How Windsurf and Cursor help with secure code review

Editors with built-in agents — Windsurf, Cursor, and similar forks of VS Code — are useful for AppSec work, not only for shipping features faster. This post is how I use them on secure code review.

What they are

Windsurf and Cursor add autocomplete and agents that can read the tree, edit files, and run commands. Typical capabilities:

• Run shell commands
• Search and read files with project context
• Create and modify files

Those are “basic,” but they map cleanly onto review workflows.

Contextualization

On a multi-million-line repo you normally spend hours answering:

• Languages and frameworks
• Project layout
• How authentication works
• How authorization works

With an agent that can list the tree and open key files, that drops to minutes: ask how the project is structured, then ask for a short summary of authn/authz. You still verify, but the first pass is fast.

Enumeration

When I start a new target I want every endpoint and its access controls. Ask the agent for a table: path, method, auth required, notes. On one project that produced 170+ routes with the fields I asked for.

Disclaimer: models are not 100% accurate. Treat the list as a draft and verify before you report.

Agents can also run commands, so enumeration is not only static grep.

Explanation and debugging

When a fragment is opaque, the agent already has file context — useful for “what does this path do?”

For debugging:

• Static — place console.log (or equivalent) where it actually helps.
• Dynamic — adjust the app or Dockerfile so you can attach a remote debugger when the built-in tools need it.

Light SAST

Agents catch common patterns (SQLi, XSS, and friends) reasonably well. Do not expect deep multi-step bugs from a single prompt. Training data skews toward known patterns; always verify.

Alternatives (prices as of the original post, mid-2025)

Windsurf’s normal plan was about $15/mo (500 credits); Cursor about $20/mo. For review work, Windsurf credits lasted me a full month even with heavier agents. Other options I looked at:

• Kilo Code — BYOK
• Roo Code — BYOK
• Claude Code — terminal; strong context, expensive at the high tier
• Gemini CLI — free tier; privacy tradeoffs
• Warp — terminal + agents (~$18/mo)
• Deep Wiki — web GUI, BYOK, self-hosted

My pick at the time was Windsurf. Examples in the original write-up used Claude 4; other models will not match that quality. Privacy matters in client work — Windsurf can disable telemetry/code training; check whatever tool you pick.

Closing notes

I left out PoC generation and MCP integrations (worth their own post). A few rules I keep:

• If you are still learning, agents can skip the muscle you need to verify AI output. Learn the basics first, then accelerate.
• The prompt is most of the leverage.
• Agents do not replace manual review; they assist it.

This is personal practice, not a vendor pitch.