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Secure Your AI Attack Surface Before an Attacker Does

Expert-validated AI penetration testing for chatbots, copilots, and AI agents wired into your data, your customers, and your business.

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AI is moving faster than most security programs can track. Chatbots, copilots, and AI agents now touch customer data and business-critical decisions - often without the scrutiny applied to everything else you run. Your board is already asking how exposed you are. InfoSight's AI Penetration Testing gives you an answer backed by evidence, not guesswork.

Why Executives Care About AI Security

AI creates a category of risk traditional software doesn't. It can be manipulated through conversation, trusted with decisions, and connected straight into sensitive systems. An attacker doesn't always need a technical vulnerability - just a way to talk your AI into doing something it shouldn't.

This isn't only an IT problem anymore. It reaches customer trust, IP, regulatory compliance, financial performance, and board oversight.

Executive questions we answer:

Can an attacker access confidential information?
Can our AI be manipulated or bypass authorization?
Could an AI agent take an unauthorized business action?
What's the business and regulatory exposure if it can?

Know Where You Stand Before Someone Else Finds Out

You've just read what's at risk. In a scoping call, we'll map that risk to your actual AI environment — no generic checklist, no obligation.

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What actually changes after an engagement:

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

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

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

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

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

Why AI Security Testing Matters

AI is already inside your organization, sanctioned or not. Employees paste sensitive data into public AI tools and stand up integrations without security review - often invisible to IT until an incident forces it into view.

AI systems can be manipulated without a single line of code being exploited. A traditional app either has a vulnerability or it doesn't. AI can be reasoned with - an attacker just needs to talk it into misbehaving.

Key risk areas:

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.

None of this means AI should be avoided. It means AI needs the same testing rigor as any system touching sensitive data - and most organizations haven't applied it yet.

What Is AI Penetration Testing?

Traditional penetration testing looks for exploitable flaws in networks, applications, and infrastructure. AI penetration testing goes further: it tests how an AI system behaves under adversarial pressure - not just whether it has a flaw, but whether it can be persuaded into acting against its intended purpose.

Attack surface traditional testing doesn't cover:

LLMs manipulated through language, not code.
Chatbots and copilots tricked into revealing instructions or internal data.
RAG systems exploited to surface data outside a user's authorization.
AI agents manipulated into unauthorized autonomous actions.
APIs connecting AI to internal tools, with an AI layer deciding access on top.

One question drives it all: if someone tried to misuse this system, what could they actually get it to do?

Who It Protects - and What We Test

InfoSight scopes engagements around three tracks. Most clients get a tailored combination.

Track 1 - If You Use AI

Organizations relying on AI tools they didn't build in-house.

Chatbots and customer-facing copilots
AI features embedded in SaaS platforms you've already purchased
Shadow AI employees have adopted outside IT's visibility

Track 2 - Microsoft 365 & Entra-Heavy Environments

Organizations standardized on the Microsoft stack.

Microsoft 365 Copilot deployments
Entra ID permission boundaries and inheritance risks
Data access controls across connected Microsoft 365 services

Track 3 - If You Build AI

Organizations developing custom AI capabilities.

Custom LLM applications, APIs, and RAG pipelines
AI agents with system access and autonomous task execution
Third-party models and plugins integrated into your applications

What we hunt for, across every track: prompt injection and jailbreak techniques, sensitive data and PII leakage, privilege escalation via AI-mediated access, and agent/integration abuse.

How the Engagement Works

InfoSight scopes engagements around three tracks. Most clients get a tailored combination.

Scope & Threat Modeling - we map your AI footprint, compliance obligations, and the attack scenarios that matter most.

Discovery - we identify AI applications, connected data sources, APIs, agents, plugins, and integrations.

Exploitation & Validation - real-world chained attacks - prompt injection, jailbreaking, data exfiltration, agent abuse - not tested in isolation.

Risk Scoring - findings rated by likelihood, impact, and compliance exposure.

Reporting & Readout - executive summary, technical report, Mitigator dashboard scores, remediation roadmap, and a live readout with your teams.

Industry Use Cases

Financial Institution - an AI assistant tricked into exposing accounts or bypassing authentication means GLBA reporting obligations, fraud liability, and reputational damage.

Healthcare - an AI clinical assistant leaking protected health information can trigger HIPAA breach notification, among the costliest breach categories in any industry.

Legal Firm - a generative AI assistant surfacing privileged client information threatens attorney-client privilege and the relationship itself.

Manufacturing - an AI production assistant exposing proprietary processes or supplier pricing erodes competitive advantage and supplier trust.

The pattern holds across every industry: AI security failures reach past IT into regulatory, financial, and reputational territory that takes far longer to repair than the underlying technical issue.

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.

Why Choose InfoSight

Expert-validated, not just tool-generated. Automated scanners surface broad, surface-level signals - they don't think like an attacker. Our certified experts personally craft, chain, and validate every attack, confirming what's real and translating each finding into business risk instead of raw output your team has to triage.

Executive summaries built for decision-makers. Your board gets plain-language risk and business impact; your engineers get reproduction steps, evidence, and concrete remediation - from the same engagement.

Business - reduce the risk of AI-driven breaches, protect customer trust, give leadership an ongoing view of AI risk via Mitigator.
Operational - identify shadow AI, establish a baseline attack surface, build a repeatable testing cadence as AI expands.
Security - uncover prompt injection, jailbreak, and manipulation vulnerabilities before attackers do; validate access controls; test agents for unauthorized actions.
Compliance - generate evidence mapped to OWASP, NIST AI RMF, HIPAA, GLBA, PCI DSS, and SOC 2 - ahead of AI-specific regulation taking effect.

Frequently Asked Questions

Scanners can't craft adversarial prompts or chain exploits; our experts do that by hand, then validate what's real.

Testing stays inside a scope you approve up front, against systems you designate, with every action documented.

Both: an executive summary, a separate technical report, and a live readout for each audience.

No - most organizations need both, since AI sits on top of infrastructure that still requires conventional testing.

Before production deployment and after any significant change, at minimum; many adopt an annual or semiannual cadence.

Yes - Track 2 is built specifically for Microsoft 365 Copilot and Entra ID.

Yes - AI connected via RAG, plugins, or direct integrations can be manipulated into surfacing unauthorized data even with controls configured correctly.

An executive summary, technical report, live Mitigator scores, remediation roadmap, compliance-mapped evidence, and a live readout.

Yes - agents that place orders, update records, or send communications are assessed for manipulation risk.

AI is already in your business - sanctioned or not. Find the gaps before someone else does.

InfoSight's AI Penetration Testing gives your organization a clear, business-grounded picture of AI risk - expert-validated, compliance-mapped, and tracked in Mitigator long after the engagement ends.

No spam-one expert follow‑up, guaranteed.

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