Security Awareness Generated Instantly With AI
Secure behavior management, end to end. Measure the risk, generate the training from what actually failed, then re-test to prove it changed.
Point the platform at your own policies and procedures and it generates the training. Run a simulation and it generates the micro-module for whatever broke. Or author your own from a blank objective. Same platform, same engagement data, all three stages: measure the risk, train against what you find, then re-test to prove it changed.
OSES™ Behave. The training stage of the Breacher.ai platform.
The module builder. Start from a policy, from a simulation result, or from a blank objective.
Describe it in plain language. The platform builds it.
The baseline the training is generated from has to come from somewhere. You describe the scenario in a sentence and the concierge assembles the campaign behind it.
The concierge drafts the playbook, assigns the persona, selects or clones the voice, places the call, and handles the inbound callback. Every object it creates stays editable, including the prompt behind the agent.
Every channel an attacker uses
Voice phishing and callback handling, deepfake video and live avatars on Teams, Zoom, and Meet, QR codes, email, SMS, chat, and calendar invitations. One campaign that crosses channels rather than seven disconnected tests.
Built in minutes, not a sprint
A scenario described in a sentence becomes a playbook with a goal, a persona, and the channel sequence to carry it. Your team builds and edits it directly, with no scenario request queue and no professional services engagement.
Consent before any likeness
Consent and scoping are agreed in writing before an executive voice or likeness is built, every engagement runs under signed authorization, and generated voice and video are handled with zero retention.
What it looks like from the other side of the call. A synthetic executive joins the Teams meeting and holds the pretext while the target tries to verify mid-conversation.
A content library cannot teach what your process got wrong
Awareness catalogues are written months in advance for a general audience, assigned on a calendar, and completed by people who were never tested on the thing the module covers. Nothing in that loop is connected to your organization.
Written before your exposure was known
A library is authored for a general audience long before anyone measured how your finance function handles an out-of-band approval or how your help desk verifies a caller. The content cannot reference a failure that had not been observed when it was written.
Assigned on a calendar, not on a finding
Quarterly assignment puts the module in front of people at the moment least connected to the behavior it targets. The failure happened in a live approval chain. The training arrives eleven weeks later, out of context, to everyone equally.
Measured by completion, not by change
Ninety-eight percent completion tells you the content was delivered. It says nothing about whether the wire still gets approved on a single voice call. Without a re-test on the same scenario, there is no reading to compare against.
Three ways in. No content library.
Every module is generated against something real: your written procedure, a failure the simulation recorded, or an objective you define yourself.
Upload the wire approval procedure, the help desk verification standard, the vendor onboarding policy. The platform reads it and produces training that teaches your procedure in your context, using your terminology, your named systems, and your escalation paths. It trains the verification step your policy already requires.
When a simulation finds that finance approved on a single voice call, the micro-module is built against that specific failure and delivered to the people it happened to. Training is triggered by the engagement rather than by a quarterly schedule, and it is scoped to the procedure that broke rather than the general topic.
Start from a blank objective and author the module yourself. Set the learning outcome, the audience, and the scenario, and use the platform to draft and structure it. Branded to your organization with no vendor watermarks, and sitting in the same dataset as generated modules. Useful for onboarding and regulatory content.
Why it sits on one platform
Most programs stitch this together from three vendors: a simulation tool, a training catalogue, and a survey that claims to score the result. Nothing connects them, so nothing can prove the training worked. OSES™ runs the measurement, the training, and the re-test on one engagement dataset.
The engine running a campaign end to end: the channel sequence, the agent handling the call, and what each target did with it recorded at every step.
Training without a re-test is a completion rate. The re-test is part of the platform, not a separate purchase, and it runs on the same scenario and population as the baseline so the two readings are comparable. Results leave through the REST API, webhooks, and SCORM export, so the evidence lands in the LMS and reporting stack you already run. See how the measurement stage works on the simulation platform, or how a deepfake simulation establishes the baseline.
Assigned versus generated
The same hour of employee time, spent on a general topic or on the procedure your own engagement data says is failing.
Built for a behavior program, not a content budget
Secure behavior management is the category Gartner names as the successor to human risk management. What the shift asks for is a measurement, an intervention, and a second measurement.
Risk based security training
Assignment follows measured exposure rather than headcount. The baseline shows which procedures failed and where, and training is routed to those roles at the depth the finding justifies. Populations with no measured failure on a procedure do not get a module for it.
Behavior based security training
The unit of training is a procedure step, not a topic. A module teaches the callback your standard requires or the identity check your help desk skipped, and the result is read as a change in that behavior when the scenario is run again.
Evidence for the SBCP
A security behavior and culture program needs to report on behavior, and behavior needs a before and an after. Documentation covers the baseline, the training delivered against each finding, and the re-test result, reported organizationally with no named individuals and no department leaderboards.
Where a procedure failure has a number attached
Organizations with approval chains, verification standards, and a regulator who expects the standard to hold under pressure.
What people say after the simulation
The reaction is consistent, and it is why the training that follows lands. People who have just been fooled by a synthetic voice do not need convincing that the threat is real.
Users were surprised with how good the Deepfakes were, I'm really impressed. Really crazy talking to a Deepfake.
I was expecting a Demo, not an episode of Black Mirror. This is really good, I'm surprised at how advanced it's gotten.
Kudos to your entire team. We haven't even seen the report and the whole company is talking about the risks of voice cloning. It's been a huge win for us already.
The training was well-structured, clear, and provided valuable insights into the growing threat landscape associated with deepfakes.
What the measurement stage finds
The baseline the training gets generated from. Both engagements ran under signed authorization, and client names never appear in our public material.
A cloned voiceprint submitted against verbal verification controls, and what it revealed about the step-up path behind them.
Read the case study Agentic AIAutonomous agents driving synthetic media generation and delivery end to end, with no human operator in the loop.
Read the case studySecure behavior management, answered
What is secure behavior management?
Secure behavior management is the practice of measuring how people and processes actually behave under a realistic social engineering scenario, training against the specific failures that measurement finds, and then re-testing the same scenario to confirm the behavior changed. It differs from security awareness training in that the content is derived from a measured result rather than assigned from a catalogue, and the outcome is a change in a measured rate rather than a completion percentage.
What is a security behavior and culture program, and how does SBCP security work here?
A security behavior and culture program, or SBCP, moves the objective from awareness to observable behavior. SBCP security work therefore needs a measurement before the intervention, an intervention scoped to what the measurement found, and a second measurement afterwards. This platform runs all three on one engagement dataset, so the program reports a behavior change rather than an attendance record.
What makes this risk based security training?
Assignment is driven by measured exposure rather than by a calendar. A baseline simulation establishes which procedures failed, in which functions, and under which pretext. Training is then routed to the roles and individuals that finding applies to, at the depth the finding justifies. Populations with no measured failure on a procedure are not assigned a module for it.
How is behavior based security training different from a content library?
A library teaches the topic. Behavior based security training teaches the verification step your own procedure requires, at the point the procedure broke, to the person it broke for. The module is generated against your wire approval standard or your help desk identity check rather than against a general lesson on fraud, and the result is measured by re-running the scenario.
How does the platform generate training from our policies?
You supply the source document, such as a wire transfer approval procedure, a help desk identity verification standard, or a vendor onboarding policy. The platform reads it and produces a module that teaches that procedure in your organization's own terminology, with your roles, systems, and escalation paths reflected in the scenario. The output is training on the control you already wrote, rather than a general lesson on the topic.
What is a micro-module and when is one created?
A micro-module is a short piece of training scoped to a single procedure failure. It is created from a simulation result: when an engagement records that a specific verification step was skipped, the module is generated against that step and routed to the people and roles it applies to. Training is triggered by the failure rather than by a calendar, which is when retention is highest.
Can we build our own content instead?
Yes. You can start from a blank objective and author a module directly, setting the learning outcome, audience, and scenario yourself, with the platform drafting and structuring it. Modules you author sit in the same dataset as generated ones, so they carry the same delivery, tracking, and re-test mechanics. Most programs use a mix: generated modules for what simulations find, authored modules for onboarding and regulatory content.
How do we describe a simulation to the platform?
In plain language. The concierge takes a scenario described in a sentence and drafts the playbook behind it, assigning the persona, selecting or cloning the voice, placing the call, and handling the inbound callback. Channels include voice phishing, deepfake video and live avatars on Teams, QR codes, email, SMS, and calendar invitations. Everything it produces stays editable, including the prompt behind the agent, and consent and scoping are agreed in writing before any executive voice or likeness is built.
Can we push results into the systems we already use?
Yes. Everything the console does is available through the REST API, and campaign and outcome events fire as webhooks, so results can land in your LMS, SIEM, GRC platform, or reporting stack without anyone exporting a spreadsheet. Modules leave as SCORM for the same reason, and target populations can sync from Microsoft Entra ID, directory-only with no agent on an endpoint. If a system can accept a webhook or a REST call, it can take this data.
How is this different from security awareness training software?
Awareness platforms give you a content library and a dashboard, and measure whether the content was completed. This measures whether behavior changed. The distinction that matters operationally is the re-test: the same scenario is run again against the same population after training, and the change between the two readings is reported. Completion rates tell you the training was delivered. A re-test delta tells you it worked.
Does this replace our existing awareness program?
Not necessarily. Many organizations keep an existing catalogue for broad annual compliance coverage and use this for the specific behaviors that carry real financial exposure, such as payment approval, credential reset, and vendor verification. Those are the procedures where a measured failure has a dollar value attached, and where a completion rate is least informative.
What evidence do we get for auditors and insurers?
Third-party assessment documentation covering the baseline engagement, the training delivered against each finding, and the re-test result. Because the re-test is run on the same scenario and population, the documentation shows a measured change rather than an attendance record, which is the form of evidence auditors and cyber insurance underwriters increasingly ask for. Reporting is organizational, with no named individuals and no department leaderboards.
Bring a procedure. We will generate the module on the call.
Thirty minutes. Bring one real procedure document and we will build the training against it live, then show you what the re-test would measure.
Or see how the measurement stage works on the simulation platform.
support@breacher.ai
