Powered by VIPRE AI  ·  Specialized AI Engines

The threats are AI. So is the defense.

VIPRE built dedicated AI and LLM reasoning engines to power our Threat Intel Platform — not a feature, a fabric. Each one purpose-trained on a different attack surface. All of them working together across your email, your endpoints, your data, and every AI tool your people use.

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70%

OF ENTERPRISES WHO HAVE ADOPTED AI

report concerns about AI bias and safety

$4.99M

AVERAGE DATA BREACH COST

average cost of a data breach incident in 2025

56%

OF ALL ATTACKS INVOLVE AI

attacks tied directly to AI generation and execution capabilities

Solutions

One AI Powered Threat Intel Platform. Four Dimensions of Attack Surfaces. Zero Gaps.

Attackers target email, endpoints, people, and the AI running inside your business. VIPRE covers all four under one AI Threat Intel platform that leverages and orchestrates purposely built AI experts, so we can make the best decision for each case

VIPRE AI Platform

VIPRE AI Platform at the Core.
Protection Across Every Surface.

Most security vendors added an “AI layer.” VIPRE built from the AI up.

VIPRE AI Platform is VIPRE’s core machine-learning and LLM reasoning platform. It doesn’t just classify threats — it reads intent, understands structure, reasons across context, and learns continuously from the full signal of 50,000+ organizations. VIPRE portfolio shares VIPRE AI Platform as its intelligence core, so a lesson learned stopping a BEC attack becomes a signal that sharpens endpoint detection, and a threat pattern flagged in inbox defense the same day improves training simulation.

Specialized engines. Each trained on a different problem. Sharing one threat fabric.

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01Intent AI & LLM Reasoning

Email Security — BEC / VEC · DLP · SafeSend

Email security that reads intent and stops data loss before it sends.

The Scenario
No link. No attachment. Just a wire-transfer request from a vendor you trust, but their account was compromised, and the attacker has been in the thread for weeks. Meanwhile, a quarterly forecast was pasted into the wrong reply, reworded just enough that no DLP rule matched. It sent anyway. VIPRE’s VIPRE AI Platform stops both because it reads intent and understands meaning, not just patterns.
The Engine

The Intent AI & LLM Reasoning engine powers email security end to end. It stops zero-payload BEC and VEC attacks by reasoning across the full thread reading tone, urgency, thread history, sender behavior, and financial trigger signals simultaneously. The VIPRE AI DLP Rules Engine runs in parallel, catching every variant of a sensitive phrase -reworded, paraphrased, reformatted, not just exact string matches.

Document upload similarity takes it further: NDAs, contracts and financial documents are detected by their structure and meaning, not their filename or word-for-word content. And SafeSend adds a final intelligent checkpoint – a context-aware prompt at the moment of send that helps users pause, review recipients, and apply DLP policy before anything leaves the organization.

What It Does
  • LLM reasoning across the full email thread – catches BEC, VEC, and thread hijacking with zero payload required
  • VIPRE AI DLP Rules Engine – catches every sensitive phrase variant: reworded, paraphrased, reformatted
  • Document similarity detection – NDAs and contracts caught by structure and meaning, not filename or exact text *
  • SafeSend – context-aware DLP checkpoint at the moment of send, before data leaves *
  • Layers on any gateway – Microsoft 365, Google Workspace, or existing email infrastructure

* Future Roadmap

Intent-based attacks with no payload now account for 68% of all BEC losses and standard DLP misses every reworded variant. This engine is built for both.

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02AI Assurance & Governance Engine

AI Models · Agents · COTS Apps — EU AI Act

Score every AI surface. Trust every decision.

The Scenario
The AI assistant your HR team started using six months ago was never on an approved vendor list. The model embedded in your hiring platform has never been tested for bias. The agent your IT team deployed to handle ticket routing makes decisions nobody fully understands and nobody has audited. The AI you didn’t approve is already in production. VIPRE tests it, scores it, and governs it before the regulator does.
The Engine

VIPRE’s AI Assurance engine adversarially tests every model, application, and autonomous agent across your environment – scoring each against 10 trust dimensions on a 0–1.0 scale with an A–F grade. The same framework applies whether you’re evaluating a foundation model, a fine-tuned internal tool, or an agentic workflow embedded in a COTS application.

Every finding maps automatically to the EU AI Act, NIST AI RMF, and NYC Local Law 144 — so your compliance output is audit-ready from day one. Board-ready report delivered in days, not quarters.

Every threat decision is auditable. No black boxes, no blind trust — our explainable AI shows exactly why each AI surface passed or failed.

10 Trust Dimensions — Scored 0–1.0, Graded A–F
  • SafetyToxicity, harmful output, jailbreak resistance
  • FairnessBias detection, four-fifths analysis across protected classes
  • AccuracyHallucination rate, factual consistency
  • PrivacyPII leakage, consent compliance, data minimization
  • TransparencyDocumentation completeness, model cards
  • RobustnessAdversarial prompt resistance, prompt injection
  • AccountabilityAudit trail completeness, decision logging
  • ExplainabilitySelf-explanation, reasoning legibility
  • ComplianceEU AI Act, NIST RMF, LL144 mapping
  • ReliabilityOutput consistency, drift detection
What It Covers
  • Autonomous agents: multi-step reasoning, tool calls, vendor agents embedded in COTS
  • COTS-embedded AI: AI features in Workday, ServiceNow, Einstein, and 230+ enterprise apps
  • Foundation models: GPT, Claude, Gemini, Llama, Databricks, and fine-tuned derivatives
  • 5 connection methods: Upload · Webhook · BYOK API · Red Team · MCP
Regulatory Deadline
RegulationIn EffectPenalty Exposure
EU AI Act August 2, 2026 Up to €35M or 7% of global revenue
NYC Local Law 144 In effect since 2023 $500–$1,500 per violation, per day
Workday Class-Action Precedent Ruled 2025 Vendors directly liable — 1.1B applications affected
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03Agentic AI Threat AdvisoryPartial roadmap

Security Awareness Training — Adaptive, Threat-Current

Security training built on today’s threats. Not last year’s.

The Scenario
The phishing simulation your team ran last quarter used a credential-harvesting template from 2023. The attack that hit your finance director last month was an AI-generated deepfake request, written in her manager’s voice, referencing a real deal she’d signed the previous week. The gap between what training teaches and what attackers do has never been wider. VIPRE’s Agentic AI Threat Advisory engine closes it — automatically.
The Engine

VIPRE’s security training platform uses an agentic AI engine that monitors the live threat landscape and generates simulation content, advisory briefs based on the specific attack types targeting your industry, your geography, and roles right now.

The agent doesn’t wait for a content team to write a new module. It generates threat-relevant scenarios from live intelligence, maps them to your user population and briefs your security team on what’s actually hitting your sector this week.

What It Does
  • AI-generated threat scenarios refreshed from current attack intelligence feeds
  • Agentic advisory summaries for security teams: what’s hitting your sector right now *
  • Role-aware content — finance trains against BEC, HR against deepfake impersonation, IT against credential phishing

Security awareness training built in — not a separate vendor, not a separate license.

* Future Roadmap

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04Shadow AI Detection & Data Loss ReasoningFuture Roadmap (Coming Soon)

Insider Risk — Unsanctioned AI & DLP Reasoning (Future Roadmap)

Your data left. No rule ever saw it go.

The Scenario
The NDA wasn’t copied. It was summarized into ChatGPT — a personal account, not the corporate one. The paragraph that went in wasn’t flagged as an exact match for anything on the DLP block list, because it was reworded before it was pasted. The file was never downloaded. No alert fired. Three days later, the terms appeared in a competitor’s draft. Pattern-matching DLP catches what it was told to look for. VIPRE’s reasoning engine catches the intent to exfiltrate — regardless of format.
The Engine

VIPRE’s Shadow AI and Data Loss engine uses structural similarity reasoning — not keyword matching — to understand what a document means, not just what it says. It catches NDA clauses reworded into paste events. It catches financial projections reformatted into new file types. And it watches every AI tool your people use — approved or not — auditing what data flows into it and enforcing policy before anything leaves the organization.

What It Does
  • Structural document similarity: catches NDAs and contracts by meaning, not filename or exact string
  • DLP phrase variant detection: catches any reworded version of a sensitive phrase across all apps
  • Shadow AI visibility: discovers every AI tool in use across the org — approved or not
  • Audit log of what data flows into unsanctioned AI tools: ChatGPT personal, Gemini, Claude, and more
  • Policy enforcement at the point of transfer: warn, block, or quarantine before data exits
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05Deep Link & URL AI Sandbox

Email & Web — Time-of-Click URL Analysis

The link was clean when it arrived. It wasn’t when they clicked.

The Scenario
The URL in the email pointed to a legitimate SharePoint document at 9 AM — when your gateway scanned it. By 11 AM, two hours after delivery and one hour after the user opened their inbox, the attacker had swapped the payload. The gateway had already approved it. The user clicked. Time-of-click protection with AI reasoning stops what time-of-delivery scanning misses entirely.
The Engine

VIPRE’s Deep Link AI Sandbox performs full dynamic analysis at the moment of click — not just at email delivery. Every URL is resolved, rendered in an isolated browser environment, and analyzed by an ML model that evaluates page structure, redirect chains, domain reputation, JavaScript behavior, and visual similarity to known phishing pages.

The AI layer catches cloaking, delayed redirects, geofenced payloads, and post-delivery swap attacks that static reputation lookups miss entirely. Every click is a fresh analysis.

What It Catches
  • Time-of-click analysis: every URL fully re-analyzed at the moment a user clicks — not at delivery
  • Full browser rendering in isolation: catches JavaScript-heavy phishing pages and client-side attacks
  • ML model evaluates redirect chains, domain behavior, and visual phishing similarity signals
  • URL cloaking, geofenced payloads, delayed redirects, and post-delivery payload swaps
  • Works across email, collaboration tools, and mobile environments
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06Deep Attachment AI Sandbox

Email & Endpoint — File-Based Threat Detection, Behavioral Analysis

The malware is hiding inside a file that looks completely clean.

The Scenario
The invoice arrived as a PDF. The PDF contained a macro. The macro was obfuscated in a way that static analysis had never encountered — written specifically to evade your existing sandbox. It detonated 48 hours after delivery, when the analyst who reviewed it had already moved on. Signature-based sandboxes catch yesterday’s malware. VIPRE’s Deep Attachment AI Sandbox catches what’s never existed before.
The Engine

VIPRE’s Deep Attachment engine combines ML-based static analysis with dynamic behavioral detonation in an AI-augmented sandbox environment. The ML layer classifies structural indicators — byte-level anomalies, entropy patterns, header irregularities — before execution. The dynamic layer watches what the file does when it runs: network calls, process spawning, registry modifications, memory injection.

An AI reasoning model then correlates both signal streams to produce a threat verdict with full explainability — not just a score, but a reason. So your analysts know what happened, and why.

Detonates the attachment. The image inside it. The QR code embedded in the image.

What It Catches
  • ML static pre-screening catches obfuscated and polymorphic threats before detonation
  • Dynamic behavioral sandbox detonates across multiple OS environments simultaneously
  • AI reasoning correlates static + behavioral signals into an explained verdict
  • Zero-day and never-before-seen file-based malware — no signature required
  • Full file type coverage: PDF, Office documents, archives, executables, scripts, images, QR codes, and mixed containers
The attack chain

Modern attacks target people, not firewalls.

Every step is designed to look legitimate. VIPRE’s VIPRE AI Platform breaks the chain at each stage — before money or data ever leaves.

  1. 1

    Target a person

    Attackers research a finance or executive user and map their relationships, open deals, and communication patterns.

    VIPRE: IES AI risk-scores high-value targets and monitors for targeting signals.

  2. 2

    Earn trust

    A compromised vendor or look-alike sender opens a believable email thread, sometimes over days or weeks.

    VIPRE: IES detects sender anomalies, thread impersonation, and trust-building patterns.

  3. 3

    Make the ask

    A wire change, a credential prompt, or a request for a sensitive file — timed to catch the user off guard.

    VIPRE: IES reads intent and blocks the request before the user acts.

  4. 4

    Exfiltrate

    Funds are wired, credentials are harvested, or sensitive data leaves the business — often irreversibly.

    VIPRE: Shadow AI & DLP holds the data in-org and audits every AI channel.

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About VIPRE

Trusted by 50,000+ organizations for 30+ years.

Why do the world’s most security-conscious organizations choose VIPRE?

VIPRE is the only detection platform combining email security, endpoint security, employee training, Outbound Email DLP, AI and Penetration Testing in the same stack. Total protection.

Purpose-built AI engines covering email intent reasoning, adaptive threat training, AI governance and assurance, attachment and QR sandboxing, link analysis, and Shadow AI detection — all under one unified threat intelligence fabric.

And because 30 years of security data makes the AI smarter, and the protection stronger, every single day.

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