Enkrypt AI vs Pillar Security

About Pillar Security

Pillar Security sells one platform to discover, test, secure and govern every AI agent across an organization. Pillar catalogs AI agents, models, prompts, frameworks, tools, MCP servers, skills and coding agents through agentless integrations. The catalog covers shadow AI and unapproved systems deployed without oversight. Pillar maps instructions, data sources, tool permissions, and external connections for each agent. Pillar traces dependencies across models and agent harness and scans agent configs, permissions, and identities.^[1][2][3][4]

For discovery, Pillar works through agentless integrations with source code repos, data platforms, and endpoints. Pillar assesses risks in AI stacks from vulnerabilities in models, frameworks, and dependencies. Pillar flags violations when unsanctioned AI appears in an environment. Pillar policy rules enforce approved models, frameworks, and data sovereignty standards across an AI stack. Pillar generates audit reports for GDPR, SOC 2, EU AI Act, and ISO 42001.^[4]

For testing, Pillar executes multi-turn adversarial attacks against complete AI systems to test tool orchestration, permission escalation, and agentic workflows. Pillar maps an AI attack surface as a graph showing relationships between agents, tools, permissions, and data sources. RedGraph maps how tools, prompts, and data combine to create exploitable surfaces specific to an environment. Pillar tests AI platforms, third-party agents, and production systems that a customer does not own or control through multi-step black box adversarial attacks against prompts, tools, and workflows. Pillar documents exploitability with attack transcripts, recordings and reproduction steps, and feeds validated findings into adaptive guardrails.^[2][3][5]

For runtime protection, Pillar analyzes user and agent intent to detect malicious behavior before it impacts production. Pillar identifies PII, PHI, secrets, and credentials flowing through AI interactions in real time. Pillar applies configurable policies to mask, block, or log sensitive data before exposure to AI models or external systems. Pillar guardrails calibrate using red teaming findings from specific applications to tune protection against the manipulation patterns detected during testing. Pillar logs prompts, responses, tool invocations, and results with timestamps. Pillar streams telemetry to security platforms for centralized monitoring.^[6]

For developer machines, Pillar deploys through an MDM and inventories the AI coding agents across a fleet: which agents run where, their versions, sandbox state and risk. Pillar runs full configuration scans for Claude Code, Cursor, Codex CLI, Gemini CLI, OpenCode and Pi Coding Agent, and detects other agents such as Amazon Q, Antigravity, Codeium and OpenClaw by fingerprint. Runtime Guardian sits in the agent's own pre-tool hook for Claude Code, Codex CLI and Cursor, and decides on every action before it runs. Pillar inventories local and remote servers across a fleet and scores each against a catalog of 23,000+ pre-analyzed servers. Pillar rolls out through Jamf Pro, Kandji, JumpCloud or any MDM that runs scripts, on macOS, Linux and Windows. On endpoints, Pillar analyzes permissions, credentials, access scopes, and auto-run settings, then provides step-by-step remediation. At runtime, Pillar monitors every prompt, tool call, and command to detect prompt injection, tool poisoning, and data exfiltration.^[7][8]

For governance, Pillar translates governance policies into technical controls that enforce approved models, licensing standards, and data sovereignty requirements at every stage. Pillar extends governance controls to external AI providers, SaaS platforms, and vendor integrations. Pillar maps governance findings, testing results, and runtime logs to regulatory requirements automatically. Pillar adds a security enforcement layer on AI gateway frameworks without re-architecting a stack. Pillar inspects every prompt and response in real time for sensitive data exposure, prompt injection, toxic content, and policy violations. For tool integrations, Pillar validates at runtime that tool calls match their declared schemas and flags anomalous behavior, like a tool accessing resources outside its expected scope.^[8][9]

Pillar can be deployed in its managed cloud, in a customer's own cloud account or data center, or as a mix of both. Self-hosted deployments include runtime guardrails, AI discovery, red teaming and agentic endpoint security. Adaptive guardrails are available in the managed cloud only today. Telemetry back to Pillar is off unless the customer enables it. A Fortune 300 manufacturer runs Pillar fully self-hosted. Pillar cites SOC 2 Type II and ISO/IEC 27001:2022.^{[1][6][7][8][10]}