Local code checks

Stop unsafe AI-generated code before it ships.

VibeLint scans proposed and existing source code for security mistakes that AI coding tools often introduce, then returns clear findings and safer fixes while keeping raw source local by default.

Start free Read the docs

VibeLint decision trace

agentwrite src/auth/session.ts

scaninsecure_authentication

riskJWT accepted without signature verification

fixverify the signature and restrict allowed algorithms

resultchange blocked until corrected

detector categories

Local

raw source scanning

MCP + CLI

developer workflow

What it does

How code security works

Code security analyzes the code itself. It gives an AI coding agent or developer a security decision before a risky change becomes part of the repository.

Receives code locally

Run VibeLint through an MCP-compatible coding tool, the CLI, or a pre-commit workflow. Raw source files stay on the developer machine during scanning.

Checks security boundaries

Detectors cover secrets, authentication, injection, framework configuration, CORS, static-analysis findings, prompt injection, LLM output execution, dependencies, rate limiting, and missing authentication.

Returns actionable findings

Each result identifies the detector, severity, affected file and line, why the pattern is risky, and a fix hint. Plans and workflow configuration determine the available coverage and blocking behavior.

Example: an AI agent edits authentication

Catch a security shortcut before it lands

An agent proposes decoding a session token without verifying its signature. VibeLint flags the unsafe authentication pattern and points the agent toward verified token handling.

VibeLint decision trace

agentwrite src/auth/session.ts

scaninsecure_authentication

riskJWT accepted without signature verification

fixverify the signature and restrict allowed algorithms

resultchange blocked until corrected

Example use cases

Where code security fits

AI coding agents

Review generated code before write

Let Cursor, Claude Code, Codex, Windsurf, or another MCP client scan a proposed file before accepting the change.

Catch secrets, auth mistakes, and injection paths earlier.

Repository safety

Add a pre-commit security check

Scan changed files before a commit so risky generated code does not quietly move into review or deployment.

Keep a repeatable security gate beside human review and tests.

AI applications

Inspect LLM and MCP trust boundaries

Find untrusted content entering privileged prompts or model output reaching commands, tools, file access, or other sensitive execution paths.

Separate model suggestions from authorized application behavior.

What code security does not do automatically

A static code scan does not automatically observe every terminal command or external tool call. The coding agent, MCP workflow, CLI, or hook must invoke the scan at the right point. Keep tests, dependency review, runtime controls, and human review in the workflow too.

One connected security loop

Connect code security to the rest of VibeLint.

Code checks, permission decisions, approvals, and action evidence work best together—before, during, and after an agent action.

Start free

Agent controlExplore this feature Agent logsExplore this feature

Local code checks

Stop unsafe AI-generated code before it ships.

VibeLint scans proposed and existing source code for security mistakes that AI coding tools often introduce, then returns clear findings and safer fixes while keeping raw source local by default.

Start free Read the docs

VibeLint decision trace

agentwrite src/auth/session.ts

scaninsecure_authentication

riskJWT accepted without signature verification

fixverify the signature and restrict allowed algorithms

resultchange blocked until corrected

detector categories

Local

raw source scanning

MCP + CLI

developer workflow

What it does

How code security works

Code security analyzes the code itself. It gives an AI coding agent or developer a security decision before a risky change becomes part of the repository.

Receives code locally

Run VibeLint through an MCP-compatible coding tool, the CLI, or a pre-commit workflow. Raw source files stay on the developer machine during scanning.

Checks security boundaries

Returns actionable findings

Example: an AI agent edits authentication

Catch a security shortcut before it lands

An agent proposes decoding a session token without verifying its signature. VibeLint flags the unsafe authentication pattern and points the agent toward verified token handling.

VibeLint decision trace

agentwrite src/auth/session.ts

scaninsecure_authentication

riskJWT accepted without signature verification

fixverify the signature and restrict allowed algorithms

resultchange blocked until corrected

Example use cases

Where code security fits

AI coding agents

Review generated code before write

Let Cursor, Claude Code, Codex, Windsurf, or another MCP client scan a proposed file before accepting the change.

Catch secrets, auth mistakes, and injection paths earlier.

Repository safety

Add a pre-commit security check

Scan changed files before a commit so risky generated code does not quietly move into review or deployment.

Keep a repeatable security gate beside human review and tests.

AI applications

Inspect LLM and MCP trust boundaries

Find untrusted content entering privileged prompts or model output reaching commands, tools, file access, or other sensitive execution paths.

Separate model suggestions from authorized application behavior.

What code security does not do automatically

One connected security loop

Connect code security to the rest of VibeLint.

Code checks, permission decisions, approvals, and action evidence work best together—before, during, and after an agent action.

Start free

Agent controlExplore this feature Agent logsExplore this feature