Pillar Security leads with agentic red teaming and guardrails for coding agents. Cranium AI leads with one platform that secures AI and proves it is governed. Here is how they compare across the AI Trust Loop.
Pillar Security is an AI security platform focused on agents, with autonomous red teaming, gateway-based runtime guardrails and hooks for coding agents on developer endpoints.
Cranium AI is an AI security and governance platform: it builds standards-based AI‑BOMs from code, enforces policy on live prompts and responses, red teams models, maps the EU AI Act, NIST AI RMF and ISO/IEC 42001, and shares evidence through AI Cards. Pillar suits offense-minded AppSec teams; Cranium AI suits teams that must secure AI and prove governance on one platform.
Every capability on this page, scored the same way for both platforms and rolled up by AI Trust Loop stage.
Cranium AI17/ 20AI‑BOMs exported as CycloneDX and SPDX
Repo, cloud and endpoint discovery
Live prompt and response monitoring
Gateway and API guardrails
Frameworks plus runtime policy
Approved-model lists, SAIL mapping
Inline enforcement, deterministic classifiers
RedGraph red teaming, endpoint hooks
AI Cards for vendors and customers
Audit-ready reports, red-team video
Scored across the 20 capabilities compared on this page: Documented = 1, Partial or Preview = 0.5, Unclear or Not documented = 0. Deployment and API rows are not scored. The capability list reflects what buyers ask about AI security and governance, and it includes areas where Pillar Security leads.
Pillar Security and Cranium AI overlap, but they were built to answer different first questions. Here is the short version.
| Cranium AI | Pillar Security | |
|---|---|---|
| Category | AI security and governance platform | AI and agent security platform |
| Built for | CISOs and AI governance leads who need security and proof in one place | AppSec, offensive security and SecOps teams |
| Company | Emerged from KPMG Studio in 2023. Short Hills, NJ | Founded 2024. Tel Aviv and Miami |
| How AI is found | Scans code repositories into AI‑BOMs; SIEM-based shadow AI view | Agentless repo, cloud and data connectors, plus MDM-deployed endpoint discovery |
| Runtime control | Inline Block, Modify or Pass on prompts and responses | Guardrails via AI gateways or API; pre-tool hooks on endpoints |
| Security testing | Arena automated red teaming and guardrail testing | RedGraph autonomous red teaming with video evidence |
| Regulations | EU AI Act, NIST AI RMF, ISO/IEC 42001 | EU AI Act, ISO 42001, NIST AI RMF and more, via SAIL risk IDs |
| Deployment | SaaS with US, EU and AU tenants | Managed cloud, self-hosted Kubernetes, hybrid or air-gapped |
Disclosure: Cranium AI publishes this comparison. Every Pillar Security detail comes from public sources, mainly Pillar Security’s own website, documentation, marketplace listings and press releases, plus a few third-party publications where cited, checked on October 29, 2026. Where we could not find public evidence, we say “Not documented,” never “No.” Spot something out of date? Tell us and we will fix it.
Organized by the AI Trust Loop: Discover, Observe, Govern, Secure and Prove. Cranium AI is held to the same standard as everyone else: if our docs don’t show it, we don’t claim it.
Find the AI you run
Scans GitHub, GitLab, Bitbucket and Azure DevOps (cloud and self-managed) into AI‑BOMs of models, datasets, packages, agents and static system prompts.1,2
AgentSensor maps agents, tools, handoffs, guardrails and MCP servers from source code across six agent frameworks.5
Agents, MCP servers, skills and plugins across code and endpoints, scored against a catalog of 23,000+ MCP servers.8
Shadow AI view built from connected SIEM activity: AI provider access, AI-enabled SaaS, AI web apps and embedded AI. No endpoint agent or browser extension.9
Discovery runs from code and SIEM activity. CloudSensor covers Azure security posture; no Bedrock, Vertex or Databricks connectors are documented.12
Watch what it does
Guardian inspects every prompt and response between your AI apps and the model, in Listen or Enforce mode.15,16
Tool Inspector, session reconstruction and agentic analytics: autonomy score, tool invocations and agent-to-agent handoffs.19,20
Sessions view and MCP tool pre- and post-invoke checks.18
Hold it to policy
EU AI Act, NIST AI RMF and ISO/IEC 42001, with self-attestation and automated answer scoring.21
EU AI Act, ISO 42001, NIST AI RMF, GDPR, SOC 2, OWASP and MITRE ATLAS, mapped through SAIL risk IDs.22
AI Card reviews with approve, request changes or decline, plus an audit trail. No use-case intake questionnaires.23
Approved-model lists, MCP allowlists and RBAC. Pillar rates its own intake “Partial” with “no intake questionnaires.”11
Profiles set Block, Modify or Pass per signal, separately for prompts and responses, and per agent event type.24
Defend it under attack
Enforce mode runs inline between your app and OpenAI, Anthropic Claude or AWS Bedrock models. New profiles start in Listen.16,26
PII, PHI, PCI, secrets, named entities and a custom blocklist, on prompts and responses.24,27
Direct attacks at runtime: jailbreaking, instruction override, prompt leaking, role impersonation, direct command injection and goal hijacking at runtime. Indirect injection is tested in Arena before release.27,28
Direct and indirect prompt injection, jailbreak, system prompt leakage and invisible Unicode.25
Deterministic, non-LLM classifiers. Trace shows the text and training samples behind each verdict.29,30
Arena runs fixed and adaptive multi-turn attacks across 9 LLM categories and 26 non-LLM task types, mapped to OWASP.31,28,32
RedGraph runs autonomous multi-turn attacks through an app’s UI, with video evidence, mapped to OWASP, MITRE ATLAS and NIST.33
Claims vulnerability risk assessment for models and dependencies; no CVE or OSV database is named.10
Scans imported model files for malicious code and unsafe serialization.
Scans agent config files in repositories (AGENTS.md, CLAUDE.md, .cursor, Copilot instructions) for exfiltration endpoints and hidden Unicode. No endpoint hooks.37
MDM-deployed endpoint agent with offline pre-tool hooks for Claude Code, Codex and Cursor.8
Show the evidence
AI Cards request, respond and publish AI‑BOMs, framework results and vulnerability data; My Vendors tracks every card received.38,39
Third-party AI discovery and vendor risk assessment; no transparency reports, AI cards or trust hub found.22
Framework and AI System PDF exports, AI Cards and audit trails on review decisions. Runtime evidence is not packaged into AI Cards.40,23
How it runs
Hosted in US, EU and AU regions. No self-hosted option is documented.41
“Documented” means the vendor’s public docs or product pages describe the capability as available. “Preview” covers beta, private preview and research preview. “Not documented” means we found no public evidence; it may exist behind a login or on a roadmap. Numbers link to the sources at the foot of this page.
The fastest way to see the difference is to follow one AI system through each platform.
Agentless connectors scan repos, data platforms and Bedrock; an MDM-deployed agent inventories coding agents, MCP servers and skills on laptops.
RedGraph maps an agent’s tools and permissions, then runs multi-turn attacks through its UI and records video evidence.
Guardrails run through AI gateways or the API to block or mask risky prompts, responses and MCP tool calls.
Approved-model lists, MCP allowlists and SAIL-mapped reports cover EU AI Act, ISO 42001 and NIST AI RMF.
CodeSensor and AgentSensor scan your repositories and build AI‑BOMs of the models, datasets, packages, agents and MCP servers in your code. A SIEM-fed Shadow AI view and AI Recon cover the AI you didn’t build.
Guardian watches live prompts, responses and tool calls between your apps and the model, with session reconstruction, agent analytics and cost tracking.
Map each AI system to the EU AI Act, NIST AI RMF and ISO/IEC 42001, and turn policy into runtime profiles that decide per signal.
Enforce mode blocks or modifies risky prompts and responses inline. Model files are scanned for malicious code, Arena red teams models before release and Arena Shield tests the guardrails.
AI Cards share AI‑BOMs, framework results and vulnerability data with customers, vendors and auditors, and flag when they fall out of sync.
Buyers trust comparisons that admit what the other platform does well. So do we.
RedGraph runs autonomous, multi-turn attacks through an agent’s own UI and records video, logs and transcripts for each finding.33
Endpoint hooks for Claude Code, Codex and Cursor work offline and are deployed through MDM, with a 23,000+ MCP server catalog.8
Documented guardrail integrations include LiteLLM, Kong, TrueFoundry and Portkey, and a Wiz partnership.17,14
Pillar documents self-hosted and air-gapped deployment for regulated environments.7
Cranium AI maps AI systems to the EU AI Act, NIST AI RMF and ISO/IEC 42001 with scored self-attestation, and AI Card reviews carry an audit trail.
Cranium AI exports AI‑BOMs as CycloneDX or SPDX and maps AI dependencies to known CVEs through OSV.
Guardian’s runtime detection uses deterministic, non-LLM classifiers, and Trace shows why each verdict was made.
AI Cards and My Vendors run a request-and-respond workflow for third-party AI. Pillar does not document one.
Running both? Security-heavy programs sometimes run an offensive specialist next to a governance platform. Pillar could own agentic red teaming and endpoint hooks while Cranium AI covers AI‑BOMs, governance and AI Card evidence. No native integration is documented.
Straight answers, kept current. Last verified .
Ask us anything →An AI security platform from a Tel Aviv and Miami company founded in 2024. It covers AI discovery and posture, agentic red teaming with RedGraph, runtime guardrails, agentic endpoint security and governance.
No. As of October 2026 the AI security company Pillar Security remains independent. A December 2025 acquisition reported under the same name involved a different, Toronto-based security services firm, Pillar Security of Toronto, acquired by Scarlet Security & Risk Group.
Through AI gateways such as LiteLLM, Kong, TrueFoundry and Portkey, or its API, where it can block or mask content. On developer endpoints it uses pre-tool hooks for Claude Code, Codex and Cursor. Cranium AI’s Guardian enforces Block, Modify or Pass inline between apps and the model.
Pillar references an AI‑BOM produced by a scanner in CI, but no CycloneDX or SPDX export is publicly documented. Cranium AI exports AI‑BOMs in both formats.
Only partially, by Pillar’s own account: approved model lists and policy, but no intake questionnaires. It recommends pairing with a GRC tool.
Yes. Pillar documents managed cloud, self-hosted Kubernetes, hybrid and air-gapped options. Self-hosting needs at least three GPU nodes, and adaptive guardrails are cloud-only.
Pillar has no public pricing page. Its AWS Marketplace listing shows $175,000 for a 12-month contract that scales with committed units.
If you need AI security and provable governance in one platform, Cranium AI combines AI‑BOMs, inline enforcement, red teaming, framework mapping and AI Card evidence in Cranium ONE.
How we built this page. We read Pillar Security’s public website, product documentation, developer docs, marketplace listings and press releases, and Cranium AI’s own documentation at docs.cranium.ai, on October 29, 2026. We compare documented capabilities. Announced or preview features are labeled as such, and analyst placements are left out. Product names and trademarks belong to their owners; Pillar Security has not reviewed or endorsed this page.
See how Cranium AI discovers, observes, governs, secures and proves every model, agent and vendor in your enterprise.
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