ChatGPT and Open AI: a new phishing target in Q2 2026
Open AI’s ChatGPT entered the top 10 of the most impersonated brands in phishing attacks for the first time in the second quarter of 2026, according to a Check Point study. Check Point highlighted a June example in which a fake "ChatGPT Plus payment failed" email was dressed to look exactly like an OpenAI billing notice and directed victims to a page built purely to steal full credit card details.
Microsoft still dominates: market share and the top five
As detailed in Check Point’s Q2 Brand Phishing Report, Microsoft remains the most impersonated brand, as it did in the previous quarter. Check Point reported Microsoft accounts for 23% of all phishing attempts — nearly double the share of LinkedIn, the second-most targeted brand, which Microsoft also owns. Google, Apple and Amazon complete the top five, and those five brands together accounted for over half of all phishing attempts in Q2 2026.
Real-world impersonation tactics observed this quarter
Check Point described brand phishing as operations where scammers impersonate trusted companies by email, fake websites or both, to steal login credentials, payment details or personal information. The firm catalogued multiple real cases in Q2: besides the ChatGPT billing scam, analysts observed full replica online stores, fake login pages and malware disguised as software updates. Specific examples included a cloned Michael Kors store that replicated the entire checkout, a fake UNIQLO storefront operating in a country where UNIQLO does not even operate, and a dodgy PayPal login page whose warped logo looked AI-generated.
Check Point’s mitigation recommendations
In a blog published on July 23, Check Point laid out several technical and operational steps to mitigate brand phishing. Recommendations include stopping phishing messages inline before they reach an inbox rather than relying on detection after delivery; using AI-powered detection to catch brand impersonation, business email compromise, credential harvesting, QR code phishing and AI-generated attacks with accuracy beyond manual review; consolidating email and workspace protection across Microsoft 365, Google Workspace and collaboration tools into a single platform to reduce operational complexity; and automating investigation and response so security teams can resolve real threats faster.
What this means for technologists, enterprises, and end users
- Technologists and security teams: Expect attacker attention to track where user behavior shifts. Check Point warned, “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.” Teams will need to apply inline defenses and AI-assisted detection across email and collaboration platforms, per Check Point’s guidance.
- Enterprises and procurement leaders: The concentration of attacks around a handful of brands — Microsoft at 23% and the top five accounting for more than half of attempts — argues for consolidating protection across those ecosystems. Check Point recommends unifying defenses across Microsoft 365, Google Workspace and collaboration tools to reduce complexity and speed response.
- End users and the general public: The Q2 report’s concrete examples — a convincing ChatGPT billing notice, cloned retail checkouts and warped logos on login pages — show phishing is exploiting familiar services and subscription flows. Users should treat unexpected payment-failure notices and storefront links with caution, because attackers are building pages specifically to harvest full payment and credential data.
Check Point’s findings place AI tools squarely in attackers’ sights and flag a trend: platforms that become daily utilities — managing subscriptions, payments and work tasks — will draw the same impersonation pressure faced historically by banks and big tech. Check Point concluded plainly, “Expect AI platforms to keep climbing this list in future quarters.” That projection turns the Q2 snapshot into an operational question for defenders: can inline blocking, AI-driven detection and consolidated protection outpace an attacker set on mimicking the very services users rely on?
