InterSec holds ISO/IEC 42001:2023 certification and runs its own Secure AI framework. We help you adopt and operate AI with the governance, assessments, and controls to protect your data, your models, and your reputation.
Adoption is racing ahead of the controls meant to keep it safe. The public data shows where the gaps are.
of employees were routinely accessing generative AI on their corporate devices, most through personal accounts outside IT oversight.
Source: Verizon 2025 DBIRof observed phishing activity already showed signs of AI by early 2025, from lure text to full campaign automation.
Source: ENISA Threat Landscape 2025of organizations vet the security of AI tools before they deploy them, even as 66% expect AI to reshape cybersecurity.
Source: WEF Cybersecurity Outlook 2025reported AI incidents in 2024, a record high and a 56.4% jump in a single year.
Source: Stanford 2025 AI IndexTools alone don’t close this gap. A governed program does. InterSec is ISO/IEC 42001:2023 certified and runs its own Secure AI framework, so the discipline we build for you is the one we hold ourselves to.
InterSec holds ISO/IEC 42001:2023 certification for our own AI management system. The governance discipline we build for you is the one we operate ourselves, so the guidance you get is grounded in practice, not theory.
That is the difference between a vendor that read the standard and a partner that lives by it.
The AI management system standard. We hold the certification and implement it for clients.
The information-security backbone most AI governance extends from.
The baseline our AI security assessments test against.
Our AI services run from ISO/IEC 42001 compliance through assessment, governance, and ongoing monitoring. Each one maps to recognized frameworks like ISO/IEC 42001 and the OWASP Top 10 for Large Language Model Applications.
That means your program holds up when a regulator, customer, or partner asks for evidence. We support federal, state, and commercial teams alike.
We take you from gap assessment to an audit-ready AI management system, the same standard we hold ourselves.
We test your AI systems against the OWASP Top 10 for LLMs and hand you a prioritized list of what to fix first.
We stand up the policies, roles, controls, and risk scoring a defensible AI program needs.
We build security into your models, pipelines, and integrations before weaknesses reach production.
We keep sensitive and regulated data protected as it moves through training and inference.
We help you spot, contain, and keep watch for attacks aimed at AI, from prompt injection to model abuse.
We check models for bias and document the fairness evidence stakeholders ask for.
We give your engineers and data teams the hands-on skills to use AI safely.
Most engagements follow the same path, scaled to where you are. You can start small and take it as far as you want.
We baseline where your AI use and governance stand today, including the Shadow AI most teams can’t see.
We rank what we find by real risk and hand you a clear, sequenced plan you can act on, not a stack of findings.
Policies, roles, and technical controls, aligned to ISO/IEC 42001 and the OWASP Top 10 for LLMs.
We watch how your AI behaves over time and adjust controls as your models and the threats change.
The kinds of problems we help teams solve across finance, healthcare, and the non-profit sector.
A bank needs to defend its AI-driven fraud detection against threats like data poisoning and adversarial inputs flagged in the OWASP Top 10 for LLMs.
We train the IT and data science teams on how these attacks work, then help build the defenses into how models are developed and shipped.
Stronger protection around customer assets and more confidence in the controls behind their AI.
A hospital network needs to confirm a new AI-powered diagnostic tool is secure and handles patient data in line with HIPAA.
Our assessment, guided by the OWASP Top 10 for LLMs, surfaces gaps in data storage and model validation, with a clear remediation plan and stronger encryption and validation controls.
Audit-ready evidence and a measurably lower risk of a data breach.
A non-profit using AI for climate modeling needs to show donors its systems are transparent, fair, and handled in line with GDPR.
We put an AI governance program in place, with clear policies for data protection, model transparency, and bias mitigation.
Documented, defensible AI governance that holds up to donor and regulator scrutiny.
Securing AI takes more than a tool. It takes a partner. Our program rests on five pillars.
We treat AI risk as a governance problem, not just a technical one. We don’t just find vulnerabilities. We build defensible, audit-ready programs.
Everything we produce is proof you can hand to an auditor, a board, or a customer. Clear, usable, and ready the moment someone asks you to show it.
We work as an extension of your team. Your people build real skills as we go, so you are stronger after the engagement, not dependent on us.
Point tools fix one piece. We cover the arc, from first assessment and policy through secure development and the monitoring that keeps it honest.
Technology matters, but our edge is people. You get GRC and cybersecurity experts who bring the judgment, threat intelligence, and hands-on guidance automated tools alone cannot.
ISO/IEC 42001 is the international standard for an AI management system. It gives an organization a repeatable way to govern how AI is selected, built, and operated, covering risk assessment, roles and responsibilities, and controls across the AI lifecycle. It is the AI counterpart to what ISO/IEC 27001 does for information security.
It matters because most AI risk is governance risk. Buyers, regulators, and partners increasingly want evidence that your AI is managed, not just deployed. Consult your compliance or legal team for final interpretation of how the standard applies to you.
A large share of the foundation. The two standards share the same management-system backbone: context, leadership, the risk process, internal audit, and continual improvement. If your ISMS is healthy, much of that structure carries over, and the new work concentrates on AI-specific risks like data provenance, model behavior, and human oversight. We break this down in our analysis of the ISO 27001 to ISO 42001 overlap.
Shadow AI is the unsanctioned use of AI tools by employees, outside any policy or review. It is common, and it is where a lot of sensitive data quietly leaves the building. We start with technical discovery to map where AI is actually used across your environment, then bring that usage under a governance policy your team can sustain. Our walkthrough on mapping Shadow AI shows the approach.
Yes. Our AI security assessments use the OWASP Top 10 for Large Language Model Applications as a baseline, covering risks such as prompt injection, insecure output handling, training-data poisoning, and model denial of service. According to OWASP, these are among the most common and serious weaknesses in LLM-based systems.
Yes. InterSec holds ISO/IEC 42001:2023 certification for its own AI management system. We run the same governance discipline internally that we help clients build, so the guidance you receive is grounded in practice, not theory.
Most start with a readiness assessment. We baseline where your AI use and governance stand today, flag the gaps that carry the most risk, and hand you a prioritized path. From there we can support policy development, secure deployment, and ongoing monitoring as far as you want to take it.
Want to turn AI risk into an advantage you can defend? Download the data sheet for a closer look at what we do, or book a short call with our AI security team.
