BEC does not look like an attack.
Agents read the claim the message is making, and verify it.
.png)
From connection to BEC report in 72 hours.
Passing authentication is not the same as being legitimate.
Every verdict shows its work
A BEC message carries nothing a scanner can object to. No attachment, no malicious link, and every authentication check passes. The only thing wrong with it is what it is asking for. Three consequences follow, and finance teams live with all three.
There is nothing to scan
BEC arrives as plain text. No attachment to detonate, no link to sandbox, no signature to match. Every control built to inspect what a message carries finds nothing, because the message carries nothing. It gets delivered on the grounds that it is clean, and by that standard it is.
It passes every authentication check
The most effective BEC comes from a real account that has genuinely been taken over, or from a lookalike domain the attacker owns and has configured properly. SPF, DKIM and DMARC all pass, because the mail really is from where it says it is. Authentication answers who sent a message. It was never built to judge whether the request inside it is real.
The only thing wrong is the request
A supplier writes to say their bank details have changed. A director asks for a transfer to close before a deadline. Neither message is anomalous on its own, and both are ordinary business requests that arrive every week. Catching them means evaluating the claim itself: who is asking, what they want changed, and whether the thread and the relationship support it.
Aegis reads the request, checks it against the thread and the sender's history, and writes down what it found and why it mattered. Not a score. A record you can read, argue with, and hand to someone else.
Reviewable
Open any verdict and read the full agent trail: the signals, the conclusion, the timestamp, and the agent that produced each finding.
Exportable
Verdicts, indicators, and audit events push into your SIEM and case management. The evidence lives where your team already works.
Reversible
Release a message and Aegis records who released it and why. Your quarantine decisions become a documented trail rather than a black box.
In a fifteen-day head-to-head on live customer mail, the incumbent tool held a legitimate customer invoice, a vendor security report, and an internal production-deploy approval. Aegis raised no false positives on the same mail over the same window. All three of those messages were unusual. None of them was an attack.
See it on your own mail
Connect by API in minutes, read-only. Our agents re-read the last 14 days of delivered mail and report what got through, with the reasoning behind every verdict. Free, and yours to keep.
Fits the stack your SOC already runs
Aegis connects to your email platform in minutes and pushes verdicts, indicators and audit events into the tools your analysts already live in. No new console to babysit.
Not listed? Verdicts and indicators are available over a documented API and webhooks, so anything that can read JSON can consume them.
What security teams say after the first week
Answered before your reviewers ask
The hard part of buying security software is not the demo. It is the questionnaire, the DPA, and the architecture review. Here is what your security, privacy, and procurement teams will want in writing.
BEC prevention FAQs
Our gateway authenticates every message. Why does BEC still get through?
Authentication answers a narrow question: did this mail really come from the domain it claims? SPF, DKIM and DMARC are good at that, and BEC is built to pass them. The most effective attacks come from a real supplier account that has been taken over, so the mail genuinely is from that supplier, or from a lookalike domain the attacker registered and configured correctly. In both cases authentication passes honestly. It was never designed to judge whether a request to change bank details is legitimate. Aegis reads the request itself: who is asking, what they want changed, and whether the thread and the sender's history support the claim, then records the reasoning behind the verdict.
How does Aegis handle zero-day email attacks?
A model that has not seen an attack pattern before has nothing to match it against, and crowdsourced intelligence needs a first victim to report it. Aegis AI's agents use real-time analysis, natural language understanding and behavior signals to identify BEC and phishing the moment they appear, before they reach any threat intelligence feed.
Can Aegis AI reduce the workload on my security team?
Yes. By stopping advanced email threats before users see or click, and providing automated triage for suspicious messages, Aegis AI significantly reduces alert fatigue, freeing your team to focus on strategic initiatives.
Why should I choose Aegis AI over other inbound email security tools?
Our platform combines deep expertise from >20 years combined building security products (reCAPTCHA, Safe Browsing, Web Risk and more) with cutting-edge AI to deliver unmatched protection, lower false positives, and effortless integration, ensuring your business stays secure without slowing operations.
How easy is it to deploy Aegis AI?
Deployment is API-based, requiring no hardware, no MX changes, no network changes and no complex policies. Most teams connect in about two minutes and work from a single dashboard for insights and automated response. Nothing sits in the mail path, so there is no migration to plan and nothing to unwind if you disconnect.
Aegis AI does not score how unusual a message looks. A panel of agents reads what the message is actually asking for, checks that claim against the sender's history and the surrounding context, and records the reasoning. That is what catches an attack with no prior signal, because it does not depend on having seen one like it before.
The limit of a score is that you cannot argue with it. It tells you a message was unusual, not what was examined or why it mattered, so a mistake cannot be inspected and corrected. Reasoning can be read, disagreed with, and handed to an auditor.How do you catch a vendor's first fraudulent invoice?
There is nothing to recognise. The account is real, the history is real, and the invoice is the first fraudulent one it has ever sent, so there is no prior signal anywhere and nothing statistically unusual about it. Anything that works by matching against what it has seen before has nothing to match. Aegis works from the message in front of it. It reads what is being asked for, compares the payment details against what the thread and the prior relationship establish, and flags the change rather than the sender. A remittance change on an otherwise ordinary invoice is exactly the case this catches.
Aegis AI's agents reason about what a message is asking for and verify whether the claim holds up, then attach that reasoning to the verdict. A targeted attack written for one company has no prior signal anywhere and is not statistically unusual, so reasoning is what catches it.
A baseline also needs history it does not have at the moments that matter most: a first-time vendor, a new employee, a first payment request. Agents reason from the message in front of them, so there is nothing to wait for.
Aegis AI reads the request itself: who is asking, what they want changed, and whether the thread and the sender's history support it. A payment-detail change from a compromised but otherwise legitimate vendor account is not statistically unusual, which is exactly why scoring misses it.
And when a scoring model is wrong, the only route to a fix is a support ticket and a retrain. When agents are wrong you can read the trail, see which check produced the finding, and correct it directly.
See What It Missed
Experience the future of Email Security
