Cinchy today announced the general availability of PeriMind, a new suite of AI governance solutions designed to help enterprises run AI safely, predictably and with confidence as artificial intelligence moves from pilots into business-critical operations.
The AI Trust Gap
Enterprise AI adoption is accelerating, but operational trust has not kept pace. Organizations are rapidly deploying copilots, AI agents and autonomous workflows to improve productivity, reduce costs and accelerate decision making. Yet many executives still lack visibility into where AI is being used, what systems it can access, how much it is costing the business or whether its actions align with organizational policy.
As AI becomes embedded in everyday business operations, these blind spots create new challenges. Shadow AI introduces unmanaged applications and models, AI systems consume resources without clear accountability, and security and compliance teams are expected to govern AI behavior without the operational visibility needed to understand what AI is actually doing.
The result is a growing gap between AI adoption and AI trust.
Many enterprise AI initiatives will struggle to scale, not because the technology fails, but because organizations lack the governance, visibility and operational controls needed to deploy AI confidently in production.
Introducing AI Action Governance
Cinchy believes organizations need more than governance frameworks, policies and risk assessments. They need operational control over AI as it works across enterprise systems.
The company defines AI Action Governance as the discipline of observing, governing and enforcing policy over AI behavior in real time as AI systems access data, interact with applications and execute business actions.
PeriMind helps organizations close the AI trust gap by providing the visibility, governance and operational oversight needed to confidently scale AI across the enterprise. Rather than asking organizations to choose between innovation and control, PeriMind enables them to move faster with AI while maintaining confidence that AI systems are operating safely, responsibly and in alignment with business objectives.
Built to Help Organizations Trust AI
PeriMind is designed to help organizations:
- Build trust in AI through operational visibility and accountability.
- Reduce the risks associated with Shadow AI and uncontrolled AI adoption.
- Better understand and manage the operational cost of AI across models, agents and enterprise workflows.
- Govern how AI interacts with enterprise data and business applications.
- Strengthen security, compliance and human oversight as AI adoption expands.
Built on a Foundation of Trusted Data Access
PeriMind is built on the same governance principles that established Cinchy as a trusted provider of enterprise data access and control solutions.
Organizations worldwide rely on Cinchy’s Data Collaboration Platform to govern how information is shared across complex enterprise environments. With PeriMind, Cinchy extends that foundation to AI, giving organizations the visibility, accountability and control needed to confidently deploy AI across enterprise data, applications and business processes.
Organizations interested in evaluating their AI readiness, governance posture and adoption strategy can schedule a complimentary trusted AI adoption assessment with Cinchy.
To learn more, visit www.cinchy.com.
Guest Post: What Is Brand Phishing and Why Does It Work?
Posted in Commentary with tags Check Point on July 23, 2026 by itnerdBrand phishing is when a scammer impersonates a trusted, well known company, through email, a fake website, or both, in order to steal login credentials, payment details, or personal information. It works because trust is transferable. If a message looks like it came from a brand you already use and rely on, your guard drops. You’re not evaluating a stranger’s request. You’re responding to what feels like routine correspondence from a company you already have a relationship with. That single psychological shortcut is the entire business model behind brand phishing.
Which Brand Was Impersonated Most in Q2 2026?
Microsoft, by a wide margin. In Q2 2026, Microsoft remained the most impersonated brand in phishing attacks, accounting for 23% of all brand impersonation attempts, nearly double the next closest brand. Here’s how the full top ten broke down.
Together, the top five brand names cover more than half of all brand phishing activity this quarter. That concentration is worth sitting with. Scammers aren’t spreading their efforts across thousands of brands. They’re focused on a small set of names that nearly everyone recognizes and uses daily, since that recognition is what makes the con work in the first place.
Why Did ChatGPT Suddenly Join the Top Ten?
For the first time, the ChatGPT appeared among the ten most impersonated brands tracked in this report. It’s a strong signal of where attacker attention is heading next. As AI tools move from novelty to daily habit for millions of people managing subscriptions, payments, and work tasks through them, they become just as attractive a target as any bank or tech giant. One example from June involved a fake ChatGPT Plus billing email, built to look exactly like an OpenAI payment failure notice, that led to a page designed to harvest full credit card details. Expect AI platforms to keep climbing this list in future quarters.
Which Industries Get Targeted Most?
Technology led as the most impersonated sector overall, with Social Networks and Banking close behind. This lines up neatly with the brand rankings above. The industries under the most pressure are the ones handling our identities, our professional relationships, and our money, which also happen to be the accounts most people would be quickest to protect if only they knew an attack was happening.
What Do Real Phishing Attempts Actually Look Like?
The following sample of documented cases from this quarter demonstrate just how varied these schemes can be.
ChatGPT. A fake subscription failure email led to a payment page built to steal credit card details, using an official looking OpenAI subject line and branding.
Michael Kors. A registered lookalike site replicated the entire shopping experience, browsing, cart, and checkout, all designed to capture payment information under the guise of a real purchase.
UNIQLO. A fake regional storefront appeared for a market UNIQLO doesn’t officially operate in. The giveaway was that its social media icons didn’t actually connect to UNIQLO’s real accounts.
Apple. A fake iCloud login page, presented in Russian, used Apple’s real logo and branding. The sign in button itself didn’t work, suggesting the page was still being tested before a fuller campaign.
PayPal. A near identical login page carried a noticeably distorted PayPal logo, a likely sign it had been produced with an AI image tool rather than lifted from PayPal’s actual assets.
Microsoft. A fake support page pushed an urgent Office security update. Clicking through didn’t install anything from Microsoft. It delivered a disguised executable file, the first step of a malware infection.
What Gives Phishing Attempts Away?
A few patterns showed up across nearly every case.
A sense of urgency is doing the work. Payment failures, security alerts, and required updates all push you to act before you stop to think, which is exactly the point.
Small visual flaws are common. A distorted logo, a button that doesn’t respond, icons that lead nowhere. None of these are obvious at a glance, but a more thorough review tends to reveal them.
Domains rarely match the real brand exactly. A slightly off spelling, an unusual extension, or a domain that has no business hosting that brand’s content is a strong signal on its own.
AI-generated assets are starting to leave their own fingerprints. As logos and pages get faked with AI tools, subtle distortions and inconsistencies are becoming one of the more reliable ways to spot a fake.
Leave a comment »