StrongestLayer in the news.

The category is still organizing threats by surface-level symptom — phishing, BEC, malware — when what it needs is a structural taxonomy that maps attacks by the underlying detection challenge they create.

The deciding factor in AI-enabled email security is not who has better models, it is who has better data and how fast they can act on it.

Threat research shows attackers shifting payload delivery to SaaS notifications and shared documents, where legacy SEGs cannot meaningfully inspect the content of the trusted platform.

The new release introduces the Evidence Engine, which autonomously investigates every inbound email threat and delivers a complete case file, a dollar-quantified risk score, and a recommended action.

Every email allow-list is a standing permission slip for attackers who compromise a trusted sender. Zero trust that stops at the email layer is not zero trust.

Practical companion to the Zero-Trust Paradox argument. Five pointed questions a CISO can bring to their email team that surface exactly how many attackers are already trusted by default.

Threat intelligence report analyzing roughly 200 advanced QR code phishing attacks that successfully bypassed Microsoft Defender E3/E5 and leading SEGs before being caught by StrongestLayer.

Threat intelligence report analyzing 2,042 confirmed email threats. 77% impersonated DocuSign, Microsoft, or Google. 77% failed SPF/DKIM/DMARC yet still landed. ≈45% showed AI-assistance indicators.

Why CISOs need a new mental model when adversaries operate at machine speed. Borrowing from Kahneman’s System 1/System 2 to reframe detection and triage when AI compresses the OODA loop to seconds.

The emails hitting your inbox in 2026 are built from real parts. AI collapsed the expertise ceiling and made APT-grade kill chains commodity.

Multi-channel evasion is the new default. A clean email with a phone number routes the payload through a conversation your email security never sees.

StrongestLayer research exposed attackers abusing M365 Direct Send to spoof internal users at scale. Every legacy gateway in our test set missed it.

RAG poisoning is the new supply chain attack. The integrity of every AI-powered defense now depends on the provenance of the corpus it trains on, and most vendors cannot document theirs.

When AI models autonomously discover and chain vulnerabilities, the exploit supply becomes infinite. The chokepoint is not patching, it is how attackers deliver the payload — that chokepoint is email.

Personalization used to cost attackers time. Now it costs them nothing. Every defense built on “attackers won’t bother” is now economically obsolete.

Signatures tell you what you already know. Context tells you what you are looking at. Next-gen email defense needs both, running against each other.

A system reflects the communication structure of the team that built it. Gateway architectures built on rules and committees produce rules-and-committees products.

A CISO evaluation framework for AI security vendors that cuts past the marketing layer — what the model sees, what it retains, and what it can actually reason about in production.

StrongestLayer research cited on the live rate of trusted-platform abuse. Analysts need evidence at the platform-interaction layer, not just the message layer.

Behind every probability score is a confidence interval no dashboard surfaces, and AiTM plus enterprise AI agents are silently breaking the behavioral baselines your detection depends on.

The parallels between AI agent architectures and classic MITM exploits are closer than the industry wants to admit. Every trusted intermediary is a potential pivot point.

An inbox-native security assistant that gives every email a verdict — Safe to Trust, Caution, or Block — with the reasoning right beside the message. Available on Microsoft AppSource.

The tells we taught users to spot (typos, pixelated logos, mismatched URLs) are exactly what LLMs eliminated. When the training data is stale and the attacker has fresh data, the training becomes misdirection.

Extended Q&A with Alan LeFort on AI-driven attack economics, the mid-market security gap, and why “good enough” email security becomes catastrophic the moment attackers automate their side.

GTM-focused founder interview with Alan LeFort. Long-form on POC strategy, category creation in a crowded market, and the discipline of refusing to overclaim.

Researchers uncovered malware scaffolded and operated by a commodity LLM. StrongestLayer research cited on prompt injection, LLM poisoning, and what it means when attack tooling becomes a prompt.

Long-form feature with Alan LeFort on what AI-native email security looks like architecturally, not just in marketing — and where the threat landscape is heading.

Full-length interview with Alan LeFort on the origin story behind StrongestLayer, the dual-evidence detection model, and why email remains the most strategic layer in security.

Sorenson Capital leads, Recall Capital participates. Funding accelerates development of the TRACE platform — an LLM-native email security architecture purpose-built for the AI threat era.

Coverage of StrongestLayer’s public launch, the TRACE reasoning architecture, and the founding team’s background at Proofpoint, McAfee, and Intel Security.