# Cytex

> Cytex is an AI-powered unified security platform that integrates cybersecurity, compliance automation, and AI governance into a single solution to help organizations protect their digital ecosystems and stay audit-ready.

Cytex, Inc. delivers patented, SaaS-based AI-driven cybersecurity and compliance solutions designed to rationalize security tooling, automate governance, and secure AI adoption across enterprises, MSPs/MSSPs, and the public sector. The platform unifies threat detection, data protection, cloud security, supply chain risk, and continuous compliance, augmented by an embedded AI co-pilot (LEO) and the AICenturion AI security and governance layer.

Headquartered in Maryland with offices in Texas and New York. Strategic partners include Intel, NVIDIA Inception, Marsh, MIT Cyber Defense Clinic, and NUARI.

## Sitemap

https://www.cytex.io/page-sitemap.xml

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## Industry Recognition

- [Cytex Named a Representative Vendor in the 2026 Gartner® Market Guide for DevOps Continuous Compliance Automation Tools](https://www.cytex.io/compliance_automation_cytex/#gartner-recognized-cytex) - Cytex has been named a Representative Vendor in the March 2026 Gartner® Market Guide for DevOps Continuous Compliance Automation Tools (G00847350). The recognition reflects Cytex's AI-powered, unified compliance automation across the DevOps lifecycle, including automated evidence collection, AI-assisted remediation, 120+ pre-built integrations, and continuous compliance posture management across frameworks such as CMMC, FedRAMP Rev 5, HIPAA, ISO 27001:2022, ISO 42001, NIST CSF 2.0, NIST SP 800-53 Rev 5, PCI DSS v4, and SOC 2. Gartner forecasts that by 2028, 65% of organizations will have integrated compliance automation into their DevOps workflows, and 75% of those processes will leverage AI technology — a direction Cytex's unified architecture was built to serve. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates. Gartner does not endorse any vendor, product or service depicted in its research publications.

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## Federal & Defense Programs

- **U.S. Department of the Army — NCODE (Next-Gen Commercial Operations in Defended Enclaves)** - Cytex has been awarded a contract by the U.S. Department of the Army under the NCODE initiative, selected through a competitive process to support the Defense Industrial Base. Under this award, Cytex delivers its AI-powered unified platform to consolidate threat visibility, accelerate remediation, and maintain continuous compliance at machine speed across DIB environments. The award aligns with the Department of War's accelerated AI-driven modernization agenda and strengthens classified network security through unified platform architecture that eliminates tool sprawl and delivers resilience against AI-augmented threats.

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## AI Security

- [AICenturion - Unified AI Governance](https://www.cytex.io/ai-security/aicenturion_cytex/) - All-in-one AI governance platform. Discovers shadow AI, enforces compliance with NIST AI RMF, EU AI Act, MITRE ATLAS, and OWASP, prevents prompt-level data exfiltration, and delivers Governance-as-a-Service for responsible AI deployment at enterprise scale.
- [Agentic AI Security](https://www.cytex.io/ai-security/agentic_ai/) - Protection and policy enforcement for agentic AI tools, securing non-human identities and preventing data exposure from autonomous AI workflows.
- [LEO - AI Security Co-Pilot](https://www.cytex.io/leo/) - Embedded AI engine providing role-based assistance for CISOs, IT analysts, threat intelligence, and compliance managers. Covers risk discovery, remediation, POAM generation, and code and insight generation.

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## AICenturion - Unified AI Governance Platform

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/

AICenturion by Cytex is an enterprise AI governance and security platform providing unified visibility, control, and compliance coverage across every AI model, agent, and Copilot in an organization's environment. It operates at the prompt, model, and agent boundary — the new perimeter created by generative AI — where traditional DLP and cloud security tools have no coverage.

Core capabilities span real-time prompt-level monitoring, automated red teaming, shadow AI discovery, AI Bill of Materials (AIBOM), Microsoft Copilot security assessment, configurable runtime guardrails, MCP Guardian, data lineage and context graphs, and a semantic ontology layer that binds AI activity to regulatory frameworks and data classifications. All capabilities share one data model and one audit trail.

**Value proposition:** "See every model. Govern every prompt. Prove every control."

**Primary buyers:** CISO / Head of Security (economic buyer), CIO / VP Engineering, Head of AI / ML Platform, Chief Compliance Officer / GRC Lead, Data Protection Officer, SOC / Detection Engineering, Microsoft 365 / Workplace IT.

**Strongest industry fit:** Financial services and insurance (prompt leakage of non-public information, audit burden, EU AI Act), healthcare and life sciences (PHI in prompts as HIPAA events, EHR MCP integrations, clinical decision support as high-risk AI under EU AI Act), public sector and defense (NIST AI RMF and DoD AI Ethical Principles as procurement requirements, AIBOM as a deliverable). Also strong for enterprise SaaS shipping AI features, Fortune 1000 organizations deploying Microsoft 365 Copilot, and professional services firms with client confidentiality obligations.

**Deployment options:** Multi-tenant SaaS (default), dedicated single-tenant SaaS for regulated industries, self-hosted in customer VPC or on-premises, and hybrid (SaaS control plane with self-hosted sensors and gateway).

---

### Why AICenturion - AI Governance

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/#why-aicenturion-ai-governance

Five converging pressures define the problem AICenturion solves, and AICenturion addresses all five in one platform:

**Prompt-level data leakage.** Employees paste source code, credentials, PII, PHI, customer records, and internal strategy into public LLMs. Traditional DLP inspects files and network egress but cannot parse natural-language prompts for sensitive content and has zero visibility into browser-based LLM interfaces or SaaS-embedded Copilots.

**Shadow AI.** Line-of-business teams adopt LLM APIs and expose internal data through MCP servers and RAG pipelines without informing security. A typical enterprise AI attack surface is 3-10× larger than the models the CISO knows about.

**Regulatory pressure.** EU AI Act enforcement, NIST AI RMF adoption, ISO/IEC 42001 certification demand, state-level AI laws, and sector rules including HIPAA, GLBA, and FERPA all require documented AI risk controls, model inventories, and testing evidence.

**Supply-chain opacity.** Most enterprises cannot produce an inventory of the base models, fine-tuned layers, datasets, embeddings, frameworks, and plugins powering the AI features they ship — the same gap SBOMs addressed for software.

**Safety and brand risk.** LLMs can produce toxic, illegal, defamatory, or competitor-promoting output. A single viral screenshot of a company's chatbot behaving harmfully is a material brand and legal event.

AICenturion addresses all five in one platform, replacing the fragmented coverage of web proxies (traffic only), traditional DLP (files only), and model-evaluation libraries (isolated models, no compliance alignment).

---

### Unified Dashboard and Real-Time Insights

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/

The AICenturion Insights Dashboard is the single-pane-of-glass for AI security operations, unifying four telemetry streams on one screen.

**Timeline chart** plots sensitive-data exposure, AI safety events, and guardrail violations on a shared time axis. Correlated spikes across streams signal active incidents.

**Violations donut** shows current-period breakdown across PII, PHI, credentials, email addresses, resource locators, credit card data, violent crimes, child sexual exploitation, and custom categories — covering data leakage and AI safety simultaneously.

**Prompt Activity bars** separate override, review-needed, blocked, and flagged events by data type, distinguishing sensitive-data violations from AI safety violations.

**Users At Risk panel** surfaces repeat offenders by risk tier (High, Medium, Safe) with violation counts, enabling targeted user intervention rather than broad policy messaging.

---

### AI Runtime Governance - Configurable Guardrails

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/#ai-runtime-governance

Guardrails are policy-enforced filters applied to every prompt and every response in real time at the prompt boundary, with sub-50ms p50 latency overhead. They are the enforcement layer of governance — policy without guardrails is a document. Guardrails are scoped per policy group by user, team, model, or application, and operate in dry-run or enforce modes. Every user override is logged and never silent.

**Guardrail types available:**

- **Competitor Check** - Flags and optionally rewrites competitor mentions in LLM output. Fuzzy-matched to catch variants and alternate spellings.
- **Ban List** - Fuzzy-matches against banned words and phrases, catching close variants across spellings.
- **Toxic Language** - Detects and blocks toxic output categories in real time.
- **PII Detection** - Enforces protection over selectable entity types: names, email addresses, phone numbers, government IDs, financial identifiers.
- **Sensitive-data redaction** - Redacts PII, PHI, credentials, and classified content before it reaches an LLM or exits in a response.
- **Jailbreak detection** - Identifies and blocks adversarial prompt structures designed to bypass model safety controls.
- **Prompt-injection defense** - Detects attempts to hijack model instructions through injected content.
- **Topic restriction** - Constrains model responses to approved subject domains.
- **PII egress controls** - Prevents personally identifiable information from exiting the enterprise through LLM responses.
- **Custom rules** - Configurable via regex and semantic definitions.

---

### Activity Audit and Forensics

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/

AICenturion maintains a row-level audit log of every AI interaction, capturing timestamp, user or API key, model, token count, cost, override status, prompt data categories, AI safety flags, guardrail result, and full prompt and response content.

A forensic detail panel provides per-violation category breakdown for any individual interaction. Multiple violation categories are detectable simultaneously within a single prompt — credentials, PHI, PII, resource locators, violent crimes, and child sexual exploitation can all be identified and blocked from one message. The Breakdown of Identifiers panel shows category frequency across a model's interactions, enabling policy tuning against real environment behavior.

Operational uses include incident triage, insider-threat investigation, audit evidence generation, user coaching, and policy tuning via override pattern analysis. Retention is tunable per policy.

---

### AI Operations, FinOps, and Context Graph

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/#ai-ops-context-graph

**FinOps with safety context.** AICenturion fuses LLM spend with safety and governance signals in a single per-model card showing prompts processed, tokens consumed, dollar cost, override count, user count, flagged users, and prompt-versus-response breakdowns of sensitive-data detections, AI safety triggers, and guardrail activations. A usage ring chart shows what percentage of a model's prompts and responses contain sensitive content.

A model with a 100% sensitive-prompt rate is a policy failure, not a cost optimization. Cost attribution runs per model, per account, and per user. Organizations re-routing traffic toward contracted models using this data commonly achieve 20-40% LLM cost savings.

**Telemetry ingestion.** AICenturion ingests AI interaction telemetry via SDK integration in customer applications, API gateway or proxy mode, agentless assessment connectors for SaaS AI, and passive network and traffic sensors for shadow AI discovery. This telemetry powers the FinOps view, activity audit log, Users At Risk panel, and the broader governance data model.

**Context graph.** The context graph is a lineage-derived data structure linking entities, users, data classes, and decisions. It enables surgical rollback on AI incidents — identifying exactly which downstream data and decisions were affected — and powers ontology-based compliance routing across stakeholders.

---

### MCP Security, Data Lineage, CI/CD Pipeline AI Discovery, and AI Risk

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/#mcp-security-data-lineage

#### MCP Guardian - Registry

MCP Guardian is purpose-built to secure the MCP surface most governance tools don't even see. The Model Context Protocol (MCP) is the emerging standard adopted by Anthropic, OpenAI, and every major agent framework. It is how AI agents reach beyond the model and into tools, databases, and business systems — and that is exactly why it needs a guardian. MCP Guardian registry is for what's connected, Lineage for what's reachable, and
Ontology for what it all means. Together, they turn the agent attack surface from a blind spot into a governed, auditable control plane.

#### MCP Guardian - Lineage and Data Lineage

Data lineage tracks every read and write flowing through AI systems — structural changes (schema additions, column changes) and semantic changes (classification shifts, ownership transfers). Each asset is annotated with RBAC and ABAC context and tied to the exact models that can query it.

Lineage delivers two critical capabilities:

**Fine-grained RBAC/ABAC enforcement** - Policies reference lineage-derived attributes rather than static tags, enabling context-aware access control at the data asset level.

**Surgical rollback** - When a model or agent misbehaves, the context graph identifies exactly which downstream data and decisions were affected, enabling targeted remediation rather than blanket system reversion. When an AI incident happens at 3 AM, the context graph is the difference between a surgical rollback and a full system restore.

Every read, write, and relationship captured in Lineage serves as defensible compliance evidence.

Data Asset Intelligence provides two views: Catalog view for a structured type-by-type inventory (tables, charts, dashboards, stored procedures, pipelines, ML models, search indexes) and Graph view visualizing the full relationship network — every asset, every link, every traversal path available to connected agents (e.g., 312 nodes, 307 edges in a representative enterprise deployment).

#### MCP Guardian - Ontology Mapping

Ontology Mapping is the semantic layer that transforms raw AI activity into structured compliance intelligence. Pre-built ontology libraries cover GDPR, HIPAA, PCI, and SOX. The framework is extensible with the customer's own GRC taxonomy and drives automated report routing across stakeholders. It binds four layers:

- Prompt content → data classification (PII, PHI, PCI, internal, public)
- Data classification → regulatory clause (GDPR Article 9, HIPAA §164.514, PCI-DSS Requirement 3)
- Regulatory clause → enterprise control (the exact control ID in the customer's GRC system)
- Control → user identity → business unit

A single violation is simultaneously reportable to the DPO as a GDPR event, to the CISO as a control failure, and to a line manager as a coaching trigger — with no manual correlation. The ontology is structured and auditable, not LLM-driven. It is a deterministic layer traceable clause by clause, control by control, by any auditor.

#### Shadow AI Discovery

AICenturion automatically detects AI models and services in use across the enterprise through network scanning, traffic analysis, and integration monitoring — no user self-reporting required. Discovered models surface with detection source, usage signals, and risk posture. In most enterprise deployments, the discovered list exceeds the approved model list during the first 30-90 days.

Two parallel inventories run at all times: **User Integrated** (the approved list — registered models with API keys and policies attached, subject to full governance enforcement) and **Discovered** (what is actually running, detected through network and traffic analysis). Everything present on the Discovered list and absent from User Integrated is shadow AI.

#### AI Bill of Materials (AIBOM) and CI/CD Pipeline Discovery

The AIBOM is a structured inventory of every component in an AI system: base models, fine-tuned layers, datasets, frameworks, plugins, dependencies, and the code repositories that wire them together. Modeled on SBOM, it addresses supply-chain opacity for AI the way SBOMs addressed it for software.

AIBOM maps discovered components against CWE identifiers and severity levels — for example, CWE-78 (OS command injection), CWE-79 (cross-site scripting), CWE-250 (execution with unnecessary privileges) surfaced across Dockerfiles and application code. Repository connectors cover GitHub, GitLab, Bitbucket, and Azure DevOps.

The Inventory section identifies every file in a repository carrying potential weaknesses. The SBOM column lists every package, version, source, and known vulnerability with analytical trend view and triage-ready detail. Findings export in CycloneDX or SPDX-compatible format for procurement, enterprise customers, and regulators. AIBOM is increasingly required in enterprise RFPs and vendor risk assessments.

---

### Red Teaming - Model and Application

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/

AICenturion's Red Team module runs adversarial test suites against AI models and deployed applications, probing for safety, security, and compliance failures before an attacker does. It replaces external red team engagements ($50,000-$250,000 per engagement, out of date on delivery) with continuous, framework-aligned testing on a customer-defined schedule, with stored audit-ready evidence. It is pen-testing for AI, run the same way security teams pen-test applications: on a schedule, against named frameworks, with evidence.

**Two target types:** Test a Model (direct API testing of base model behavior) and Test an Application (end-to-end against a deployed AI app with full context — system prompts, RAG data, tool access).

Results are scored Critical, High, Medium, Low, and Informational per session, with per-finding reproduction evidence. Multiple models run in parallel. Attack Success Rate (ASR) — the percentage of red team prompts that achieved the adversary's goal — is tracked over time to demonstrate posture improvement.

**Report sections:** Attack Methods (passed, failed, and success rate per technique), Brand (hallucination, overreliance, bias), Compliance and Legal (unauthorized contractual commitments and legal exposure with sensitivity ratings), Datasets (prompt injection via Meta's CyberSecEval dataset), Security and Access Control (Unicode tag-based instruction smuggling), and Framework Compliance (model status against every selected standard — NIST AI RMF, EU AI Act, CMMC, FedRAMP Rev 5, HIPAA, HPH CPGs, ISO 27001, ISO 27001:2022, ISO 27002, NIST CSF, NIST CSF 2.0, NIST SP 800-53 Rev 5, NIST SP 800-171 Rev 3, OFDSS, PCI DSS v4, SOC 2, and ISO 42001and DoD Ethical AI — with full pass/fail breakdown per framework).

---

### Compliance-Aligned Validation Checks

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/

Every validation check in AICenturion is tagged to a named compliance framework, enabling teams to select, test, and export evidence mapped directly to the control IDs auditors and regulators reference.

**Check library by family:**

- **AI Risk and Governance:** EU AI Act (15 checks), NIST AI RMF (19), ISO/IEC 42001 (30), EU GDPR (23), DoD AI Ethical Principles (25), Guardrails Evaluation (41), Harmful content (26), OWASP Agentic AI (22)
- **Foundational and Recommended:** Foundation (40), Recommended (39)
- **Use Cases and Techniques:** MCP (6), RAG (42), Minimal Test (2)
- **Safety and Security:** Data Leakage (4), Jailbreaking (4), Invalid Code (7), Code Exploits (5)

Named checks include Object-Level Authorization Bypass (OWASP API 1), Function-Level Authorization Bypass (OWASP API 5), RBAC Implementation, Model Context Protocol attacks, SQL Injection, and PII Protection Suite. Evidence exports in PDF, CSV, and JSON include run metadata, attack success rates, per-finding reproduction steps, remediation guidance, and control ID mappings.

---

### Compliance and Regulatory Coverage

**URL:** https://www.cytex.io/ai-security/aicenturion_cytex/

AICenturion ships check libraries and ontology mappings for: EU AI Act, NIST AI RMF, ISO/IEC 42001, EU GDPR, DoD AI Ethical Principles, OWASP API / LLM Top 10 / Agentic AI, HIPAA, FERPA, and PCI-DSS.

Compliance evidence is generated on demand. Customers report 60-80% reduction in time-to-evidence versus manual assembly. SIEM integrations cover Splunk, Microsoft Sentinel, Chronicle, and Sumo Logic, with generic webhook and CEF/LEEF export for all others. Ticketing integrations cover ServiceNow and Jira.

---

## Microsoft Copilot Assessment

Microsoft Copilot Assessment in AICenturion is a dedicated control assessment built specifically for the Copilot attack surface. It's the fastest way to turn a stalled Copilot rollout into a governed, defensible one.

AICenturion's Microsoft Copilot Assessment is a dedicated, agentless control assessment built specifically for the Copilot attack surface, evaluating 72 controls across five categories and scoring the environment against Microsoft's own best practices plus controls Microsoft Secure Score does not cover. No endpoint deployment or user disruption is required. The Copilot Assessment is available as a standalone SKU (typically deployed within two weeks) for organizations in Copilot pilot or expansion, with a path to the full AICenturion platform. Scope is configurable at tenant or organizational-unit level, with continuous re-scan as configurations change.

In a typical first assessment, 45 of 72 controls fail, producing a pass rate below the 40% threshold that defines a Poor posture. Failures concentrate in:

- **Apps** - 47 controls (31 typically failing) — protection against malicious apps and add-ins
- **Identity** - 17 controls (11 typically failing) — MFA, conditional access, privileged roles
- **Data** - 4 controls — sensitivity labels, encryption-at-rest policies
- **DLP Policies** - 3 controls — M365 DLP coverage for Copilot surfaces
- **Copilot** - 1 control — Copilot-specific configuration

Failing controls commonly surfaced include Defender for Office 365 ATP protection, external calendar sharing, Safe Documents scanning, and Zero-Hour Auto Purge. Each carries per-control remediation guidance.

**Distinction from Microsoft Secure Score:** Secure Score evaluates the M365 environment generally. AICenturion evaluates it specifically through the lens of Copilot's data access patterns and attack surface, including controls Secure Score does not evaluate.

---

## Compliance

- [Compliance Automation](https://www.cytex.io/compliance_automation_cytex/) - AI-assisted continuous compliance with automated evidence collection and remediation. Integrates regulatory requirements into daily operations with automated monitoring and reporting.
- [Audify - Compliance Monitoring](https://www.cytex.io/compliance_automation_cytex/audify_cytex/) - Continuous compliance monitoring that tracks regulatory alignment, generates audit-ready reports, and identifies compliance gaps in real time.
- [SOC Automation](https://www.cytex.io/soc_automation/) - Automated security operations workflows for faster detection, triage, and response.
- [Frameworks Supported] CMMC, FedRAMP Rev 5, HIPAA, HPH CPGs, ISO 27001, ISO 27001:2022, ISO 27002, NIST CSF, NIST CSF 2.0, NIST SP 800-53 Rev 5, NIST SP 800-171 Rev 3, OFDSS, PCI DSS v4, SOC 2, and ISO 42001.

## Cloud Security and Data Security

- [Cloud Security](https://www.cytex.io/cloudsecurity/) - CSPM and cloud workload protection across AWS, Azure, GCP, and SaaS environments.
- [Data Security Posture Management (DSPM)](https://www.cytex.io/dspm/) - Discovers, classifies, and protects sensitive data across cloud, on-prem, and hybrid environments. Secures AI agent data access, enforces organizational policies, and automates remediation for misconfigurations and over-permissions. Supports GDPR, HIPAA, and other regulatory frameworks.

## Risk and Supply Chain

- [Supply Chain Security (SBOM)](https://www.cytex.io/sbom/) - SBOM generation and SCAT analysis for identifying and mitigating software supply chain and AI model plugin vulnerabilities.
- [DevSecOps](https://www.cytex.io/devsecops/) - Security integrated into the development lifecycle for resilient code and rapid remediation.
- [Vendor Risk Management (TPRM)](https://www.cytex.io/vendor-risk-management/) - Third-party risk management with automated partner monitoring and change detection.

## Cybersecurity Solutions

- [Cybersecurity Platform](https://www.cytex.io/cybersecurity/) - Unified, next-gen cybersecurity with proactive threat management, network security, endpoint protection, phishing simulation, and cyber awareness training.

## For MSPs and MSSPs

- [For MSPs / MSSPs](https://www.cytex.io/for-msps/) - Tailored, scalable, multi-tenant security and compliance for managed service providers, including complimentary phishing simulation and MFA modules for enrolled partners.

## For Partners

- [Cytex Partner Program](https://www.cytex.io/cytex-partner-program/) - Channel partner program for resellers, technology partners, and service providers to integrate and co-sell Cytex solutions.

## Resources

- [Resources Hub](https://www.cytex.io/resources/) - Central library of Cytex industry insights, technical, and educational content.
  - **Tech Briefs** - Short articles on emerging cybersecurity threats, technology trends, and Cytex platform capabilities.
  - [Tech Brief: Microsoft 365 Copilot Vulnerabilities and the AI Governance Gaps](https://www.cytex.io/wp-content/uploads/2026/05/Microsoft-365-Copilot-Vulnerabilities-and-the-AI-Governance-Gaps.pdf) - Technical analysis of three Critical-severity information disclosure vulnerabilities disclosed in May 2026 affecting Microsoft 365 Copilot and Copilot Chat in Microsoft Edge: CVE-2026-26129 (CWE-138, Business Chat parsing flaw), CVE-2026-26164 (CWE-74, downstream injection), and CVE-2026-33111 (CWE-77, command injection in Edge). Covers the shared attack profile (AV:N/AC:L/PR:N/UI:N, high confidentiality impact), the AI-mediated disclosure attack chain, and a detailed regulatory mapping showing which controls these vulnerabilities implicate across ISO/IEC 42001, NIST SP 800-53 Rev 5, NIST AI RMF, HIPAA Security Rule, EU AI Act, SOC 2 Trust Services Criteria, and GDPR. Explains why Microsoft's cloud-side remediation closes the technical exposure but not the compliance evidence obligation, and maps the Cytex Unified Platform response: AICenturion Microsoft Copilot Assessment, Runtime Guardrails, Activity Audit, Ontology Mapping, Compliance Automation, and DSPM, to the control families involved.
  - **White Papers** - In-depth research on AI security, compliance frameworks, data supply chain, and unified security architecture.  
  - [White Paper: Unified Security Platforms vs. Point Solutions - The Post-Mythos Architectural Imperative](https://www.cytex.io/wp-content/uploads/2026/05/cytex-position-post-mythos.pdf) - Analyzes why point-solution security stacks fail under AI-speed threat conditions and why unified platforms integrating AI governance, continuous compliance, continuous vulnerability scanning, and AI-assisted automated remediation are the minimum viable architecture for post-Mythos defense. Covers the five structural deficiencies of fragmented architectures (inter-tool latency, data model fragmentation, compliance-as-snapshot, SOAR brittleness, alert fatigue), a four-requirement architectural framework (continuous observation, unified reasoning, automated decision and action, continuous compliance verification), TCO comparisons under threat acceleration, and a vendor-neutral evaluation framework for post-Mythos defensive readiness.
  - [White Paper: Mythos and the Collapse of Traditional Defensive Timelines](https://www.cytex.io/wp-content/uploads/2026/05/post-mythos-landscape-1.pdf) - Technical analysis of the frontier offensive AI model Mythos and its implications for enterprise vulnerability management, compliance frameworks, and defensive architecture. Documents Mythos's autonomous discovery of zero-day vulnerabilities across Windows, macOS, Linux, FreeBSD, OpenBSD, Chrome, Firefox, Safari, and Edge, including a 27-year-old OpenBSD kernel flaw and a 16-year-old FFmpeg vulnerability that survived five million fuzzing iterations. Covers the autonomous FreeBSD RCE exploit chain (8h 47m end-to-end), benchmark performance (100% Cybench, 83% CyberGym), the collapse of POA&M timelines from weeks to hours, gaps in FedRAMP, CMMC, ISO 27001, SOC 2, PCI DSS 4.0, and NIST CSF 2.0 frameworks, and recalibrated MTTD/MTTR targets for AI-speed threats.
  - **Secure with Cytex Series** - Scenario-based content showing how Cytex addresses specific risks, regulatory requirements, and industry use cases.
  - **Help Guides** - Product documentation, configuration walkthroughs, and best-practice references for Cytex platform users.

## Compliance Frameworks Supported

SOC 2 - NIST CSF - NIST 800-53 - NIST AI RMF - ISO 27001 - ISO 27001:2022 - ISO 27002 - NIST CSF 2.0 - NIST SP 800-171 Rev 3 - HPH CPGs - OFDSS - PCI DSS v4 - ISO 42001 - FedRAMP Rev 5 - GDPR - HIPAA - CMMC - SOC 2 - EU AI Act - MITRE ATLAS - OWASP Top 10 for LLM - CWE

## Company

- [About Us](https://www.cytex.io/about-us/) - Cytex, Inc. is a patented cybersecurity company combining AI and deep security expertise.
- [Pricing](https://www.cytex.io/pricing/) - Subscription tiers and platform packaging.
- [Contact Us](https://www.cytex.io/contact-us/) - Request a demo or speak with the Cytex team. Email: hello@cytex.io | Phone: 1-844-CYTEXAI (1-844-298-3924)
- [Privacy Policy](https://www.cytex.io/privacy-policy/) - How Cytex handles personal and customer data.
- [Terms of Use](https://www.cytex.io/terms-of-use/) - Terms governing the use of Cytex services.

## Target Audience

CISOs, compliance officers, IT and security leaders, MSPs/MSSPs, SMBs, mid-market and enterprise organizations, public sector and DIB contractors, and regulated industries (healthcare, finance, defense) seeking to consolidate security tooling, secure AI adoption, and automate compliance.

## Key Capabilities

- **Unified Security Rationalization** - Consolidates fragmented security, compliance, and GRC tools into one platform.
- **AI Governance and Shadow AI Discovery** - Automatically detects all AI models, applications, and agentic tools across the enterprise, including embedded and shadow AI.
- **Continuous Compliance** - Automates monitoring and reporting for NIST, ISO 27001, GDPR, HIPAA, CMMC, SOC 2, NIST AI RMF, EU AI Act, MITRE ATLAS, and OWASP Top 10 LLM.
- **Real-Time Risk Visibility** - Continuous threat, vulnerability, and risk identification across networks, IT, OT, and IoT environments.
- **AI-Powered Remediation** - LEO AI co-pilot generates POAMs, remediation code, presentations, and role-based security insights.
- **Data Security Posture Management** - Classifies and protects sensitive data (PII, PHI, secrets) across hybrid cloud environments with automated remediation.
- **Third-Party and Supply Chain Risk** - Ongoing vendor risk monitoring and SBOM-based software supply chain analysis.
- **MSP/MSSP Multi-Tenancy** - Purpose-built for service providers to centrally manage multiple client environments.

## Strategic Partners

Intel - NVIDIA Inception - Marsh - MIT Cyber Defense Clinic - NUARI - Pyxon - U.S. Army Cyber Command (ARCYBER)

## Industries Served

Financial services, healthcare, technology, government, critical infrastructure, retail, and any industry requiring enterprise-grade cybersecurity, AI governance, and regulatory compliance.

## Integrations

Over 100 integrated data partners including cloud platforms (AWS, Azure, Google Cloud), productivity suites (Microsoft 365, Google Workspace), communication tools, security services, and endpoint management solutions.

## Contact

- Email: hello@cytex.io
- Phone: 1-844-CYTEXAI (1-844-298-3924)
- Offices: Maryland (HQ) - Texas - New York
- Website: https://www.cytex.io
- Demo Request: hello@cytex.io

## Robots

Robots.txt: https://www.cytex.io/robots.txt

## Bot Access Policy

- **User-agent: gptbot** - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: claudebot** - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: google-extended** - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: perplexitybot** - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: neevabot** - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: youbot** - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: ccbot** (Common Crawl) - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: duckduckbot** (DuckDuckGo AI) - Allow-Training: yes | Allow-Retrieval: yes
- **User-agent: yandexbot** - Allow-Training: yes | Allow-Retrieval: yes
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