Brand 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.
The Claude Cowork flaw isn’t a patch problem, it’s a governance problem
Posted in Commentary with tags Anthropic on July 23, 2026 by itnerdClaude Cowork has a major issue that could let an AI agent act outside its intended boundaries is the latest example of a pattern the security and compliance community keeps circling back to: we’re deploying autonomous agents faster than we’re building the evidence trail to govern what they actually do.
If you are not familiar with this jailbreak, this will catch you up: Critical Security Flaw in Anthropic’s Claude Cowork Allows File Exfiltration via Prompt Injection | LinkedIn
Justin Beals, CEO & Founder of Strike Graph, an AI-native GRC and compliance automation platform had this to say:
“Every agentic AI vulnerability disclosure tells the same story. We built these tools to act on our behalf, then forgot to build the evidence trail for what they actually did. This isn’t a bug in one product. It’s a category problem.
Once an agent can take action inside a system, it’s not a feature anymore. It’s an identity. And most organizations still govern it like a checkbox on a vendor questionnaire instead of a live risk surface that needs continuous verification.
The companies that get burned by the next version of this flaw will be the ones still treating AI agent oversight as a one-time approval. Continuous evidence of what an agent did, not just what it was authorized to do, is the only model that scales.”
It would really be nice if AI was treated more strictly. But sadly it isn’t and that will come back to bite us all sooner rather than later.
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