Criminals clone a voice to move money and reset the wrong account. Now they hide instructions inside a website to steer someone's AI assistant. DeepBlocker runs the attack the way they would, shows you exactly what got through, and blocks it live. Offence finds the gap, defence closes it, and the evidence proves it to a board, an insurer or a regulator.
Cloned voices and faces are already moving real money out of real organisations. The figures below come from named, public sources.
A first call is friendly and forgettable. It picks up a name, a system, a schedule, nothing that raises an alarm. A second call follows up days later, sounds familiar, and earns one small yes. The third call spends that trust on the real ask: a code, a reset, a payment. This is close to how the 2023 Retool breach actually ran: a text message, then a phone call, then an escalating request for an MFA code. Attack Sequences now runs the same chain against your own team, on a schedule, so you find the gap before a real attacker does. You pick from a library of these chains, each modelled on a documented breach, and the caller can even carry what it learned from one campaign into the next, months later.
Every product does one of two jobs. Red team finds the gap by running the attack. Blue team closes it by blocking what gets through. Today that runs on your phone lines. Now it runs on the AI assistants your staff and customers let act on websites too.
Where the attack lands today. Two protect you from calls coming in, one protects a phone company from the calls its customers send out, and one is the raw sensor for developers.
Where it lands next. AI assistants now take real actions on websites inside a logged-in session, and they can be talked into the wrong one. Same engine, same evidence pack, a target that is not human.
Most voice detection relies on a single AI model. DeepBlocker doesn't. Every call goes through three independent checks before it is trusted, so if an AI-generated voice gets past one, the next catches it. Because we verify your real voice, not the latest AI model, protection stays accurate as voice technology evolves.
Our deepfake detector, trained on degraded real-world telephony where lab models collapse. Catches synthetic and cloned speech.
Each authorised voice is enrolled once. Every future call is matched against that fingerprint. New voice AI does not change what your real people sound like.
An AI agent reads the conversation and scores the ask against policy: amount, counterparty, urgency, pressure tactics.
Every voice-AI vendor sells you a number: "we're 96% accurate." A number you cannot verify, from a model that changes next month. When a regulator or insurer asks what happened on one specific call, a number is worthless.
DeepBlocker seals every verdict into a record you can prove: what ran, which model version, what it decided, when. Not "trust us." Verify it yourself.
Just as STIR/SHAKEN forced every US carrier to install caller-ID authentication, fraud-call screening is becoming mandatory plumbing. The rules being written now will fine the carrier, per call, unless it can prove it was screening. That proof is the product.
A Vishing Readiness Assessment is the fastest way to see your exposure, and the first page of an evidence trail you will be glad to have.