Deepfake and voice-fraud intelligence from the people building the detection. Real attacks, new generation models, what defends against them, and where the regulation is heading.
Executive voice impersonation has moved from a hypothetical concern to a testable control failure, and firms need evidence that urgent requests can be independently verified.
Read the post →Synthetic identity risk is moving through recruiting, payroll and executive communications, so readiness must be tested across the workflows that confer trust.
Read the post →AI voice fraud is becoming familiar vishing with a more convincing voice, so firms need evidence of how people verify unexpected requests, not another reminder that deepfakes exist.
Read the post →AI voice cloning turns a familiar caller into an operational test of how your organisation verifies urgent requests.
Read the post →Synthetic-voice vishing is now an operational risk, so regulated firms need evidence that their controls work in real conversations, not only on paper.
Read the post →AI voice cloning turns recognition into a weak control, so the question is whether your staff verify identity before acting on an urgent request.
Read the post →The reported €95 million bank fraud is a reminder that payment workflows, not awareness training alone, must be tested against synthetic callers.
Read the post →The test for AI voice fraud is not whether staff recognise a scam, but whether they follow independent verification when urgency arrives in a familiar voice.
Read the post →The reported Fideuram fraud is a reminder that voice verification must end in an independently confirmed payment instruction, not recognition of a trusted executive.
Read the post →AI voice fraud is testing whether urgency, authority and familiarity can override the controls your organisation believes are already in place.
Read the post →AI-cloned executive and supplier voices turn familiar phone calls into payment-risk events, making tested behaviour and sealed evidence more important than another awareness module.
Read the post →A Vishing Readiness Assessment tests whether people and escalation paths hold up when a familiar voice makes a high-risk request under pressure.
Read the post →Recent fraud guidance points to a practical control question: will staff independently verify and escalate when a convincing caller applies pressure?
Read the post →Phishing training matters, but it does not prove that staff and payment workflows can withstand a convincing vishing attempt.
Read the post →Why regulated firms need to test how people verify urgent requests, not merely whether they recognise suspicious wording.
Read the post →Deepfake calls are making voices, faces and caller IDs unreliable, so regulated firms must test the workflows that sit behind verification.
Read the post →The reported disruption to the Bankruptcy Noticing Center is a reminder that vishing readiness belongs in operational resilience, not only security awareness.
Read the post →The reported Fideuram incident is a reminder that payment controls must withstand convincing identity, voice and urgency together.
Read the post →AI voice cloning makes familiarity a weak control, so regulated firms need evidence that staff can follow independent verification under pressure.
Read the post →A convincing face and familiar voice should never be able to bypass callback, approval, separation-of-duties and escalation controls.
Read the post →A reported voice-cloning fraud case is a reminder that resilience depends on workflow design, escalation and evidence, not on asking staff to judge whether a voice sounds genuine.
Read the post →Office background noise hid a cloned voice from our own detector. The cause was how detectors average a call, not the model. Here is the test, the fix, and what to check in yours.
Read the post →The evidence is moving from theoretical threat to board-level risk, but many firms still test training and identity checks rather than the phone workflows attackers are targeting.
Read the post →Two stories, eleven days apart, that belong together, and the enforcement gap between them.
Read the post →An open-source app clones a voice in 646 languages from three seconds of audio, locally and free. The threat model just changed.
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