According to a recent LinkedIn post from StrongestLayer, the company has published an extensive taxonomy of email attacks that maps 37 subtypes across four detection architectures. The post highlights that many of the most financially damaging threats now resemble normal business communications and often evade traditional pattern-matching defenses.
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The LinkedIn post cites internal analysis indicating that 68% of advanced email attacks analyzed fall below a 0.30 Jaccard similarity threshold, suggesting limited effectiveness for legacy, signature-based tools. It further notes that techniques such as adversary-in-the-middle phishing, QR code exploits, account-takeover BEC, and thread hijacking are increasingly common rather than rare exceptions.
StrongestLayer’s post references industry data including $55 billion in cumulative business email compromise losses since 2013 and an average breach cost of $4.45 million when email is the initial vector. The post also argues that AI-generated spear phishing has sharply reduced the cost of personalized attacks, and that more than 10,000 organizations were hit simultaneously by AiTM campaigns by 2023.
For investors, this content underscores a growing demand backdrop for advanced email security solutions that can address structural gaps in secure email gateways and basic machine-learning tools. By positioning an interactive, architecture-rated taxonomy as a reference for security buyers, StrongestLayer may be seeking to establish thought leadership, support enterprise sales cycles, and differentiate its approach in a crowded cybersecurity market.
If widely adopted by CISOs and security teams, such a taxonomy could influence how organizations evaluate and budget for multi-layered defenses, potentially expanding the addressable market for vendors focused on behavioral and multi-agent architectures. While the post is primarily educational and does not disclose commercial metrics, it signals that StrongestLayer is targeting complex, high-value email risk scenarios where spending tends to be less discretionary and more resilient through cycles.

