AI Coding Security
Security for the AI-assisted workflow itself · AI-generated code risks, agent and MCP security, prompt injection, and AI code review.
- Is Vibe Coding Safe? Security Risks of AI-Generated Code · Vibe coding is safe only with a security layer the AI doesn't provide: in scans of 500+ AI-built apps, 63% shipped a critical vulnerability, 41% exposed API keys in client code, and 38% had broken access control. Prompt for security explicitly, review generated code, and scan every app before it ships.
- AI Code Review vs Security Review: Why You Need Both · Code review asks whether code works; security review asks whether it can be exploited · they are not interchangeable. In SimplyScan's scan data, 73% of apps that pass functional testing still have at least one vulnerability and 41% expose API keys. AI-built apps need both reviews before shipping.
- AI Security Risks: Prompt Injection, LLM Abuse, and API Key Exposure · AI features add three major risks: prompt injection, where user input overrides your system instructions; cost attacks on unprotected endpoints; and exposed AI API keys that can rack up thousands of dollars in hours. Defend with role-separated prompts, output filtering, authentication, per-user rate limits, max_tokens caps, and server-side keys only.
- OWASP Top 10 for AI-Built Apps: What Vibe Coders Need to Know · AI-generated apps are vulnerable to every OWASP Top 10 category, from broken access control to SSRF, because AI tools reproduce insecure patterns from their training data. The most common failures are frontend-only access control, missing input validation, shipped debug defaults, and outdated dependencies · all fixable with server-side enforcement and regular scanning.
- API Security Best Practices for AI-Built Applications · Every API endpoint is a public attack surface: callers can send any request, not just what your frontend allows. Secure AI-generated backends with authentication on every sensitive endpoint, schema-based input validation, parameterized queries, per-endpoint rate limits, object-level authorization checks, locked-down CORS, and generic error messages that reveal no internals.
- Why Your AI-Built App Is Slow (And How to Fix It) · AI-built apps are typically 500 to 2000ms slower than they need to be, with 30-40% larger JavaScript bundles and redundant network requests. The top fixes: remove duplicate auth calls, drop full-page loading gates, code-split routes, replace framer-motion with CSS, cache queries, and preload the hero image. SimplyScan's Speed category finds all 10 issues automatically.
- Why Cursor, Lovable, and Bolt Don't Optimize Your App's Speed (And What Does) · Cursor, Lovable, Bolt, Replit, and Windsurf optimize development speed, not runtime speed: none audit their generated code for redundant requests, missing code splitting, or heavy bundles. The result is apps that ship in a day but lose 53% of mobile visitors past 3 seconds. SimplyScan audits the deployed app and flags exactly what your AI tool left behind.
- Scan Your App for Security From Inside Cursor and Claude · SimplyScan runs a Model Context Protocol server at api.simplyscan.io/mcp, giving assistants like Claude, Cursor, and Windsurf seven tools · a full security and speed scan plus header, SSL, SEO, AI-visibility, email-security, and exposed-file checks · without leaving the editor. Your agent finds issues, writes fixes, and re-scans in one conversation.
- Is ChatGPT-Generated Code Safe to Ship? What to Check First · ChatGPT-generated code is safe to ship only after verification. It runs on the happy path but routinely carries outdated security patterns, hallucinated package names attackers can squat, placeholder credentials that become real leaked keys, and missing server-side validation. Verify every dependency, sweep for secrets, and confirm authorization before production.
- Claude Code Security Checklist: Ship Agent-Written Code Safely · Secure Claude Code by securing the session: keep auto-approval off for shell commands, deny-rule .env files so secrets never enter the context, treat everything the agent reads as a potential prompt-injection vector, review every diff before committing, vet MCP servers for source and scope, and scan the deployed app when the work ships.
- Vibe Coding Guardrails · How to Let AI Write Code Without Getting Burned · Vibe coding guardrails are fixed rules you set before AI writes any code: never hardcode API keys, enable Row-Level Security on every table, validate all input server-side, and keep secrets in environment variables. Enforce them with project-level instructions, security prompts after each feature, and an automated scan before every deploy.
- The Best AI Code Security Tools in 2026 · What Actually Catches AI-Written Bugs · The best AI code security tools fall into five categories: SAST (Semgrep, CodeQL), secret scanners (gitleaks, TruffleHog), dependency and supply-chain checkers (Snyk, Socket), DAST scanners (OWASP ZAP), and no-setup black-box scanners like SimplyScan. Vibe coders should start with a black-box scan of the deployed app, then add secret and dependency scanning.
- AI API Security · Protecting LLM-Powered Apps, Keys, and Endpoints · AI API security covers two attack surfaces: the LLM APIs your app calls and the endpoints you build around them. Keep OpenAI, Anthropic, and Gemini keys server-side behind an edge-function proxy, set spend caps and rate limits, sanitize model output, and treat prompt injection as a path to key and data leaks.
Browse other categories: Platform Security Guides · Vulnerabilities & Fixes · Database & API Security · Security Checklists · Comparisons & Reviews · Speed & Performance · Security Fundamentals
All security guides