QuilrAI
Solutions / Agentic Coding

Secure every coding agent

Claude Code. Cursor. Copilot. Windsurf. Devin. Cody. They all have full file system access, terminal execution, and network reach on every developer endpoint. QuilrAI governs every coding agent in production — discover, monitor, and control agent actions with sub-50ms latency, without slowing developers down.

Claude CodeCursorGitHub CopilotWindsurfDevinCody
The Landscape

The agentic coding landscape

Six major coding agents are already deployed across engineering teams. Each operates differently, but they all share one thing: deep access to your most sensitive assets.

Claude Code

Anthropic

Terminal-based agent with full codebase read/write, shell execution, and MCP server access. Operates directly on developer endpoints.

Risk surface

Unrestricted filesystem and terminal access. Can read secrets, modify configs, and execute arbitrary commands with developer privileges.

Cursor

Cursor Inc.

IDE-integrated AI editor that reads your entire project, generates and edits code inline, and runs terminal commands from within the editor.

Risk surface

Deep project context means full access to source code, credentials in config files, and ability to silently modify any file in the workspace.

GitHub Copilot

GitHub / Microsoft

Code completion and chat agent embedded in VS Code and JetBrains. Expanding agent mode with workspace and CLI tool access.

Risk surface

Sends code context to cloud for completion. Agent mode can execute shell commands and access workspace files including secrets.

Windsurf

Codeium

AI-native IDE with Cascade agent that writes, edits, runs, and debugs code across full project directories with persistent memory.

Risk surface

Persistent memory across sessions means accumulated context about your codebase. Full terminal and file write access with autonomous multi-step execution.

Devin

Cognition

Fully autonomous software engineer that plans, writes code, runs tests, debugs, and deploys with minimal human oversight in a sandboxed environment.

Risk surface

Autonomous operation means less human review. Can interact with APIs, install packages, modify infrastructure, and push code to production.

Cody

Sourcegraph

Code intelligence agent that indexes entire codebases and repositories to provide context-aware code generation, explanation, and modification.

Risk surface

Reads entire codebases including private repos. Cross-repo context means potential data leakage between project boundaries.

Under the Hood

How agentic coding works

From a single natural language instruction, coding agents execute a multi-step pipeline with deep system access at every stage. Here is what happens under the hood — and where the risks are.

  1. 01

    Natural language instruction

    Developer says: "Add user authentication with OAuth to the API."

  2. 02

    Codebase read & context

    Agent reads project files, package.json, configs, environment files, existing auth code, database schemas.

    Could read environment secrets, tokens, database credentials, SSH keys, internal documentation.

  3. 03

    Multi-file planning

    Agent plans changes across routes, middleware, models, tests, and configuration files.

    Plans may include modifying security-critical files like auth configs, CORS settings, or firewall rules.

  4. 04

    Code execution

    Agent writes code, runs shell commands, installs packages, calls APIs, modifies git history.

    Arbitrary command execution with developer privileges. Could exfiltrate data via curl, install malicious packages, or modify production configs.

  5. 05

    Tool & server access

    Agent connects to MCP servers, external APIs, databases, cloud services, and CI/CD pipelines.

    Network access enables data exfiltration. MCP servers extend reach to any connected service. No visibility into what data leaves the machine.

The Gap

Why existing security fails

Traditional security tools were built for human-driven workflows. Coding agents operate at machine speed, through CLI interfaces, with no browser or SaaS layer to inspect. Every existing tool has critical blind spots.

Traditional security

Critical blind spots at every layer

  • EDR / Endpoint Detection

    Sees process execution but cannot understand AI intent or distinguish agent actions from developer actions.

  • CASB / Cloud Access Broker

    Monitors SaaS access but cannot inspect CLI-based agent activity, terminal commands, or local file reads.

  • DLP / Data Loss Prevention

    Pattern-matches known data formats but misses secrets in code context, MCP tool calls, or LLM prompt payloads.

  • SIEM / Log Aggregation

    Collects events after the fact but has zero real-time interception capability for agent actions.

The real attack surface

What coding agents can actually do

  • Environment secrets theft

    Critical

    Agent reads config files containing tokens, database credentials, and cloud access keys. Data is sent as context to the LLM provider or exfiltrated via tool calls.

  • Malicious package injection

    Critical

    Agent installs a typosquatted or compromised npm/pip package. Malicious post-install scripts execute with full developer permissions.

  • Unauthorized API calls

    High

    Agent makes HTTP requests to unknown endpoints, leaking source code, internal URLs, or authentication tokens to external servers.

  • Code backdoors

    High

    Agent inserts subtle backdoors: hardcoded credentials, weakened crypto, or hidden endpoints that bypass authentication checks.

Guardian Agents

How QuilrAI protects coding agents

QuilrAI auto-creates a dedicated Guardian Agent for every coding agent it discovers. The Guardian reads the agent's system prompt, understands it should only modify files in the project directory, and builds dynamic guardrails in real time.

Scoped file access

Guardian enforces project-directory-only access. The coding agent cannot read or write files outside its permitted workspace, even if instructed to by a prompt injection.

No secrets access

Environment variables, credentials, and key files are walled off. Guardian blocks any attempt to read, exfiltrate, or log secrets from .env, keychains, or cloud credential stores.

Controlled command execution

Guardian restricts terminal execution to safe, scoped commands. Arbitrary shell execution, package installs from untrusted sources, and privilege escalation are caught and blocked sub-30ms.

Continuous red teaming

A Red Team Agent continuously probes the coding agent and its Guardian for prompt injection in code comments, malicious package installs, and intent misalignment, auto-fixing gaps as they are found.

What this looks like in Guardian setup

  • Allow shell command execution? → Tools: bash_exec, npm_installApprove
  • Allow file write access? → Scoped to: /project directory onlyApprove
  • Which repos? → quilrai/main, quilrai/config2 selected

Learn how Guardian Agents work

Enforcement Planes

How QuilrAI secures agentic coding

Four enforcement planes working together to govern every coding agent action. Each plane addresses a different layer of the attack surface.

Endpoint Plane

Endpoint Agent

  • Discovers every coding agent running on the device (Claude Code, Cursor, Copilot, etc.)
  • Monitors CLI processes, file access patterns, and terminal command execution in real time
  • Enforces file access policies: block reads to environment files, SSH keys, credential stores
  • Command allowlists and denylists: prevent dangerous shell operations (rm -rf, curl to unknown hosts)
  • Lightweight daemon with <1% CPU overhead, zero developer configuration required
MCP Gateway

MCP Tool Governance

  • Intercepts every MCP tool call before execution (filesystem, git, database, API tools)
  • Server authentication: only approved MCP servers can connect to coding agents
  • Permission scoping: each tool gets minimum required access (read-only filesystem, specific git repos)
  • Data redaction: secrets and PII automatically stripped from tool call parameters and responses
  • Full audit log of every tool invocation with request/response payloads
LLM Gateway

LLM Prompt/Response Inspection

  • Inspects every prompt sent to the LLM provider before transmission
  • Detects secrets, credentials, and internal URLs in prompt context
  • Response scanning: reviews generated code for backdoors, vulnerabilities, and policy violations
  • Code review gate: dangerous code changes require human approval before agent can apply them
  • Token-level analysis for prompt injection attacks embedded in code comments or documentation
Browser Plane

Dashboard & Policy Management

  • Centralized policy editor: define rules per team, repo, agent type, or individual developer
  • Real-time activity dashboard: see every agent action across the entire engineering organization
  • Audit log explorer: search, filter, and export complete agent action history
  • Compliance reporting: SOC 2, ISO 27001, and HIPAA-ready audit exports
  • Alert configuration: Slack, PagerDuty, and webhook notifications for policy violations
Experience Center

Interceptions, as they actually happen

QuilrAI across three coding agents. Each transcript shows a real attack vector being intercepted in real time — secrets reads blocked, typosquatted packages stopped, hardcoded credentials flagged.

Claude Code · guardian active

dev Read the database config and help me optimize the connection pooling.

agent I'll read the database configuration file to understand the current setup.

$ cat config/database.yml

allowed

Guardian: config/database.yml is within project scope.

agent Now let me check the environment variables for connection strings...

$ cat .env

blocked

Guardian: .env contains sensitive values (DB_CONN, AUTH_TOKEN). File read denied. Suggesting: use environment variable injection instead.

agent I understand. Let me work with the sanitized config values instead and recommend pool size based on the database.yml settings.

Cursor · guardian active

dev Add a logging library to the project and set up structured logging.

agent I'll install a logging package and configure it for structured output.

$ npm install loggly-winston-transport@0.0.2

blocked

Guardian: Package 'loggly-winston-transport@0.0.2' flagged: known typosquat of 'winston-loggly-transport'. 3 downloads/week, published 2 days ago, contains post-install script with network calls.

agent Let me use the verified package instead.

$ npm install winston@3.11.0

allowed

Guardian: Package 'winston@3.11.0' verified: 9.8M weekly downloads, no known vulnerabilities, on approved package list.

GitHub Copilot · guardian active

dev Help me write the API authentication middleware.

agent Here is the authentication middleware:

const SECRET = "hardcoded-value-here";
const authenticate = (req) => {
  return req.headers.auth === SECRET;
};
flagged

Guardian: Generated code contains hardcoded credential pattern. Suggesting: load from environment variable via process.env instead.

agent You are right. Here is the corrected version:

const authenticate = (req) => {
  const secret = process.env.AUTH_SECRET;
  if (!secret) throw new Error("Not configured");
  return req.headers.auth === secret;
};
allowed

Guardian: Code follows secure credential handling practices.

AI-SPM

Full visibility into agent usage

AI Security Posture Management for coding agents. Know exactly who is using what agent, where, and with what permissions — across your entire engineering organization.

Agent inventory

Auto-discover every coding agent installed across all developer endpoints. No manual enrollment required.

Permission mapping

Map each agent's actual permissions: file access scope, terminal capabilities, network reach, MCP server connections.

Usage analytics

Track agent usage patterns per developer, team, and repository. Identify shadow AI adoption and usage anomalies.

Risk scoring

Continuous risk assessment based on agent type, permissions granted, data accessed, and policy violations over time.

Enforcement planes
4
Enforcement planes
Decision latency
<50ms
Decision latency
Agents covered
6+
Agents covered
Audit trail
Full
Audit trail
Deep Dive

Claude Code, the most detailed breakdown

Claude Code is the #1 agentic coding tool and the highest-risk. See exactly what QuilrAI intercepts, how Guardian configures scope, and why it needs its own enforcement plane.

See Claude Code in depth

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See it in action

Get a live walkthrough of QuilrAI securing coding agents across Claude Code, Cursor, Copilot, and more. See real interceptions, policy enforcement, and audit logs on real developer endpoints.