Portland's economy blends the Silicon Forest's technology and semiconductor presence with globally recognized apparel and footwear brands, a strong craft food and beverage industry, and busy port and freight logistics operations along the Willamette and Columbia rivers. InfoSight's AI Penetration Testing Services give Portland organizations the visibility to fix these gaps first.
Our human-led AI security assessments evaluate Agentic AI, LLM-powered applications, enterprise copilots, and customer-facing chatbots built on Microsoft Copilot, OpenAI, Claude, and Gemini. We test for prompt injection, jailbreaks, identity abuse, privilege escalation, sensitive data exposure, RAG data leakage, and unsafe plugin or API behavior across technology, apparel, and logistics environments unique to Portland.
Every result is scored against the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework, giving Portland's technology firms, apparel brands, and logistics operators a clear, prioritized path to stronger AI security.
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Protect your Portland organization with expert-led AI Penetration Testing Services from InfoSight.
Our specialists simulate realistic attacks against the AI technologies powering Portland's technology, apparel, healthcare, and logistics organizations. From product design tools and supply chain analytics to Copilot deployments and RAG-based knowledge assistants, we uncover prompt manipulation, unauthorized data access, excessive permissions, and unsafe autonomous actions—helping your team close gaps before they become incidents.
AI Security Practice Expertise
We are testers trained specifically in LLM exploitation techniques — not generalists running automated prompt scanners.
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.
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.
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.
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.
U.S.-Based Delivery Team
No outsourcing of your AI system's sensitive prompts, data flows, or architecture to third-party contractors.
From the Silicon Forest's technology cluster to Portland's global apparel and footwear brands, healthcare systems, and river-based logistics operations, every Portland organization carries a distinct AI risk profile. Our AI Penetration Testing Service is tailored to your environment and delivers:
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 over each 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.
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.
AI penetration testing is an authorized security assessment that examines LLM applications, AI agents, chatbots, RAG pipelines, and enterprise AI integrations for exploitable weaknesses across Portland's technology, apparel, healthcare, and logistics sectors.
Testing can assess generative AI applications, autonomous AI agents, customer-facing chatbots, retrieval-augmented generation environments, Microsoft Copilot deployments, APIs, plugins, and third-party integrations used by organizations throughout the Portland metro and Silicon Forest corridor.
An assessment can uncover prompt injection, jailbreaks, indirect prompt manipulation, sensitive data exposure, insecure output handling, excessive agency, unauthorized tool execution, privilege escalation, and other risks aligned with the OWASP Top 10 for LLM Applications.
Yes. Technology companies and global apparel and footwear brands headquartered in the Portland area can have AI-driven design tools, supply chain platforms, and customer service agents assessed for privilege escalation, data leakage, and model abuse risks.
Traditional penetration testing focuses on networks, applications, and infrastructure, while AI penetration testing also evaluates model behavior, prompt manipulation, data retrieval, autonomous decisions, and tool permissions unique to AI-driven systems.
Yes. Testing can evaluate Microsoft Copilot deployments, Entra ID permissions, connected data sources, and identity pathways to determine whether AI functionality could contribute to unauthorized access or sensitive information exposure.
Specialists simulate attacks to determine whether prompts, AI agents, RAG pipelines, APIs, or connected data sources could be manipulated to expose protected health information, port and freight logistics data, or other sensitive business content.
AI systems should be tested before production deployment and after significant changes to models, prompts, data sources, integrations, or permissions. Recurring assessments aligned with the NIST AI Risk Management Framework help manage risk as adoption grows.
Deliverables may include an executive summary, detailed technical findings, risk prioritization, business impact analysis, remediation recommendations, compliance-focused documentation, and a stakeholder briefing on your organization's AI security posture.