AI Coding Security

Secure code as it's written

Architectural threat modeling inside Claude Code, Cursor, Copilot, and any MCP-compatible agent.

Install MCP →Request a demo

✓ Works with Claude Code, Cursor, Copilot✓ Zero context switching

acme-checkout — payments.ts

payments.tsuploads.tsREADME.md

1import { Request, Response } from 'express';

2import multer from 'multer';

4// POST /uploads/video

5export async function uploadVideo(req: Request, res: Response) {

6 const file = req.file;

7 if (!file) return res.status(400).send();

9 // trust the client-provided MIME type

10 const ok = file.mimetype.startsWith('video/');

11 if (!ok) return res.status(415).send();

13 await storeRaw(file.buffer, file.originalname);

14 res.json({ ok: true });

15}

main10 errorsTypeScriptUTF-8Ln 9, Col 6

The problem

AI-generated code ships without security oversight

Agents write code faster than humans can review it. The tooling that secures human-written code wasn't built for code that writes itself.

Output speedPer session

Agent output1,840 LOC

Human review capacity~340 LOC

5.4×faster than review capacity

How it works

Security awareness in the moment of generation

Three integration points. One threat model. Security travels with the agent, not after it.

Step 1

MCP integration

Works natively with Claude Code, Cursor, and other MCP-compatible agents. Zero context switching for the developer.

Agent↔MCP↔Oplane

Step 2

Threat-model-aware suggestions

Before the agent commits, Oplane checks the change against the architectural threat model. Trust boundaries, data flows, agent permissions.

Generating route...Cont.

Crosses trust boundaryCheck

Suggesting scoped tool listFix ✓

Step 3

Automated review in the agent pipeline

For autonomous workflows, Oplane runs as a security checkpoint inside the agent's own loop. Security travels with the agent, not after it.

Agent-introduced blind spots

What scanners can't see in agent-built code

?Prompt injection paths through tool definitions

?Confused deputy patterns where the agent acts beyond its scope

?Tool misuse through unbounded MCP permissions

?Token scope creep across chained agents

?Data flows the agent introduced without anyone asking for them

?Implicit trust escalation between agent-to-agent calls

For AI program leads

Unblock AI adoption without fighting security

Most AI rollout problems aren't technical. They're trust problems. Legal, security, and risk teams don't have evidence that AI-generated code is being reviewed. So they slow the rollout, or block it.

Oplane gives AI program leads the artifact those teams actually need. Continuous, architecturally-aware security review of every change the agent makes, with a paper trail.

Integrations

Wherever the agent runs

Claude Code

Cursor

Copilot

Any MCP-compatible client

Security travels with the agent

Install the Oplane MCP. See the next agent-written change get reviewed inline, before it ever reaches a PR.

Install MCP →Request a demo →