Cyber Guru Phishing
Training Platform / Cyber Guru Phishing
Cyber Guru Phishing
Cyber Guru Phishing is an experiential anti-phishing training platform that uses cognitive automation to offer individual learning pathways that motivate people to recognise and report real attacks.
With its training techniques, special training methodology and experiential learning, Cyber Guru Phishing maximises training effectiveness in three specific areas: danger perception, readiness to act correctly and threat awareness.
Automation and Artificial Intelligence techniques also make the training programme completely autonomous in the realisation of customised training programmes and the scheduling of simulation campaigns, reducing management costs to zero.
Anti-phishing training with a personal trainer
To protect against the Phishing phenomenon, every organisation must inevitably invest in the human factor, training each user to recognise a Phishing or Smishing attack.
To develop maximum resilience, however, it is necessary to tailor training to the specific characteristics of each individual and their personal ability to resist cyber attacks.
For this reason, Cyber Guru’s Phishing simulation campaigns are customised, thanks to an artificial intelligence-based personal trainer, to the behavioural characteristics of each individual user. The user is subjected to simulated attacks with varying frequency, but on a continuous basis, which become increasingly complex and challenging.
To maximise training effectiveness, adaptive and automatic learning pathways, which are decided by the personal trainer based on the user’s performance, reproduce the real user experience by simulating the different attack strategies adopted by cyber criminals.
Simulations carried out
Features of Cyber Guru Phishing
- CONTINUOUS TRAINING
- INSTANT ERROR TRAINING
- REMEDIATION POLICIES
- REPORTING PROCEDURE
- MULTILINGUAL FORMAT
- ADAPTIVE PROCESS
- CUSTOM SIMULATIONS
- RISK GROUPS
- DIFFICULTY LEVELS
- LOCALISED TEMPLATES
- SaaS PLATFORM
- TURNKEY SERVICE
- AUTOMATED CAMPAIGNS
- PRE-LOADED TEMPLATES
- COMPREHENSIVE REPORTING
Adaptive and customised training
Simulations are automatically specialised on the basis of the user’s behavioural profile, which takes into account the individual’s ability to resist attacks.
Each time the user falls victim to a simulated attack, they receive a light training intervention to formally understand their mistake, but also to help them appreciate that they have made a mistake they could have avoided.
The adaptive process acts at various levels, automatically conditioning the selection of attack templates for each campaign and their distribution on the target. This selection is essentially based on some macro variables:
- user profile: based on the specific degree of resistance to attacks, the difficulty level to be used is chosen for each user and the periodicity of the next attack is determined.
- template ranking: the difficulty level of the attack is instead prepared by calculating not only static parameters, but also dynamic ones, such as observing the click-rate that template has amassed in that specific context.
Transform the Phishing experience into effective training
Each campaign will have a different composition from the previous and the next, with no need for human intervention. The learning algorithms adopted by the platform will be able to select attack templates, based on the criterion of maximum training effectiveness.
Simulated attacks are structured into campaigns, the result of an adaptive process that automatically determines the selection of ideal attack templates with respect to the development level of the training course.
If the user fails a simulation, and thus falls for the scam in the template, they immediately receive customised training content on the specificity of the scam in the attack template.
The reporting, available in a dashboard, goes far beyond the simple detection of the average Click-Rate, providing for advanced metrics to assess the risk and track its concrete reduction as the programme progresses.