Executive summary: AI has supercharged brand impersonation, with Q2 2024 seeing nearly half of all processed emails containing spoofing or phishing attempts—40% of which were AI-generated. The scale, speed, and sophistication of these attacks are overwhelming security teams, draining resources on false positives, and leaving critical threats undetected. Consumers are unforgiving when trust is breached—most will hold the brand, not the attacker, responsible. Defending against this wave requires equally advanced AI-driven protection that can discover every misuse of brand assets, triage threats at machine speed, and adapt continuously to evolving attack methods.
3 Key Takeaways
- AI is now a core weapon for attackers – Brand spoofing surged 20% year-on-year, with phishing kits like Morphing Meerkat offering ready-made templates for hundreds of well-known brands.
- The cost of lost trust is enormous – 75% of consumers will cut ties with a brand after a cyber incident, and most will blame the company for failing to protect their data, not the attacker.
- Fighting AI with AI is essential – Effective defense requires AI tools that can scan the full attack surface, detect deepfakes and lookalike domains, prioritize the most dangerous threats, and drastically cut manual triage workloads.
Brands are under attack. Like the rest of us, artificial intelligence (AI) has given bad actors the tools to do their jobs more efficiently and cost effectively. In Q2 of 2024, approximately 1.8 billion emails were processed. Of them, 49% (a 20% YoY increase) were found to contain brand spoofing and other phishing techniques, with 40% generated by AI tools.
For those of us in the defense business, a 20% increase in AI-driven attacks in less than 12 months is not a surprise. Nor is the news that the Morphing Meerkat phishing kit contained 114 brand design templates, including Bank of America, Amazon, PayPal, Google Workspace, and Apple iCloud. No, what is hard to believe is the flurry of solutions that have appeared out of nowhere to actually solve this problem, which has cost companies more than $12 billion in lost revenue and brand remediation.
What we’re hearing on the ground
Over the past year, I have listened to CISOs, security analysts, and marketing leads who manage some of the world’s most recognizable brands. Their stories are remarkably similar:
- Too much noise, too little clarity: Threat feeds churn out thousands of alerts, yet the incidents that turn into headlines often slip through unseen.
- Manual triage is burning teams out: Analysts spend hours proving that 99% of what they review is harmless, leaving precious little time for the 1% that can hurt customers.
- Blind spots keep multiplying: New web domains, executive-impersonation accounts, AI-generated deepfakes, and sprawling partner ecosystems create an attack surface that changes faster than any spreadsheet can track.
Security leaders are desperate for the ability to manage their brand’s assets and identify threats quickly (especially with the ongoing advancements in AI), without reliance on complicated tools and solutions that don’t serve their needs. The need for full visibility into the complete attack surface is urgent, not a nice-to-have.
Brands build value, but trust is fleeting
Speed, as with most cyber attacks, is critical. Companies spend billions (and often decades) building a brand, only for trust to be eroded overnight. According to recent industry research, 75% of consumers are ready to sever ties with a brand in the aftermath of any cybersecurity issue, with the blame remaining at the brand’s door. In the U.S., 64% of Americans would blame the company—not the hacker—for the loss of personal data. Likewise, 44% of consumers attribute cyber incidents to a company’s lack of security measures.
For CISOs preparing for the next board meeting, investing in the right security tools to ensure full visibility should be a top priority. We are seeing some industry progress and I welcome the recent announcement by Microsoft on the launch of their Eutheropean Security Program, to combat the rise of AI as an evolving threat actor. The company to this date remains the most open to brand phishing attempts, accounting for 61% in 2024.
How AI can drive brand protection forwarda
To combat the speed, scale, and increasing sophistication of AI, you have to use AI. With the right tool, like Red Sift Brand Trust, you can now scan millions of domains and subdomains across the entire Internet, processing more data in a minute than a human team could review in a month. The secret is looking for specially trained models that can detect brand-spoofing campaigns such as lookalike domains, doctored logos, deepfake executive photos, and text patterns that have become more effective than traditional phishing scams.
And beyond detection of such weaponized content, specially trained AI imposes clarity on chaos. It groups thousands of related artifacts into a single storyline, turning a daily fire hose of raw indicators into a concise narrative AI analyst can act on without scrolling through endless alerts. Next, continuously self-retraining risk scores put the most consequential threats at the top of the queue. Analysts must no longer waste cycles chasing whatever popped up most recently; instead, they should focus on what can do real damage right now. Finally, by automating discovery, enrichment, and first-pass triage, precious hours can be regained. Those reclaimed hours become investigations, takedowns, and customer education, giving back vital resources and time for organizations.
A customer-driven checklist for evaluating solutions
Rather than comparing catalog features, my conversation with security leaders has focused on four practical questions. I share this advice for all moving forward:
What does good look like? | Why it matters |
2. Does it reduce my manual work week-over-week? | Attackers exploit forgotten sub-domains, dormant SaaS instances, and lookalike spellings you never registered. Comprehensive discovery closes those gaps before they become social-engineering tools. |
3. How fast does the system learn from each incident? | The ROI of any security investment is measured in analyst hours saved as much as dollars lost or recovered. Look for workflows that shrink triage backlogs without creating new ones. |
4. Will it age well? | A system should fold every confirmed takedown or false positive back into its model, so your next alert is smarter than the last. Static rule sets can’t keep up with AI-generated phishing kits that pivot daily. |
4.Will it age well? | Cloud migrations, re-brands, and market expansions all change your attack surface. Platforms that ingest fresh data sources and retrain continuously are future-proof; those that rely on one-off integrations are not. |
If a vendor can prove progress on these four fronts, feature matrices quickly become secondary. But beyond checking boxes, the most important thing a vendor should have is vision. The right tool equips your brand with a real-time, holistic map of the brand attack surface, with the most critical vulnerabilities alerting you to act before reputational damage occurs.
For those who think they can wait to invest in a proper brand detection solution, let me be emphatic: The surge in AI-assisted phishing will not slow; Q2 2024’s 20% year-on-year jump is already old news.
If you’re ready to get started, we’re ready to support you at Red Sift. Drop us a message and get started.
