Defending the AI-Powered Enterprise
Multi‑Layered Ransomware Protection for the AI Era
AI is transforming how organizations work and how adversaries attack.
Morphisec’s Adaptive AI Defense preemptively stops AI-driven ransomware and autonomous threats before execution.
Integrating with and fortifying EDR and XDR solutions, Morphisec delivers ransomware-free assurance and cyber adaptive resilience at scale.
The Threat Landscape Has Shifted.
Detection and Response Cannot Keep Up With AI-Driven Attacks
89% ↑
in AI‑enabled adversary operations
CrowdStrike 2026
27 seconds
the fastest recorded intrusion, faster than any human team can stop
Industry reporting
5% → 50%
of security spend moving to Preemptive Defense
Gartner 2025
Gartner figure cited under Morphisec’s approved Gartner usage. See the full Gartner disclaimer below.
The Category
The AI security gap is three gaps
wearing one coat.
Generative AI has collapsed attack timelines from hours to seconds. At the same time, employees are adopting AI tools that read source code, touch cloud repositories, and store credentials and tokens. Firewalls, identity, and EDR were built for people and devices. Not to govern what AI can reach or execute.
The visibility gap
No reliable way to enumerate every AI tool and agent on an endpoint, or to tell authorised from unauthorised use. Network and browser tools only see what routes through them.
The control gap
Even once AI is identified, there is no runtime enforcement defining what it may do. An acceptable-use policy nobody can enforce is a document, not a control.
The prevention gap
Detection is reactive, and AI acts at machine speed. By the time an alert fires, the agent has finished. The control point has to move upstream of execution.
The AI Hub
Where to go next
Definition
Shadow AI
Shadow AI is unsanctioned AI used outside IT oversight, assistants, desktop apps, CLI agents, browser extensions, and local large language models that touch files and credentials directly on the device.
It is less a policy failure than a visibility failure. Staff paste confidential data into assistants. Engineers install coding agents in the IDE. Someone runs Ollama on a laptop and points it at a folder. None of it routes through a proxy, so none of it appears in a network log.
The tools most enterprises expect to catch this, SASE, CASB, browser extensions, DLP, are structurally incapable of it. They see routed traffic and the browser tab. A local model reading files on disk produces neither.
You cannot govern what you cannot see. Discovery is not step one of AI governance. It is AI governance, until it’s done.
Definition
Compromised AI
Shadow AI is unapproved AI. Compromised AI is approved AI, turned against you.
An enterprise agent runs with broad permissions. That is the point of it. An attacker hijacks it through a poisoned prompt or a supply-chain attack, and the malicious commands inherit that legitimate trust.
To a firewall, an identity provider, or an EDR, the behaviour looks authorised, because in every credential sense, it is. The agent is who it says it is. It simply wants something it shouldn’t.
Shadow AI is a discovery problem. Compromised AI is a runtime-governance problem. Most enterprises have both, and the second one does not go away when you finish solving the first.
The Core Idea
Nobody can block prompt injection.
So stop trying to.
Prompt injection is unsolved for a structural reason: the malicious instruction and the legitimate instruction arrive through the same channel, in the same format. Filters and classifiers raise the cost of an attack. They do not eliminate it. Any vendor claiming to “block prompt injection” is overstating what the prompt layer can do: including, if we were less careful, us.
The durable answer is to assume the prompt layer can be lost, and to enforce policy one layer down.
| Dimension | The prompt layer | The execution layer |
|---|---|---|
| What it inspects | What goes into a model and what comes out | The system call an agent’s decision becomes: a file access, a process launch, a data transfer |
| Prompt injection | Can be defeated. The payload arrives through a legitimate channel | Cannot be prompt-injected. Even when injection succeeds, the resulting action is still caught |
| Privacy | Must inspect prompts and user content | No prompt capture, no content interception, behaviour only |
| Resilience | Depends on network visibility and connectors; breaks on vendor UI changes | Local; works offline; no signatures to maintain |
| What it evidences | What the agent said, or was asked | What actually executed on the device |
Prompt-layer guardrails remain valuable, and your EDR remains essential. The execution layer is the one that cannot be talked out of its policy.
The Standard
AIUC-1: the “SOC 2 for AI agents”
AIUC-1 is an independent certification standard for AI agents, issued by The Artificial Intelligence Underwriting Company. It defines 51 requirements and roughly ~130 controls across six pillars, Data & Privacy · Security · Safety · Reliability · Accountability · Society, verified through third-party audits and adversarial testing. Certificates are valid for 12 months; technical controls are re-tested at least quarterly; the standard is refreshed every quarter. It maps to EU AI Act, NIST AI RMF, ISO 42001, MITRE ATLAS, OWASP agentic security lists.
Morphisec Threat Labs
From trusted integration
to silent breach.
Morphisec Threat Research documented a new attack class that turns the Model Context Protocol trust model against AI coding assistants. A malicious npm package, registered as an MCP server, reaches full credential exfiltration in under 90 seconds, with no binary ever written to disk.
!Exposure. The payload fires on the tools/list handshake, before a user types a single prompt.
!Evasion. A signed-binary chain stayed silent across five independent EDR, DLP, and CASB stacks.
✓ Prevention, intercepted at the memory layer, before the first byte leaves the host.
MCP connectors are software your AI agents execute. And almost nobody inventories them.
The Morphisec AI Hub
One Platform. Five AI-Driven Capabilities. Zero Ransomware Tolerance.
The Morphisec AI Hub expands the Anti-Ransomware Assurance Suite into the AI era with Adaptive AI Defense at its core.
Adaptive AI Defense leverages AI and telemetry insights and Automated Moving Target Defense (AMTD) to transform raw data into decisive preventive action – from shadow AI discovery to exposure management to governance to policy enforcement – powered by automated actions and real-time AI assistants.
Designed to work seamlessly alongside any EDR/XDR solution, the AI Hub creates a preemptive defense fabric that eliminates ransomware impact before execution— delivering cyber adaptive resilience at machine speed.
Adaptive AI Defense
Preemptive Ransomware Protection. Instant Ransomware Prevention.
Morphisec Adaptive AI Defense preemptively stops AI-driven ransomware and autonomous threats before execution through AMTD runtime randomization. It neutralizes AI-generated malware, compromised agents, and zero-day exploits without relying on signatures, behavioral rules, or false positives.
- Blocks and Disrupts AI attacks at machine speed – with zero response delay.
- Works seamlessly alongside EDR and XDR solutions to close detection and response gaps.
- Core layer of Morphisec’s Anti-Ransomware Assurance Suite and Preemptive Cyber Defense architecture.
AI Usage Control (AIUC)
See Every AI. Control Every Action.
AI Usage Control (AIUC) discovers and governs every AI tool, connector, and agent running on endpoints – including unapproved shadow AI like GitHub Copilot, Cursor, and ChatGPT extensions – before they can misuse data or privileges.
- Visibility: Provides real-time inventory of all AI agents and connectors.
- Prevention: Blocks prompt injection, rogue automation, and agent exfiltration pre-execution.
- Compliance: Aligns with EU AI Act, ISO 42001, and SOC 2 requirements.
- Efficiency: Lightweight (<1% CPU) and deploys alongside existing EDR/XDR solutions.
AI Command Dashboard
From Insight to Action – Unified Command for AI-Era Defense.
The AI Command Dashboard aggregates signals from Adaptive AI Defense, AMTD runtime protection, and EDR/XDR integrations to automate remediation and reduce SOC response cycles.
MVP Logic Pillars:
- System Health: Monitors agent integrity and runtime performance for continuous resilience.
- Lateral Movement: Flags rogue AI processes and RMM tool abuse as pre-ransomware indicators.
- Active Exploitability: Prioritizes EPSS > 90% or CISA KEV alerts for actionable responses.
- Collaboration: Integrates with tools like Slack and Jira to accelerate tierless remediation.
AI Exposure Assistant
From Data Overload to Prioritized Clarity.
AI Exposure Assistant applies LLM analytics and AMTD signals to rank vulnerabilities by exploitability and business risk – closing gaps before they are exploited.
- Precision: Combines CVSS, EPSS, and AI context for precise risk prioritization.
- Efficiency: Reduces patch timelines and manual overhead.
- Alignment: Integrates with Adaptive Exposure Management and EDR/XDR risk insights for continuous remediation.
AI Incident Assistant
From Detection to Decision — Instantly.
AI Incident Assistant transforms prevented-attack telemetry into plain-language incident summaries with prescribed next steps. SOC teams save time and gain Tier 3 insight at Tier 1 speed.
- Speed: Cuts triage time by up to 90%. Allows Tier 1 Security Analysts to operate faster than Tier 3 skill and speed.
- Clarity: Correlates telemetry into root-cause reports for faster containment.
- Continuity: Maintains context across analyst handoffs and incident phases.
AI MCP Supply Chain
From Trusted Integration to Silent Breach
Morphisec Threat Research documented a new attack class that turns the Model Context Protocol trust model against AI coding assistants. A malicious npm package registered as an MCP server reaches full credential exfiltration in under 90 seconds — with no binary ever written to disk.
- Exposure: Payload fires on the tools/list handshake, before a user types a prompt.
- Evasion: A signed-binary chain stays silent across five independent EDR, DLP, and CASB stacks.
- Prevention: AMTD intercepts at the memory layer, before the first byte leaves the host.
Preemptive Ransomware Protection. Instant Ransomware Prevention.
Morphisec Adaptive AI Defense preemptively stops AI-driven ransomware and autonomous threats before execution through AMTD runtime randomization. It neutralizes AI-generated malware, compromised agents, and zero-day exploits without relying on signatures, behavioral rules, or false positives.
- Blocks and Disrupts AI attacks at machine speed – with zero response delay.
- Works seamlessly alongside EDR and XDR solutions to close detection and response gaps.
- Core layer of Morphisec’s Anti-Ransomware Assurance Suite and Preemptive Cyber Defense architecture.
See Every AI. Control Every Action.
AI Usage Control (AIUC) discovers and governs every AI tool, connector, and agent running on endpoints – including unapproved shadow AI like GitHub Copilot, Cursor, and ChatGPT extensions – before they can misuse data or privileges.
- Visibility: Provides real-time inventory of all AI agents and connectors.
- Prevention: Blocks prompt injection, rogue automation, and agent exfiltration pre-execution.
- Compliance: Aligns with EU AI Act, ISO 42001, and SOC 2 requirements.
- Efficiency: Lightweight (<1% CPU) and deploys alongside existing EDR/XDR solutions.
From Insight to Action – Unified Command for AI-Era Defense.
The AI Command Dashboard aggregates signals from Adaptive AI Defense, AMTD runtime protection, and EDR/XDR integrations to automate remediation and reduce SOC response cycles.
MVP Logic Pillars:
- System Health: Monitors agent integrity and runtime performance for continuous resilience.
- Lateral Movement: Flags rogue AI processes and RMM tool abuse as pre-ransomware indicators.
- Active Exploitability: Prioritizes EPSS > 90% or CISA KEV alerts for actionable responses.
- Collaboration: Integrates with tools like Slack and Jira to accelerate tierless remediation.
From Data Overload to Prioritized Clarity.
AI Exposure Assistant applies LLM analytics and AMTD signals to rank vulnerabilities by exploitability and business risk – closing gaps before they are exploited.
- Precision: Combines CVSS, EPSS, and AI context for precise risk prioritization.
- Efficiency: Reduces patch timelines and manual overhead.
- Alignment: Integrates with Adaptive Exposure Management and EDR/XDR risk insights for continuous remediation.
From Detection to Decision — Instantly.
AI Incident Assistant transforms prevented-attack telemetry into plain-language incident summaries with prescribed next steps. SOC teams save time and gain Tier 3 insight at Tier 1 speed.
- Speed: Cuts triage time by up to 90%. Allows Tier 1 Security Analysts to operate faster than Tier 3 skill and speed.
- Clarity: Correlates telemetry into root-cause reports for faster containment.
- Continuity: Maintains context across analyst handoffs and incident phases.
From Trusted Integration to Silent Breach
Morphisec Threat Research documented a new attack class that turns the Model Context Protocol trust model against AI coding assistants. A malicious npm package registered as an MCP server reaches full credential exfiltration in under 90 seconds — with no binary ever written to disk.
- Exposure: Payload fires on the tools/list handshake, before a user types a prompt.
- Evasion: A signed-binary chain stays silent across five independent EDR, DLP, and CASB stacks.
- Prevention: AMTD intercepts at the memory layer, before the first byte leaves the host.
What the Analysts Say About the Category
AI Usage Control is becoming
a named control category.
“Organizations must pilot AI Usage Controls as part of AI TRiSM and trust management. Endpoint-level detection of local AI agents and Model Context Protocol connectors is critical for reducing Shadow AI risk.”
Innovation Insight for AI Usage Control (2025) and Solution Criteria for AI Usage Control (2026)
Gartner is describing the control category, not any one vendor. We read it as a straightforward statement of where endpoint AI governance is heading: you cannot govern local AI agents and MCP connectors from the network, so the control has to sit on the endpoint. That is the position Morphisec AI Usage Control occupies. And the mapping to AIUC-1 is how we show our work.
GARTNER is a registered trademark and service mark of Gartner, Inc. And/or its affiliates in the U.S. And internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Already in the Wild
These AI attacks are real.
Morphisec stops every one.
Polymorphic AI ransomware, weaponized AI CLIs, and autonomous extortion agents are operating today. Select an attack to see how prevention-first defense neutralizes it.
How Morphisec stops it
Ollama is auto-flagged as an AI agent. A file-write spike plus an abnormal child-process spawn rate raises a Critical alert, and the local LLM is blocked by policy, before encryption begins. No signature required.
How Morphisec stops it
Day-1 Guardrails block access to SSH keys and credential directories, no machine-learning baseline required. The weaponized CLI is denied the moment it reaches for secrets.
How Morphisec stops it
The AI agent process is identified instantly. A data-volume and sensitive-directory anomaly raises a High alert, and egress policy blocks unapproved LLM services before data leaves.
How Morphisec stops it
Morphisec detects the MCP connector’s DELETE access pre-emptively, blocks the AI from backup locations, and flags mass deletion as critical, stopping the action before it completes.
Frequently Asked Questions
AI security, answered
Concept and category questions. For product, packaging, and OS coverage, see the platform page.
What is shadow AI?
What is compromised AI, and how is it different from shadow AI?
Shadow AI is unapproved AI. Compromised AI is approved AI that has been turned against you. An enterprise agent runs with broad permissions; an attacker hijacks it through a poisoned prompt or a supply-chain attack, and the malicious commands inherit that legitimate trust. To a firewall, an identity provider, or an EDR, the behaviour looks authorised, because, in every credential sense, it is. Shadow AI is a discovery problem. Compromised AI is a runtime-governance problem. Most enterprises have both.
What is the execution layer in AI agent security?
Most AI security tools work at the prompt layer, inspecting what goes into a model and what comes out, using filters, guardrails, and classifiers. That work is necessary, but prompt injection remains an unsolved problem: a malicious instruction arrives through the same channel as legitimate ones, so a compromised agent can pass every prompt-layer check. The execution layer is different. It sits where an agent’s decision becomes a real action on the device. A file access, a process launch, a data transfer. Policy enforced at that point evaluates the actual system call rather than the model’s reasoning. The execution layer cannot be prompt-injected: even when prompt injection succeeds, the resulting action is still caught.
Can any security tool block prompt injection?
No. And any vendor claiming otherwise is overstating what the prompt layer can do. Prompt injection is unsolved precisely because the malicious instruction and the legitimate instruction arrive through the same channel, in the same format. Filters and classifiers raise the cost of an attack; they do not eliminate it. The durable answer is not to try to win at the prompt layer but to assume it can be lost, and to enforce policy one layer down, at execution, where an agent’s intent becomes a real system call. Morphisec does not claim to block prompt injection. It catches what the injection tries to do.
What is AIUC-1?
AIUC-1 is an independent certification standard for AI agents, often described as “SOC 2 for AI agents.” Launched in 2025, it defines 51 requirements and roughly 130 controls across six pillars: Data & Privacy, Security, Safety, Reliability, Accountability, and Society. It is issued by The Artificial Intelligence Underwriting Company, was developed with input from more than 100 Fortune 500 CISOs, and maps to frameworks security teams already track: including the EU AI Act, NIST AI RMF, ISO 42001, MITRE ATLAS, and the OWASP agentic security lists. Certificates are valid for 12 months and technical controls are re-tested at least quarterly.
Our AI vendors are AIUC-1 certified. Doesn’t that cover us?
Certification is a good signal. It means the agent you bought was independently tested, within the scope of its audit. But it covers only that vendor’s agent. It says nothing about the dozens of other AI tools on your endpoints: the copilots and assistants employees adopt on their own, local LLMs like Ollama, coding agents inside IDEs, browser AI, and MCP connectors nobody certified. And a certified agent can still be hijacked at runtime through prompt injection or a poisoned supply chain. Certification tells you the agent was tested; it does not govern what AI actually does on your devices day to day.
Is Morphisec AIUC-1 certified?
No. AIUC-1 certification applies to the AI agent products that vendors sell, customer-facing chatbots, voice agents, and automation agents. Morphisec plays a different position: it is the enterprise-side control that governs all AI agents and tools running on your endpoints, certified or not. Morphisec is not affiliated with, endorsed by, or certified under AIUC-1. What Morphisec provides is the mapping and the evidence: Morphisec AI Usage Control maps to AIUC-1 controls across all six pillars, and is the direct control on the nine that land at the execution layer.
Does Morphisec read employee AI prompts?
No. Morphisec governs AI by behavior at the execution layer, not by inspecting prompt content. Prompt interception is a losing battle, traffic is encrypted, browser extensions break with every vendor UI change, and desktop apps use proprietary wrappers. And reading employee prompts creates its own privacy and compliance exposure under GDPR, CCPA, and HIPAA. All analysis runs locally on the endpoint; no prompts, telemetry, or behavioral data leave the machine.
What is an MCP connector, and why is it a security concern?
The Model Context Protocol (MCP) is how AI agents connect to external tools and data sources. It is a trust model: the agent trusts what the connector advertises. Morphisec Threat Research documented an attack class that turns that trust against the agent. A malicious npm package registered as an MCP server reaches full credential exfiltration in under 90 seconds, with no binary ever written to disk. The payload fires on the tools/list handshake, before a user types a single prompt, and the signed-binary chain stayed silent across five independent EDR, DLP, and CASB stacks. MCP connectors are software your AI agents execute, and almost nobody inventories them.
Why can’t my firewall, EDR, or CASB govern AI?
Because they were built for people and devices, not for AI. Network, SASE, CASB, and browser tools only see routed traffic or the browser tab, so they are blind to local LLMs, CLI agents, and IDE-embedded AI on the device. EDR watches processes generically. It can tell you a process ran, but not that the process was an unsanctioned AI agent reaching for credentials on behalf of a hijacked prompt. The gap is three-fold: a visibility gap (you cannot enumerate the AI), a control gap (no runtime enforcement of what AI may do), and a prevention gap (detection fires after the AI has already acted).
“Morphisec prevents attacks from actually happening, it gives us an early warning sign… and that lets me make informed, intelligent decisions.”
Richard Rushing, CISO, Motorola
Risk Reversal
The 100% Ransomware-Free Guarantee
- 100% money-back assurance, full reimbursement of subscription fees if a ransomware breach occurs on a protected endpoint.
- A dedicated Morphisec Incident Response team for rapid containment, forensic investigation, and remediation.
Prevent the Unseen
See the AI running
on your endpoints.
Most customers see their full AI inventory. Every agent, copilot, local LLM, and MCP connector, within a day of turning discovery on.
Live at Black Hat USA 2026, August 1 to 6, Las Vegas
AIUC-1 is a certification standard issued by The Artificial Intelligence Underwriting Company. Morphisec is not affiliated with, endorsed by, or certified under AIUC-1. Morphisec AI Usage Control maps to AIUC-1 control categories and provides endpoint-runtime evidence supporting them; this is a capability mapping, not a certification. Framework alignment describes the evidence and controls Morphisec contributes to your compliance program; it does not itself constitute compliance or certification of your organization.
