(UserData.user_id == user_id).all()
Any user can query any other user's data by changing the parameter. This pattern ends up in production because it works during internal demos where everyone is trusted.
2. Environment variables hardcoded in tests
When a developer writes a test for a new feature, the AI assistant typically generates test fixtures that include real-looking (or sometimes real) secrets for convenience:
# AI-generated test setup
def test_payment_flow():
stripe_client = stripe.Client(api_key="sk_live_...") # pasted from .env
...
These end up committed to Git, and once a secret hits version control it is effectively leaked regardless of whether it is later removed.
3. CORS set to wildcard
When a frontend developer cannot get their local dev environment to talk to the backend, they (or their AI assistant) add the fastest possible fix:
# AI-generated CORS "fix"
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
This configuration is dangerous because allow_credentials=True combined with allow_origins=["*"] allows any website to make authenticated requests to the API using the visitor's cookies. It is also a pattern that AI assistants generate confidently and often.
A Pre-Launch Checklist for CTO Sign-Off
Rather than attempting a full security audit at launch (which rarely happens under deadline pressure), a focused checklist targeting known AI-generation failure modes is more practical:
[ ] All endpoints require authentication except explicitly public routes
[ ] No secrets in any file tracked by Git (run: git log -p | grep -E 'sk_live|password|secret')
[ ] CORS allow_origins is an explicit list, not "*"
[ ] Database queries use parameterised statements (no f-strings with SQL)
[ ] Rate limiting is in place on auth endpoints
[ ] Dependency versions are pinned (no open ranges like ^1.0.0 on critical packages)
Why This Is a Business Risk, Not Just a Technical One
A breach at seed stage is often fatal. Investors expect product risk; they do not expect to read about a customer data leak in TechCrunch three months after funding. The cost of a 40-hour security review before launch is negligible compared to the legal, reputational, and investor-relations damage of a breach.
Vibe coding does not create new vulnerability classes. It dramatically accelerates the delivery of old ones.
Key Takeaways
- Under deadline pressure, AI assistants produce working code that defers authentication, hardcodes secrets in tests, and opens CORS to all origins: these are the three most common production-ready vulnerabilities in vibe-coded projects.
- A targeted pre-launch checklist of six items catches the majority of AI-generated security shortcuts before they reach customers.
- Security investment at launch is an investor-relations decision, not just an engineering one: a breach at seed stage carries existential business risk.