Buyer’s Guide to Cybersecurity Awareness Training
Key Takeaways
- Cybersecurity awareness training is a primary security control, not a compliance requirement, and must be evaluated based on its ability to reduce human risk.
- The human element drives the majority of breaches, making behavior—not knowledge—the critical factor in security outcomes.
- Social engineering succeeds through emotional manipulation, requiring training that explicitly prepares users to recognize and respond to psychological triggers.
- Engagement is the mechanism of retention and behavior change, with narrative and storytelling significantly improving recall and real-world application.
- Monthly training is required to sustain effectiveness, with recent training shown to dramatically improve phishing reporting rates.
- Personalization is essential, as users vary widely in susceptibility and must be trained based on individual risk patterns and emotional triggers.
- Behavioral metrics matter more than activity metrics, with report rates, click rates, and response times providing meaningful indicators of risk.
- Simulated phishing must be dynamic and realistic, functioning as both a measurement tool and a learning mechanism.
- Many legacy programs fail because they prioritize compliance over outcomes, resulting in high completion rates but limited risk reduction.
- NINJIO aligns most closely with a behavior-driven model, integrating engagement, emotional intelligence, and continuous reinforcement into a cohesive system.
What is Cybersecurity Awareness Training?
Cybersecurity awareness training is the structured process of educating and conditioning employees to recognize, resist, and respond appropriately to cyber threats, particularly those that rely on social engineering and human interaction. At its most basic level, it aims to reduce risky behaviors such as clicking malicious links, disclosing sensitive information, or failing to report suspicious activity. However, in modern security environments, this definition is insufficient.
Effective cybersecurity awareness training is not simply an educational program. It is a behavioral control system within a broader Human Risk Management strategy. Rather than focusing solely on knowledge transfer, it must influence how individuals make decisions under pressure, uncertainty, and emotional manipulation. This includes preparing users to recognize not just what an attack looks like, but what it feels like while it is happening, and how to respond in real time.
As outlined throughout this guide, the most effective programs combine engagement, emotional intelligence, personalization, continuous reinforcement, and behavioral measurement into a unified system. When implemented correctly, cybersecurity awareness training becomes an operational layer of defense, reducing the likelihood of successful attacks, improving detection and reporting, and strengthening overall organizational resilience.
Executive Summary
Cybersecurity awareness training has shifted from a compliance requirement into a strategic security control that directly influences breach likelihood, attacker dwell time, and organizational resilience. Modern social engineering attacks are engineered to exploit predictable human responses using highly polished, AI-assisted communications that remove traditional indicators of fraud, which means that knowledge alone is insufficient and behavior under pressure becomes the decisive factor.
The modern buyer must evaluate platforms not by their content volume or completion rates, but by their ability to change behavior at scale, sustain that change over time, and demonstrate measurable improvements in reporting, detection, and response. This requires a system that integrates engagement, emotional intelligence, adaptive simulations, and behavioral analytics into a continuous learning loop.
This level of cybersecurity awareness training, when combined with your other human-centric controls, becomes the foundation of a Human Risk Management program.
Social Engineering in Cyber Risk
Most successful cyberattacks do not begin with technical failure. They begin when a person is persuaded to act in a social engineering attack. That is why the human layer remains both the largest vulnerability and the most scalable control in cybersecurity. Verizon’s 2025 Data Breach Investigations Report found that the human element is involved in about 60% of breaches, reinforcing that attackers consistently rely on human behavior as a primary path to compromise. Social engineering has been a reliable tool for cybercriminals for years, and they show no signs of abandoning it.
What makes this especially important is that attackers are not simply exploiting a lack of knowledge. They are exploiting how people make decisions under enticement, coercion, or pressure. Research on phishing design shows that urgency cues are deliberately used to hinder rational evaluation and increase compliance, which helps explain why employees can recognize phishing concepts in theory yet still make risky choices in the moment.
This needs to define the role of cybersecurity awareness training within the Human Risk Management program and overall security posture. It is not enough to teach people what phishing looks like. Training must prepare people for what manipulation feels like while it is happening so they can recognize a social engineering attack in progress. That requires a training approach grounded in behavioral science and learning theory rather than one-time information transfer. The academic body of research supports this shift: a review in Nature Reviews Psychology identifies spacing and retrieval practice as especially effective strategies for improving long-term retention, yet too many rely on annual awareness training sessions and hope for the best.
Cybersecurity-specific research points in the same direction. Recent work in MIS Quarterly argues that phishing simulations can function not only as measurement tools but also as learning opportunities, especially when they include post-simulation feedback rather than standing alone as tests. The human risk management programs that work are those that create a feedback look between simulation and training tailored to each user.
The business case is equally strong. IBM reported that the global average cost of a data breach reached $4.88 million in 2024 and the 2025 Allianz Risk Barometer found that cyber incidents were the top business risk for the fifth year in a row, and by the largest margin ever. When social engineering drives the majority of that risk, it’s clear that organizations need training programs that do more than satisfy compliance checklists.
Taken together, the evidence supports a straightforward conclusion: cybersecurity awareness training should function as a behavior-change catalyst within the broader human risk management program. It should continuously teach, test, and reinforce decision-making under realistic conditions. Programs that fail to do that do not materially reduce risk.
Emotional Manipulation Drives Social Engineering
A growing body of cybersecurity and behavioral research shows that social engineering attacks are not random acts of deception, but highly structured manipulations of predictable human responses. Rather than relying solely on technical sophistication or user ignorance, attackers exploit cognitive biases and emotional triggers that shape how individuals interpret risk, trust, and urgency in real time.
These emotional drivers consistently appear across phishing, vishing, business email compromise, and emerging AI-enabled attack patterns. Research demonstrates that these triggers can override rational decision-making, compress response time, and increase the likelihood of error.
Understanding these drivers is critical because they represent the mechanism through which attacks succeed. Training that does not explicitly address them may increase awareness at a conceptual level, but it does not prepare users for the psychological conditions under which real attacks occur. And that does not contribute to a Human Risk Management program in the way that the threat landscape demands.
The Seven Emotional Exploits in Manipulation
Below are seven commonly observed emotional drivers used by bad actors in social engineering attacks.
Fear
Fear is one of the most powerful drivers in social engineering because it directly impacts cognitive processing, narrowing attention and increasing the likelihood of impulsive action. Attackers frequently use threats such as account compromise, legal consequences, or financial loss to trigger immediate action.
Experimental research shows that emotionally charged phishing messages, particularly those inducing stress or anxiety, are associated with increased decision errors and reduced detection accuracy.
Urgency
Urgency reduces the time available for evaluation, forcing individuals to rely on instinct rather than analysis. This is particularly effective because humans often equate speed with importance in professional environments.
Research into phishing design confirms that urgency cues are deliberately embedded in messages to bypass rational scrutiny and increase the chances the victim will act before recognizing the attack.
Obedience
Authority-based manipulation exploits the human tendency to comply with perceived figures of power or legitimacy. Messages impersonating executives, IT staff, or external authorities are particularly effective because they align with organizational or societal hierarchies and expectations.
Classic behavioral research demonstrates that individuals will comply with authority even when doing so conflicts with their own judgment, a phenomenon repeatedly validated in both psychological and cybersecurity contexts.
Curiosity
Curiosity-driven attacks leverage the human desire for information, novelty, or insider knowledge. These attacks often present intriguing or unexpected content that encourages exploration, such as confidential documents or breaking news.
Behavioral research shows that curiosity can override caution, particularly when information appears relevant or personalized, increasing the likelihood of interaction with malicious content.
Opportunity
Opportunity-based manipulation appeals to perceived gain, advantage, or access. These attacks often promise rewards, exclusive access, or beneficial outcomes, creating a perceived upside that justifies risk-taking behavior.
Studies in behavioral economics show that perceived gains can distort risk evaluation, leading individuals to engage in actions they would otherwise avoid when no reward is present.
Sociality
Social drivers exploit the human tendency to trust familiar people, align with group behavior, and respond positively to perceived relationships. These attacks often mimic colleagues, partners, or known contacts to establish credibility. They appeal to our human desire, as social animals, for belonging.
Research on social engineering highlights that trust, familiarity, and social proof significantly increase the likelihood of compliance, as individuals are predisposed to believe and respond to those within their perceived network.
Greed
Greed-based attacks leverage financial incentives or material gain to override caution. These include prize notifications, investment opportunities, or financial windfalls.
Empirical observations show that reward-based lures are particularly effective because they create a strong motivational pull, often leading individuals to act before verifying legitimacy.
Why This Matters for Cybersecurity Awareness Training
Across all seven emotional drivers of social engineering, the common pattern is clear: social engineering succeeds by exploiting predictable human responses, not by defeating technical controls. These emotional triggers temporarily suspend critical thinking, making even trained users vulnerable in the moment.
For this reason, effective cybersecurity awareness training must move beyond static instruction and instead focus on:
- Recognizing emotional manipulation in real time
- Building awareness of internal decision-making signals
- Reinforcing correct responses through repeated exposure
- Simulating realistic attack conditions
That’s how we take a cybersecurity awareness training program from a compliance checkbox to part of a Human Risk Management program.
Why Traditional Training Programs Fail
Traditional awareness training programs fail because they are designed for compliance tracking rather than the behavioral change that reduces cyber risk. They rely on infrequent delivery, generic content, and passive learning formats, which leads to disengagement, low retention, and minimal real-world application.
Employees complete training without internalizing it, and when faced with a realistic attack, they respond instinctively rather than analytically. This gap between knowledge and action is where most breaches occur.
Approaches to Cybersecurity Awareness Training
| Dimension | Ineffective (Legacy/Compliance-Driven) | Effective (Behavior-Driven) |
| Primary Goal | Check compliance boxes | Reduce human risk and improve behavior |
| Training Cadence | Annual or quarterly sessions | Continuous, monthly reinforcement |
| Content Style | Generic, slide-based, low engagement | Narrative, scenario-based, high engagement |
| Focus Area | Knowledge transfer | Decision-making under pressure |
| Emotional Context | Ignored or minimal | Explicitly addressed and trained |
| Personalization | One-size-fits-all | Adaptive based on user behavior and risk |
| Phishing Simulations | Static templates | Dynamic, realistic, evolving scenarios |
| User Feedback | Limited or delayed | Immediate, contextual coaching |
| Metrics Tracked | Completion rates, quiz scores | Report rates, click rates, time-to-report |
| Outcome | High completion, low impact | Measurable behavior change and risk reduction |
Many ineffective, legacy programs are predicated on the requirements laid out by insurance policies that organizations take out against the financial risks posed by cyberattacks. But these are unreliable – 44% of cyber insurance claims were denied in 2023, underscoring the fact that even accepting an ineffective program to placate an underwriter isn’t the safe bet.
Engagement as a Security Control
Engagement with security awareness training material is not a nice-to-have. It is the mechanism that determines whether users retain and apply what they learn when faced with a real attack. Research shows that phishing susceptibility is driven less by lack of knowledge and more by how individuals process information under pressure, often relying on fast, intuitive thinking rather than deliberate analysis.
This means training must create retrievable mental models, not just deliver information.
Narrative and storytelling are uniquely effective at building those mental models because they align with how human memory works. Emotionally engaging, story-based content is more likely to be encoded deeply and recalled under stress, improving decision-making in real-world scenarios. In contrast, generic, compliance-style modules produce shallow learning that decays quickly and fails to influence behavior when it matters.
Effective programs therefore use storytelling not as entertainment, but as a structured learning tool, combining narrative engagement with reinforcement and feedback. Research on psychology shows behaviors improve when paired with repeated exposure and feedback loops. The result is training that is not only remembered, but applied, which is the outcome that ultimately reduces risk.
Monthly Training as Operational Cadence
Monthly cybersecurity awareness training is a requirement grounded in how humans learn, forget, and apply information under pressure. Research in learning science consistently shows that knowledge decays rapidly without reinforcement, and that spaced repetition is one of the most effective methods for sustaining retention over time.
Infrequent training, such as annual or quarterly programs, fails to counteract this decay, resulting in users who may recognize concepts in theory but cannot reliably apply them in real-world scenarios.
This is reinforced by empirical cybersecurity data. The 2025 Verizon DBIR cited research finding that users who had received training within the previous 30 days were four times more likely to report phishing attempts, demonstrating a direct relationship between training recency and not just attack avoidance, but recognition and active defense.
This finding underscores that awareness is not static. It must be continuously refreshed to remain operationally effective in the face of evolving attack techniques.
Personalization and Dynamic Learning
Not all users are equally vulnerable, and not all attacks are equally effective, because susceptibility to social engineering is shaped by individual differences in cognition, experience, context, and emotional response patterns. Research in human-centered security shows that phishing susceptibility varies significantly across individuals based on factors such as attention, workload, prior exposure, and psychological traits, meaning that a uniform training approach cannot adequately address risk.
This variability is further reinforced by the role of emotional triggers, as different individuals respond more strongly to different drivers such as urgency, obedience, or opportunity, which directly affects how attacks succeed in practice.
Effective cybersecurity awareness training must therefore move beyond static, one-size-fits-all content and instead identify individual risk patterns, map them to emotional susceptibility, and deliver targeted interventions. Research shows that users are more likely to fall for attacks that align with their personal context and expectations, meaning that training must be equally contextual and adaptive to be effective. This requires platforms to continuously assess behavior through simulations, identify which types of lures or emotional triggers are most effective against each user, and adjust both training content and difficulty accordingly.
Critically, susceptibility is not fixed. Human behavior changes over time based on experience, reinforcement, fatigue, and evolving threat exposure. Learning science demonstrates that behavior improves through iterative practice and feedback but can also regress without continued reinforcement. The most effective programs therefore use personalized learning paths, dynamic phishing simulations, and evolving behavioral profiling to create a continuous feedback loop in which users are assessed, trained, retested, and refined over time. This transforms awareness training from a static curriculum into a responsive system that accounts for both individual differences and the changing nature of human susceptibility.
Measuring Resilience, Not Failure
Focusing on plain activity metrics such as completion rates or training attendance is insufficient because these measures capture compliance rather than actual behavioral change. Academic research shows that many security awareness programs remain overly focused on completion-based indicators, even though these do not reflect whether employees can recognize or respond to real threats in practice. As a result, organizations may believe their programs are effective while employees continue to exhibit risky behaviors, reinforcing the broader problem that activity metrics track inputs, not outcomes or real-world security performance.
Instead, organizations need to prioritize resilience-based metrics that directly measure how employees behave under realistic threat conditions presented in simulated phishing exercises, including:
Risky Outcomes
• Click rate – the percentage of trainees who click on a link in a simulated phishing email or vishing meeting.
• Average time to lure – how long it takes, on average, for someone in the organization to click on a simulated phishing link.
• Repeated Clickers – the share of trainees who repeatedly click on simulated phishing exercises.
Resilient Outcomes
• Report rate – the percentage of trainees who report a simulated phishing email or vishing meeting.
• Average time to report – how long it takes, on average, for someone in the organization to report a phishing simulation.
• Repeated Reporters – the share of trainees who repeatedly report simulated phishing exercises.
These behavioral indicators provide a clearer picture of whether training is actually reducing risk, with studies showing that improvements in detection and reporting correlate with stronger security outcomes and reduced incidents. Modern measurement frameworks emphasize that metrics like increased reporting rates and shorter report times are stronger signals of a healthy security culture and improved cybersecurity posture because they reflect active participation in defense rather than passive training completion.
Program Vendor Summaries
NINJIO
Client Likelihood to Recommend
• Gartner Peer Insights: 97%
• G2: 97%
NINJIO delivers cybersecurity awareness training through a behavior-driven methodology that integrates narrative storytelling, emotional susceptibility modeling, and dynamic phishing simulations into a continuous learning system. By focusing on engagement, personalization, and measurable behavior change, it differentiates itself as a platform designed not just to educate users, but to transform how they recognize and respond to social engineering attacks over time.
Good Fit For:
• Organizations prioritizing behavior change over compliance
• Teams seeking high engagement through storytelling and narrative
• Companies building a Human Risk Management program
• Buyers who want personalized training tied to emotional susceptibility
• Security leaders focused on measurable behavioral outcomes
Drawbacks:
• Less focused on broad compliance library depth than legacy platforms
• May require organizational alignment to fully leverage behavior-driven approach
• Not positioned as a general-purpose LMS replacement
KnowBe4
Client Likelihood to Recommend
• Gartner Peer Insights: 93%
• G2: 93%
KnowBe4 provides a comprehensive, enterprise-scale platform with a large content library, extensive integrations, and mature program management capabilities, making it a common choice for organizations prioritizing standardization. However, its approach is largely compliance-driven and content-centric, with less emphasis on emotional engagement, storytelling, and individualized behavioral transformation that reduces cyber risk.
Good Fit For:
• Large enterprises needing scale and standardization
• Organizations prioritizing content breadth and integrations
• Teams with strong focus on compliance requirements
• Buyers seeking a mature, widely adopted platform
Drawbacks:
• Training is often content-centric rather than behavior-driven
• Limited emphasis on emotional engagement and storytelling
• Personalization is less tied to behavioral or emotional factors
• Can result in high completion but limited real-world impact
Hoxhunt
Client Likelihood to Recommend
• Gartner Peer Insights: 98%
• G2: 96%
Hoxhunt emphasizes gamified learning and adaptive phishing simulations, using frequent interactions and feedback loops to drive user engagement and incremental improvement. This model is effective at building habits over time, but it relies more heavily on gamification and repetition than on deeper narrative-driven learning or explicit emotional susceptibility frameworks that underpin social engineering threats.
Good Fit For:
• Organizations that value gamification and user engagement
• Teams looking for frequent phishing simulations and feedback loops
• Buyers interested in habit-building through repetition
• Environments where user participation is a challenge
Drawbacks:
• Relies heavily on gamification over deeper narrative learning
• Less emphasis on explicit emotional susceptibility frameworks
• Engagement may not always translate to long-term behavioral understanding
• Training depth can be secondary to interaction frequency
Adaptive Security
Client Likelihood to Recommend
• Gartner Peer Insights: New Entrant
• G2: New Entrant
Adaptive Security focuses on modern, AI-driven attack simulations, including deepfakes, vishing, and multi-channel social engineering scenarios, positioning itself strongly for emerging threat environments. While its strength lies in realism and forward-looking attack coverage, its training model is more simulation-centric and less differentiated in terms of structured learning design and long-term behavioral reinforcement.
Good Fit For:
• Organizations focused on emerging threats like deepfakes and vishing
• Teams seeking AI-driven, multi-channel simulations
• Buyers prioritizing realism and forward-looking attack scenarios
• Security programs evolving toward next-generation threat models
Drawbacks:
• Training model is simulation-centric rather than learning-centric
• Less mature in structured learning design and reinforcement
• Limited differentiation in behavioral training methodology
• May lack depth in long-term behavior change frameworks
Arctic Wolf
Client Likelihood to Recommend
• Gartner Peer Insights: 99%
• G2: 93%
Arctic Wolf delivers cybersecurity awareness training as part of a broader managed security service model, emphasizing operational simplicity, guided program execution, and integration with its SOC and risk management offerings. This approach is valuable for organizations with limited internal resources, but the training itself is typically service-led rather than differentiated by a distinct learning or behavioral methodology.
Good Fit For:
• Organizations with limited internal security resources
• Teams seeking a fully managed awareness program
• Buyers already using Arctic Wolf for broader security services
• Environments prioritizing operational simplicity
Drawbacks:
• Training is service-led rather than methodology-driven
• Less differentiation in engagement and learning design
• Limited focus on behavioral science and personalization
• May not deliver deep behavior change at scale
Proofpoint
Client Likelihood to Recommend
• Gartner Peer Insights: 86%
• G2: 89%
Proofpoint delivers security awareness training as part of a broader security platform, tightly integrated with its email security and threat intelligence ecosystem. This approach is particularly valuable valuable for existing customers but less focused on the training effectiveness that actually reduces risk.
Good Fit For:
• Enterprises already invested in Proofpoint’s ecosystem
• Organizations prioritizing email security integration
• Teams seeking centralized security tooling
• Buyers focused on threat intelligence alignment
Drawbacks:
• Training is secondary to broader platform capabilities
• Less emphasis on engagement and behavioral transformation
• Limited differentiation in learning methodology
• May not deliver standalone training effectiveness
Huntress
Client Likelihood to Recommend
• Gartner Peer Insights: N/A
• G2: 91%
Huntress offers a managed approach to security awareness and phishing that prioritizes ease of deployment and ongoing administration, making it attractive for smaller teams or MSP-driven environments. However, its training capabilities are generally more streamlined and less differentiated in terms of depth, personalization, and behavioral science compared to platforms that focus specifically on awareness training as a core discipline.
Good Fit For:
• Small to mid-sized organizations or MSP-driven environments
• Teams seeking simple deployment and low overhead
• Buyers prioritizing managed phishing and awareness basics
• Organizations early in their security maturity journey
Drawbacks:
• Training capabilities are more limited in depth and sophistication
• Minimal focus on personalization and emotional drivers
• Less robust behavioral analytics and reporting
• Not designed for advanced Human Risk Management programs
Feature Comparison by Vendor
| Capability | NINJIO | KnowBe4 | Hoxhunt | Adaptive Security | Arctic Wolf | Proofpoint | Huntress |
|---|---|---|---|---|---|---|---|
| Training Philosophy | Behavior change | Compliance | Gamified | AI-driven | Managed | Ecosystem | Detection |
| Monthly Training | Yes | Optional | Yes | Yes | Yes | Optional | No |
| Emotional Drivers | Core focus | Limited | Partial | Partial | Limited | Limited | None |
| Personalization | High | Medium | High | High | Low | Medium | None |
| Simulated Phishing | Adaptive | Extensive | Advanced | Advanced | Moderate | Strong | Basic |
| Gamification | Light | Moderate | High | Low | None | Low | None |
| AI Enablement | Strong | Strong | Strong | Core | Limited | Strong | None |
| Behavioral Reporting | High | High | High | High | Medium | Low | Low |
| Compliance Coverage | High | High | Low | Moderate | High | High | Low |
Conclusion
When the majority of breaches involve the human element, cybersecurity awareness training cannot be treated as a supporting function. It is a primary control layer in modern security architecture, and it must be designed accordingly. Programs that rely on infrequent, generic, compliance-driven content will continue to produce the same outcome: high completion rates paired with persistently high human risk.
In contrast, organizations that treat awareness training as a continuous behavior change system, grounded in engagement, emotional intelligence, personalization, and behavioral analytics, create a workforce that is not only informed, but operationally resilient. This shift is measurable in real outcomes, including higher phishing reporting rates, faster response times, and reduced susceptibility to social engineering attacks.
Among current market options, NINJIO most closely aligns with this evolved model. Its integration of narrative-driven engagement, emotional susceptibility frameworks, adaptive simulations, and continuous reinforcement reflects a cohesive approach to changing behavior rather than simply delivering content. In a landscape where many platforms prioritize scale, compliance, or feature breadth, NINJIO differentiates by focusing on how people actually learn and respond under pressure. For organizations seeking to meaningfully reduce human risk and improve security outcomes, this alignment between training design and real-world attack dynamics is what ultimately defines effectiveness.
Frequently Asked Questions
Cybersecurity awareness training is a structured approach to teaching employees how to recognize, resist, and respond to cyber threats, especially social engineering attacks. Modern programs go beyond knowledge transfer and focus on shaping real-world decision-making and behavior under pressure.
Because the human element is involved in the majority of breaches, making employee behavior one of the biggest risk factors in security. Effective training reduces risky actions like clicking malicious links and improves detection and reporting of threats.
Most legacy programs focus on compliance rather than behavior change. They rely on infrequent, generic training that leads to low engagement, poor retention, and minimal impact when employees face real attacks.
They exploit emotional triggers like urgency, fear, curiosity, and opportunity to override rational thinking. Attackers manipulate how people make decisions in the moment, which is why training must prepare users for what an attack feels like, not just what it looks like.
They should prioritize programs that drive measurable behavior change through engagement, personalization, continuous reinforcement, and realistic phishing simulations. Metrics like reporting rates and response times matter more than completion rates.
Cybersecurity awareness training should be delivered continuously, with monthly reinforcement as a baseline. Frequent training improves retention and has been shown to significantly increase phishing reporting rates compared to infrequent, annual programs.
The most meaningful metrics are behavioral, not activity-based. These include phishing report rates, click rates, time to report, and repeated user behavior over time. Completion rates and quiz scores don’t reflect real-world risk reduction.
Personalization is critical because users have different risk levels and respond to different emotional triggers. Effective programs tailor training and simulations based on individual behavior and susceptibility patterns to reduce risk more effectively.
Yes, phishing simulations are essential. They serve as both a measurement tool and a learning mechanism, especially when paired with immediate feedback that reinforces correct behavior and improves future responses.
About NINJIO
NINJIO’s human risk management platform reduces cybersecurity risk through personalized security coaching, engaging awareness training, and adaptive testing. Our multi-pronged approach to risk mitigation focuses on the latest attack vectors to build employee knowledge and the behavioral science behind social engineering to sharpen users’ intuition. Our simulated phishing and coaching tools build a proprietary Emotional Susceptibility Profile for each user to identify their specific social engineering vulnerabilities and change behavior.
