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Cincinnati AI Penetration Testing & LLM Security Services

We Protect Cincinnati's Consumer Brands and Insurers From AI Risk

Cincinnati's consumer goods manufacturers, insurance carriers, and industrial companies are embedding AI copilots and large language models into product, claims, and operations workflows. InfoSight's AI Penetration Testing Services uncover prompt injection, model abuse, and data exposure across these AI deployments before attackers exploit them.

Our red team probes Agentic AI, enterprise copilots, and RAG pipelines built on Microsoft Copilot, OpenAI, Claude, and Gemini for prompt injection, sensitive data and PII leakage, identity and privilege escalation, RAG data exposure, and API or plugin weaknesses, then translates every finding into measurable business impact for Cincinnati organizations.

Findings are mapped to the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework, helping Cincinnati manufacturers, insurers, and industrial firms prioritize remediation and strengthen AI governance.

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User outline icon Human-Led AI Red Teaming
Audit checklist icon Audit-Ready AI Risk Reporting

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Trusted by organizations deploying AI across regulated industries.

Wayspring
BankUnited
Santander
iThink Financial
Tampa Museum of Art
Ohio Electric Cooperatives
APCU
Colgate University
Tampa Bay Fisheries
Apple Federal Credit Union
Charlotte County Florida
CEA

Don't let AI vulnerabilities and Abuse become your next security incident.

Protect your Cincinnati organization with expert-led AI Penetration Testing Services from InfoSight.

We simulate sophisticated real-world attacks against your AI ecosystem to reveal the vulnerabilities that matter most. From LLM-powered applications and AI agents to copilots, chatbots, and RAG implementations, our assessments identify exploitable weaknesses such as prompt injection, data exposure, privilege abuse, jailbreaks, and unauthorized AI actions—allowing your team to strengthen defenses before attackers capitalize on them.

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Why InfoSight for AI Security?

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AI Security Practice Expertise

We are testers trained specifically in LLM exploitation techniques — not generalists running automated prompt scanners.

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25-Year Regulated Industry Track Record

Since 1998 we've guided banks, hospitals, and utilities through every audit, breach, and compliance overhaul — now extended to AI risk.

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SOC 2 Type II Attested

Independent SOC 2 Type II attestation proves our own controls protect the sensitive data your AI systems expose to us during testing.

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Human-Led, Machine Validated

We use advanced tools at machine speed to find security gaps – then expert testers validate findings and use techniques to chain vectors together using human manipulation the way real adversaries do.

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Governance-Minded Testers

Findings mapped to the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework — not just a list of broken prompts.

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U.S.-Based Delivery Team

No outsourcing of your AI system's sensitive prompts, data flows, or architecture to third-party contractors.

Serving Clients Nationwide!

Customized AI Security Testing, Detailed Reporting

Every AI environment has a different risk profile. Our Cincinnati AI Penetration Testing Service is tailored to your models, agents, and integrations, and delivers:

  • Clear vulnerability prioritization - understand which AI security risks require attention first
  • Actionable remediation guidance - receive practical fixes, not simply a list of broken prompts
  • Compliance-ready documentation - support AI governance, security assessments, and audit requirements

What actually changes after an engagement:

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Real exposure, not assumed exposure. Evidence - validated, reproducible, ranked by business impact - instead of a guess.

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A shrinking attack surface. Findings are tracked to closure, and Mitigator shows exposure trending down over each engagement.

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A defensible answer for your board. When leadership asks "are we exposed," you have evidence, not an opinion.

Remediation icon

A to-do list, not a PDF to interpret. Every finding ships with reproduction steps and remediation guidance your engineers can act on immediately.

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A repeatable process. Each new AI feature gets tested against the same standard, so you're never starting from zero.

What We Test

Testing Area
What We Do
Sensitive data exposure
AI can be manipulated into disclosing information it was never meant to share.
Prompt injection
Malicious instructions hidden in input or connected data can override intended behavior.
Model manipulation
Attackers bypass restrictions or extract underlying instructions.
Compliance exposure
HIPAA and GLBA raise the stakes on how AI handles protected data.
IP leakage
connected AI assistants can surface proprietary information to the wrong audience.
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InfoSight AI penetration testing process diagram for businesses
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MITIGATOR Cyber Risk and Threat Intelligence Platform

Powered by Mitigator™

Most penetration test findings live and die in a PDF - read once, filed away, stale the moment the ink dries. InfoSight's don't. Every AI Penetration Testing engagement runs through Mitigator, InfoSight's proprietary threat-intelligence dashboard, and stays there for as long as you're a client.

  • A live portal, not a static report - see current AI risk posture any time, no waiting on the next PDF.
  • Remediation tracking, not a findings list - every finding carries a status: open, in progress, validated closed.
  • Trending over time, not a snapshot - see whether AI risk is going up or down release over release.
  • Board-ready views on demand - pull a current risk summary ahead of a board meeting or audit.
  • Exposure mapped to your frameworks - NIST AI RMF, OWASP Top 10 for LLMs, HIPAA, PCI DSS, GLBA - updated as findings are remediated.
CompTIA PenTest+ Certified Plus Series
CompTIA CySA+ Certified Plus Series
CompTIA CSAP Security Analytics Professional
CISM Certified Information Security Manager
INE ICCA Certification
eJPT Certification
Google Cloud Certified Associate Cloud Engineer
CompTIA Security+ Certified Plus Series
CompTIA Cloud Essentials+ Certified Plus Series
CRISC Certified in Risk and Information Systems Control
CISA Certified Information Systems Auditor
Certified Banking Cybersecurity Manager (CBCM)
AWS Certified Cloud Practitioner Foundational
American Water Works Association Utility Risk & Resilience

How the Assessment Works

  • Scope & Threat Modeling - We map your AI ecosystem, assets and data flows; define business priorities; and model threat actors and attack paths that matter most.
  • Discovery - We identify AI tools, integrations, data flows, and permissions including shadow AI and third-party services across the environment.
  • Certified practitioners - simulate real-world attacks, exploit findings safely, and validate impact with hands-on testing and abuse-case scenarios.
  • Exploitation & Validation Risk Scoring - Findings are ranked by likelihood, impact and business criticality and mapped to frameworks (e.g., NIST AI RMF, OWASP, ISO, SOC 2) so teams know what matters first.
  • Reporting & Readout - You receive an executive summary, technical report, prioritized remediation roadmap, and a live walkthrough with clear next steps and ownership recommendations.

Cincinnati - AI Penetration Testing Frequently Asked Questions

AI penetration testing is an authorized security assessment that identifies vulnerabilities in large language models, AI applications, chatbots, AI agents, RAG systems, and enterprise AI integrations used by Cincinnati organizations.

Testing can assess LLM applications, AI agents, customer-facing chatbots, RAG pipelines, generative AI platforms, Microsoft Copilot, Entra ID integrations, APIs, plugins, and other enterprise AI systems.

Our testing identifies prompt injection, jailbreaks, sensitive data exposure, insecure output handling, excessive agency, unauthorized tool access, model abuse, and other risks aligned with the OWASP Top 10 for LLM Applications.

Yes. Testing is planned around an approved scope and can target designated environments, applications, and AI workflows to minimize operational disruption while validating real-world security risks.

Vulnerability scanners identify known technical weaknesses, while AI penetration testing uses adversarial techniques to evaluate how models, prompts, data sources, tools, and AI workflows behave under realistic attack scenarios.

Yes. AI security testing can assess Microsoft 365 Copilot, Entra ID, connected data sources, permissions, integrations, and potential pathways to unauthorized access or sensitive information exposure.

Testing evaluates whether prompts, RAG systems, plugins, APIs, AI agents, or connected data sources can be manipulated to expose confidential information or perform unauthorized actions.

AI systems should be tested before production deployment and after significant changes to models, prompts, integrations, data sources, or permissions. Many organizations also schedule recurring annual or semiannual assessments.

Deliverables may include an executive summary, detailed technical findings, vulnerability prioritization, remediation recommendations, compliance-mapped evidence, and a live security readout for stakeholders.