AI Security Assessment & Remediation

A comprehensive evaluation of your organization's protection against OWASP Top 10 for LLM Applications and MITRE ATLAS threats — powered by the Fortinet AI Security Fabric, deployed and managed by AirGap Labs.

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Assessment Phases


1) AI-Powered Threat Assessment

Map exposure across OWASP LLM Top 10 & MITRE ATLAS2

2) Risk Analysis — Exposure Score

Quantified score across 5 fabric dimensions3

3) Remediation Plan

Layer-by-layer Fortinet roadmap to close every gap

4) Fortinet AI Fabric Alignment

Every layer of the Fortinet fabric is purpose-built to stop a specific class of OWASP LLM or MITRE ATLAS threat. AirGap Labs ensures each layer is correctly deployed, integrated, and tuned.

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Your Full Assessment Package

Every engagement delivers a complete, actionable security picture — not a generic report, but a precise roadmap built for your specific Fortinet environment.

  • ✓Full OWASP LLM Top 10 exposure report with per-risk coverage status

  • ✓MITRE ATLAS technique coverage map across all attack phases

  • ✓Prioritized risk score across all five Fortinet fabric dimensions

  • ✓Layer-by-layer remediation roadmap with quick wins and long-term additions

  • ✓Fortinet fabric deployment & management plan tailored to your environment

  • ✓Engineering walkthrough with AirGap Labs team — not a slide deck, a working session
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Phase 1a · OWASP LLM Top 10 Assessment

Coverage Mapping — Every Risk, Every Layer

Every OWASP LLM risk is mapped to the specific Fortinet fabric layer that blocks it. Your assessment reveals which risks are covered, partially covered, or unmitigated.

  • LLM01 Prompt Injection

    Direct and indirect prompt injection attacks targeting your LLM inputs and outputs.
    ▸ Blocked by FortiWeb & FortiAI

  • LLM02 Sensitive Data Disclosure

    Unintended leakage of PII, credentials, or proprietary data through model outputs.
    ▸ Blocked by FortiDLP & FortiCASB

  • LLM03 Supply Chain Risk

    Compromised ML artifacts, third-party models, and dependency chain vulnerabilities.
    ▸ Blocked by FortiSandbox & FortiRecon

  • LLM04 Data & Model Poisoning

    Adversarial manipulation of training data or fine-tuning pipelines to corrupt model behavior.
    ▸ Blocked by FortiNDR & FortiSIEM

  • LLM05 Improper Output Handling

    Downstream execution of unchecked LLM outputs enabling XSS, SSRF, or privilege escalation.
    ▸ Blocked by FortiWeb & FortiGate

  • LLM06–10 Agency, Overreliance & More

    Excessive agency, overreliance, insecure plugins, unbounded consumption, and model theft.
    ▸ Assessed across full Fortinet AI Security Fabric

Phase 1b · Mitre Atlas Assessment

Adversarial ML Threat Coverage

Every MITRE ATLAS tactic is mapped to the Fortinet fabric layer that detects and blocks it — from initial reconnaissance through impact and exfiltration.

  • Reconnaissance & Resource Development

    Pre-Attack Targeting

    • Search victim-owned websites & repositories
    • Acquire public ML artifacts
    • Develop adversarial ML attacks
    ▸ Covered by: FortiRecon, FortiGuard

  • Initial Access & Execution

    System Compromise

    • LLM Prompt Injection (Direct & Indirect)
    • ML Supply Chain Compromise
    • LLM Plugin Compromise & Jailbreak
    ▸ Covered by: FortiGate, FortiSIEM, FortiDeceptor

  • Persistence, Evasion & Exfiltration

    Deep Infiltration

    • Backdoor ML Model, Poison Training Data
    • Evade ML Model, Adversarial Perturbation
    • Exfiltration via ML Inference API & AI Agent
    ▸ Covered by: FortiEDR, FortiNDR, FortiDLP

  • Impact

    Operational & Reputational Damage

    • Denial of ML Service, Cost Harvesting
    • Erode ML Model Integrity
    • External Harms via AI outputs
    ▸ Covered by: FortiWeb, FortiAI, FortiSandbox

Phase 2 · Risk Analysis

Your Exposure Score — Five Dimensions

AirGap Labs delivers a prioritized risk analysis that quantifies your exposure across five dimensions of the Fortinet AI Security Fabric.

  • 🔓

    Inbound Attack Surface

    Unprotected entry points for prompt injection, exploit, and supply chain attacks reaching your AI workloads.

  • 🔍


    AI Threat Detection Gap

    Coverage gaps in behavioral AI analysis and real-time anomaly detection across your environment.

  • 🧠

    AI Analysis Depth

    Degree to which AI/LLM workloads are inspected for adversarial manipulation and model abuse.

  • 📤

    Outbound / DLP Risk

    Sensitive data and model output leakage risk across cloud and endpoint channels.

  • 🌐

    Allowed Traffic Risk

    Legitimate-looking traffic that bypasses controls and enables covert exfiltration.

Phase 3 · Remediation Plan

Your Layer-by-Layer Roadmap

AirGap Labs translates your risk score into a prioritized remediation roadmap — specifying exactly which Fortinet fabric layer to deploy, configure, or tune to close each identified gap.



  • Immediate

    Quick Wins

    Immediate policy and configuration changes within your existing Fortinet deployment — zero new spend, maximum impact from what you already own.

  • Near-Term

    Layer Additions

    Deploy missing fabric components — FortiAI, FortiDLP, FortiDeceptor — to close critical gaps that existing configuration cannot address.

  • Ongoing

    Managed Monitoring

    Ongoing FortiSIEM and FortiNDR management to detect and respond to emerging AI threats as the attack landscape evolves.

Phase 4 · Fortinet AI Security Fabric Alignment

Which Layer Stops Which Attack

Every layer of the Fortinet fabric is purpose-built to stop a specific class of OWASP LLM or MITRE ATLAS threat. AirGap Labs ensures each layer is correctly deployed, integrated, and tuned.

ProductThreats BlockedCoverageDescription
FortiGate & FortiAI
Prompt Injection & Jailbreak
OWASP LLM01
AI-powered next-gen firewall with inbound request inspection and behavioral analysis for LLM traffic.
FortiDLP & FortiCASB
Data Leakage & Exfiltration
OWASP LLM02
Outbound content inspection and cloud access control preventing sensitive data disclosure.
FortiSandbox & FortiRecon
Supply Chain & ML Artifacts
OWASP LLM03
Artifact analysis and external threat intelligence to block compromised ML dependencies.
FortiNDR & FortiSIEM
Data Poisoning & Anomaly
OWASP LLM04
Network detection and correlated event analysis catching model poisoning in real time.
FortiGuard
Reconnaissance & Threat Intel
ATLAS Recon
Global threat intelligence feeds updated in real time to block known adversarial ML infrastructure.
FortiEDR
Persistence & Evasion
ATLAS Evasion
Endpoint detection and response stopping adversarial perturbation and model backdoor techniques.
FortiDeceptor
Lateral Movement & Plugin Exploit
ATLAS Access
Deception technology that lures and exposes attackers attempting LLM plugin compromise or jailbreaks.
FortiWeb
API Abuse & Inference Attack
ATLAS Impact
Web application firewall protecting AI inference APIs from abuse, cost harvesting, and model extraction.