Introducing: Pillar For AI Coding Agents

Today we're excited to announce Pillar for AI Coding Agents, a unified security solution that discovers and secures every AI agent deployed locally across your enterprise environment. It provides complete visibility and runtime control into security risks that exists in Claude Code, Cursor, Codex, Antigravity, GitHub Copilot, OpenClaw and emerging AI development tools, scanning their configurations, permissions, MCP server connections, and behavioral detection of AI Coding Agent in runtime. 

Pillar for AI Coding Agents extends the Pillar platform to endpoint deployments, giving customers a unified view and control of their AI stack from development to production and from discovery to runtime.

The AI Coding Agents Attack Surface 

AI Coding Agents are everywhere. Developers use local AI agents to write code, execute commands, manage files, and interact with external services. These tools operate with extensive privileges and access to sensitive corporate data. Agents have access to file systems  and can read any project file or environment variable, run arbitrary commands and install packages, use tools to connect to production databases with stored credentials, and custom hooks that execute code on every action

Security teams face two problems:

Configuration Posture Risks

• Agent configurations scatter across home directories (.cursor, .claude, .continue) with no central inventory

• MCP servers store hardcoded credentials for production databases and cloud services

• Access controls grant wildcard permissions and unrestricted tool invocations

• Custom plugins and skills execute arbitrary code without security review

• Shadow AI proliferates when employees install unapproved agents without proper IT approvals

Runtime Execution Threats

• Direct and Indirect Prompt injection attacks manipulate agent behavior through malicious instructions

• Tool poisoning exploits MCP metadata to execute unauthorized commands

• Credential harvesting and data exfiltration occur during active sessions

• Unauthorized API calls bypass security gateways

• Anomalous command execution deviates from normal workflows

• Context window data leakage exposes credentials and proprietary code

Security teams have zero visibility into any of it and can't answer basic questions:

• Which local AI agents run across our organization?

• What permissions and system access did these agents have access to?

• What do agents actually do during runtime?

• Do MCP servers connect to production with valid credentials?

• Are behavioral anomalies indicating compromise?

Introducing: Pillar for AI Coding Agents

Pillar for AI Coding Agents provides protection through two integrated security layers:

Layer 1: Deep Configuration Posture Management

Discover and analyze every AI coding agents. Get full visibility into agent inventory, permission scopes, MCP server connections, and credential exposure. Harden configurations before runtime execution begins.

Layer 2: Active Runtime Behavioral Controls

Monitor agent actions during execution with real-time threat detection and policy enforcement. Behavioral analysis identifies prompt injection attempts, tool poisoning exploitation, data exfiltration, and anomalous patterns. Alert, log, or block malicious actions based on your risk tolerance.

Key capabilities: 

Discover Every AI Agent Across Your Organization

Pillar scans every workstation to find coding assistants like Claude Code, Cursor, and GitHub Copilot, plus custom research tools and productivity agents. Dependency files and environment manifests reveal shadow AI that employees installed without IT approval. You get a complete inventory showing which agents run where and their risks, regardless of how they were deployed or where they're installed.

Scan Configurations for Security Risks

Agent configuration files hide critical risks. Pillar scans policy files for excessive permissions and overly broad access scopes. It identifies settings with high loop limits or unrestricted recursive calls that enable excessive agency. Network configurations reveal direct model connections that skip the AI gateway, bypassing required proxies and firewalls. Connection strings and manifests expose untrusted MCP servers. Pillar also detects which agents can exfiltrate data to arbitrary public domains. Auto-run flags indicate immediate code execution without approval. Missing input filters and sensitive file paths in context definitions create data exposure risks. Authentication settings set to optional or disabled allow unauthorized account access.

Detect Attacks During Execution

Runtime monitoring catches attacks that configuration scans miss. Pillar watches context windows and external content processing to identify prompt injection—malicious instructions embedded in files or web content that hijack agent behavior. Tool poisoning detection triggers when agents execute unauthorized commands based on poisoned MCP metadata. Data leakage prevention tracks credentials, API keys, and PII being included in context windows or transmitted to external endpoints.

Learn Normal Behavior, Flag Anomalies

Pillar establishes behavioral baselines for each agent deployment—typical file access patterns, command execution sequences, network communications, and tool invocations. Deviations trigger alerts. Rapid sequential access to credential files signals harvesting attempts. Unusual directory traversal indicates reconnaissance. Suspicious command patterns reveal lateral movement or privilege escalation. Unauthorized API calls show gateway bypass.

Enforce Policies, Respond to Threats

Security policies apply across the full lifecycle. Configuration-time validation blocks risky deployments before agents execute. Runtime enforcement monitors active sessions and stops policy violations during execution. When threats surface, configurable responses kick in - alert your security team, log events for forensic analysis, terminate compromised sessions, or block specific operations. You control the balance between protection and productivity based on your risk tolerance.

Unified AI security platform: across your entire AI stack

Pillar for AI Coding Agents is part of the unified Pillar platform, giving you visibility across every layer of your AI stack.  AI Coding Agents Security extends Pillar's coverage from cloud AI services and API-based applications down to the endpoint, where developers run coding assistants and productivity tools on their workstations.

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Available Now

Pillar for AI Coding Agents delivers what security teams actually need: complete visibility, actionable findings, and audit documentation. It works with any AI coding assistant, deploys in minutes, and provides results you can immediately act on. 

Visit pillar.security/get-a-demo to schedule a demonstration or contact sales@pillar.security.

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