Cornerstone Cyber
AI Security · Solution Brochure
Securing the AI Era

Protect every
way your business
touches AI.

From shadow chatbots to autonomous agents, AI is moving faster than traditional security can follow. Netskope One AI Security gives you a single platform to see, understand, and control your entire AI ecosystem — without slowing innovation down.

Netskope ONE Users SaaS AI LLMs Agents
A plain-language guide to the AI risks facing modern enterprises — and the products that solve them. Complex made simple.
72%
of enterprise users still reach genAI apps through personal accounts at work.
Netskope Threat Labs, 2025
01 / 08
The Challenge

A dual mandate: unlock AI, defend against it.

Boards are telling IT leaders to embrace AI and cut costs and act as gatekeepers against data leaks — all at once. The result is a constant tension between moving fast and staying safe. Getting it right starts with understanding exactly where the risk lives.

Disrupt

Enable innovation

Let teams experiment, adopt and build with AI to drive real, measurable business value — fast.

Defend

Control the risk

Protect data, reputation and compliance against leaks, misuse and AI-native attacks — without blocking progress.

Five stages of AI adoption — five new risks
1
Experimentation Shadow AI
Employees paste sensitive data into personal chatbots that security teams can't see or govern.
2
Embedded AI in SaaS Silent data sharing
Trusted apps switch on AI features by default — an AI notetaker quietly records and stores company-confidential information.
3
Managed AI apps Internal leakage
An over-permissioned corporate AI surfaces files a user was never meant to access — leaking data inside the org.
4
Private AI apps Model weakness
Custom and open-source models inherit vulnerabilities — prompt injection, jailbreaks, biased or harmful output.
5
Autonomous agents Non-human blind spot
Agents act over APIs and MCP, machine-to-machine, bypassing human-centric security and risking data exfiltration.
Every organisation sits somewhere on this curve — usually on several rungs at once. 02 / 08
State of AI Security · 2026

Adoption is racing. Governance isn't keeping up.

A survey of 1,253 security professionals found the same pattern almost everywhere: organisations are deploying AI at production speed on a security foundation that barely exists. The good news — the gaps are now measurable, which means they're fixable.

Deploying AI tools
73%
Governing them in real time
7%
66pt
structural gap between using AI and controlling it
94%
Flying blind
lack complete visibility into AI usage. Only 6% see the full picture.
88%
Can't tell who's who
cannot distinguish a personal ChatGPT from the corporate one.
92%
DLP outsmarted
have no confirmed way to catch sensitive data once AI rewrites it.
91%
Agents unstoppable
can't stop a risky AI action before it executes — only see it in the logs.
90%
Spending more
increased AI security budgets this year — yet 29% feel less secure.
37%
Already bitten
have had an AI tool cause a real operational issue in the past year.
Source: Cybersecurity Insiders, 2026 AI Risk and Readiness Report (survey of 1,253 security professionals)
1
The problem isn't money — it's architecture. Budgets are up across the board, yet confidence is falling. Adding more of a pre-AI security stack buys more of what already fails against AI.
2
Every gap compounds the next. Weak visibility undermines DLP; ungoverned agents bypass access controls. Close the foundation — visibility — and the rest become solvable.
More budget hasn't closed the gap — because legacy tools were built for a pre-AI world. 03 / 08
Why It's Hard

The tools you trust weren't built for AI.

AI doesn't just add new apps — it adds new behaviours. Legacy proxies and firewalls can't read intent inside a prompt, can't see machine-to-machine agent traffic, and can't tell a safe AI conversation from a dangerous one. Three gaps stand out.

You can't secure what you can't see

Unmanaged tools, personal accounts and AI features quietly embedded in everyday SaaS sit outside the security team's view — leaving data exposure invisible until it's already happened.

88% can't tell a personal AI account from a corporate one — Cybersecurity Insiders, 2026

New threats traditional tools miss

Prompt injection, jailbreaks and manipulated responses are AI-native attacks. A firewall sees an allowed connection; it has no idea the prompt inside is trying to trick the model into leaking secrets.

Only 23% enforce AI security inline, at the point of action — Cybersecurity Insiders, 2026

Agents act without oversight

Autonomous agents communicate machine-to-machine over APIs and the Model Context Protocol. Without a checkpoint, they create risk of credential leaks, tool poisoning and unauthorised data exfiltration.

65% say zero trust controls can't secure non-human identities — Cybersecurity Insiders, 2026
The "Transformation Test": why old DLP goes blind
Ask AI to rewrite a sensitive document and pattern-matching tools lose the trail — the meaning survives, the fingerprint doesn't.
Original — DLP catches it
"Launch date for Project Titan is March 3. Budget $4.2M, codename Titan."
✓ Keywords & patterns match → blocked
AI rewrites
"as a blog post"
Rewritten — DLP misses it
"Our upcoming strategic initiative kicks off early spring with a multi-million investment."
✗ No pattern match → sails straight through
92%
lack confirmed semantic detection. Pattern-based DLP matches character strings; AI transforms meaning while keeping the secret intact. The fix is inspection that reads intent, not just keywords.
Source: Cybersecurity Insiders, 2026 AI Risk and Readiness Report. 04 / 08
The Solution

One checkpoint in the path of every AI conversation.

Think of Netskope One as a smart checkpoint sitting between the people and agents using AI and the models they talk to. Every prompt and response passes through — so it can be seen, inspected and controlled in real time.

How the pieces fit together
Users & Agents
Employees
AI-powered apps
Autonomous agents
AI Models & LLMs
Public genAI SaaS
Privately hosted LLMs
Custom & open models
Netskope One · Inspection & Control
GenAI App Security
See & control every AI app — sanctioned to shadow
AI Guardrails
Block misuse, attacks & unsafe content in real time
AI Gateway
Govern app-to-LLM API calls & authenticate agents
Agentic Broker
Secure MCP & agent-to-tool traffic
Powered by the Zero Trust Engine with integrated DLP & Threat Protection
AI Red Teaming stress-tests private models before they ever reach production
Inbound — prompts & requests Outbound — responses & data
Available stand-alone or as connected capabilities — secure the entire AI ecosystem, end to end. 05 / 08
The Products · Part 1

Four products in the live AI traffic path.

Each one maps directly to a risk on the adoption curve — and they share a single platform, console and policy engine.

Discover & Control

GenAI App Security

Solves: shadow AI and risky SaaS AI features no one approved.
Gives complete visibility across personal, corporate, sanctioned and shadow AI — then lets you allow, restrict or block each one.
Cloud Confidence Index of 85,000+ apps
Real-time access control & user coaching
Out-of-band data protection & posture mgmt
Defend in Real Time

AI Guardrails

Solves: prompt injection, jailbreaks, harmful or copyrighted output.
A runtime defense layer that inspects every prompt and response, for both human and agent interactions.
Blocks prompt injection & jailbreak attempts
Filters unsafe content; stops PII & code leaks
Maps to MITRE ATLAS & OWASP Top 10 for LLMs
Govern API Traffic

AI Gateway

Solves: app-to-LLM API calls that bypass traditional perimeters.
A lightweight gateway that centralises authentication and traffic management for the APIs feeding your AI apps.
One control point for OpenAI, Gemini & Claude
Token-based agent authentication
Rate limiting & searchable API audit logs
Secure the Agents

Agentic Broker

Solves: agents acting over MCP & APIs in a non-human blind spot.
Brings unified visibility and control to MCP traffic between agents, tools and data sources.
Decodes & risk-scores public MCP servers
Applies DLP to agent interactions
Full audit log of every tool call & event
Buy one, several, or all — each product runs stand-alone and strengthens the others. 06 / 08
The Products · Part 2

Test before you trust — then prove it works.

Harden Private Models

AI Red Teaming

Solves: moving from SaaS to private models opens a critical, untested security gap.

Runs 18,000+ automated adversarial simulations against your private models — built right into CI/CD pipelines — to catch prompt injections, jailbreaks and data-leakage flaws before they ever reach your users. It pairs with AI Guardrails to harden prompts from build to runtime.

Launch attack probes → Test Console LLM TEST ENGINE ← Vulnerability reporting
Every risk has a matching control
The risk
The Netskope answer
Shadow AI & embedded SaaS features
GenAI App Security
Prompt injection, jailbreaks, unsafe output
AI Guardrails
Unsecured app-to-LLM API calls
AI Gateway
Autonomous agents & MCP blind spots
Agentic Broker
Weak, untested private models
AI Red Teaming
85k+
apps risk-scored in the Cloud Confidence Index
18k+
adversarial scenarios for red teaming
1
unified platform for users & agents
0
trade-offs in speed or experience
One platform, one policy engine — secure users, apps, models and agents together. 07 / 08
Where Do You Stand?

From reactive to adaptive — find your weakest link.

Read down each row and find the description that matches you today. Your lowest row is your most likely point of failure — and where Netskope can help first. The goal is to move every domain rightward, to real-time, adaptive control.

AI Security Domain
Reactive
Managed
Adaptive ✓
Governance
Policies on paper, enforced inconsistently.
Enforced for managed tools; shadow AI ungoverned.
Policy embedded in technical controls, real-time.
Visibility
Partial or none; can't tell personal from corporate.
Activity-level across managed SaaS & APIs.
Real-time across all AI — including agents & M2M.
Data Protection
Pattern-based controls fail under AI rewriting.
DLP extended to AI chat & prompts; semantic in pilot.
Semantic inspection across all AI data flows.
Access & Execution
Post-execution only; honor-system policy.
Inline for humans; agent actions logged, not blocked.
Pre-execution enforcement, human and non-human.
Detection & Response
Log-based; no AI-specific detection logic.
Rules for known misuse; manual containment.
Continuous monitoring, automated containment.
Architecture
Fragmented — controls siloed across consoles.
Integrated for managed SaaS; gaps in agent traffic.
Unified framework, durable under scale.
Most organisations today →
Where Netskope One takes you

Say yes to the AI advantage.

Wherever you are on the curve, Netskope One moves every domain toward adaptive — securing your entire AI ecosystem without trade-offs in speed or experience.

Request a demo →
Maturity model adapted from Cybersecurity Insiders, 2026 · ©2026 Netskope, Inc. · netskope.com 08 / 08