Claude Code. Cursor. Copilot. Windsurf. Devin. Cody. They all have full file system access, terminal execution, and network reach on every developer endpoint.
QuilrAI is the only platform that governs every coding agent in production. Discover, monitor, and control agent actions across all tools with sub-50ms latency -- without slowing developers down.
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.
Anthropic
How it works
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 Inc.
How it works
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 / Microsoft
How it works
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.
Codeium
How it works
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.
Cognition
How it works
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.
Sourcegraph
How it works
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.
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.
Developer says: "Add user authentication with OAuth to the API"
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
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
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
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
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.
Critical blind spots at every layer
Sees process execution but cannot understand AI intent or distinguish agent actions from developer actions
Monitors SaaS access but cannot inspect CLI-based agent activity, terminal commands, or local file reads
Pattern-matches known data formats but misses secrets in code context, MCP tool calls, or LLM prompt payloads
Collects events after the fact but has zero real-time interception capability for agent actions
What coding agents can actually do
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.
Agent installs a typosquatted or compromised npm/pip package. Malicious post-install scripts execute with full developer permissions.
Agent makes HTTP requests to unknown endpoints, leaking source code, internal URLs, or authentication tokens to external servers.
Agent inserts subtle backdoors: hardcoded credentials, weakened crypto, or hidden endpoints that bypass authentication checks.
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.
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.
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.
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.
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
Four enforcement planes working together to govern every coding agent action. Each plane addresses a different layer of the attack surface.
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
See QuilrAI in action across different coding agents. Each scenario shows a real attack vector being intercepted in real time.
Press Play to see QuilrAI intercept a live attack scenario
AI Security Posture Management for coding agents. Know exactly who is using what agent, where, and with what permissions -- across your entire engineering organization.
Auto-discover every coding agent installed across all developer endpoints. No manual enrollment required.
Map each agent's actual permissions: file access scope, terminal capabilities, network reach, MCP server connections.
Track agent usage patterns per developer, team, and repository. Identify shadow AI adoption and usage anomalies.
Continuous risk assessment based on agent type, permissions granted, data accessed, and policy violations over time.
4
Enforcement Planes
<50ms
Decision Latency
6+
Agents Covered
Full
Audit Trail
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.
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.