How Can Generative AI Be Used in Cybersecurity Training?

Traditional security tools rely on pre-built modules that quickly become outdated.

Here at Hoxhunt, we speak to countless security teams that spend hours creating customized training content...

But the process is time-consuming and resource-heavy.

That’s why Hoxhunt's security awareness training uses generative AI tools - and you should too.

47% of businesses are already using Gen AI for cyber risk detection and mitigation.

AI now means that cybersecurity professionals can generate real-time, customized training that aligns with security policies, employee behavior, and company culture.

Below we'll look at exactly how AI-powered cybersecurity training can make your security awareness training faster, smarter, and more effective.

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What is generative AI?

Generative AI refers to artificial intelligence systems that can create new content like text, images, music and code.

What sets generative AI systems apart is that instead of just analyzing or classifying existing data, they can produce original outputs that didn't previously exist.

The most prominent examples today (like ChatGPT) use large language models (LLMs) or diffusion models.

These systems learn patterns and relationships within their training data, enabling them to generate new content that maintains similar characteristics and follows learned patterns.

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How are threat actors using GenAI?

Generative AI tools are transforming the threat landscape.

The IBM X-Force Threat Intelligence Index 2024 found that GenAI capabilities facilitate upwards of a 99.5% reduction in the time needed to craft an effective phishing email.

And 85% of security professionals that witnessed an increase in cyber attacks over the past 12 months attribute the rise to bad actors using generative AI.

Threat actors can use generative AI to:

• Create more convincing phishing emails with fewer linguistic errors
• Generate malicious code at scale with less technical expertise
• Develop polymorphic malware that continuously changes its signature
• Craft personalized social engineering attacks using publicly available information

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Generative AI cybersecurity use cases

Generative AI may present a new wave of potential threats, but it can also be used to fight them too!

Security teams are now essentially in an arms race - fighting AI with AI. 

According to Forbes, 76% of enterprises have already prioritized AI and machine learning in their IT budgets...

With 58% of organizations feeling that AI-driven security systems give them a big edge in detecting and responding to threats.

Organizations are leveraging GenAI to:

• Automatically generate security policies and documentation.
• Create realistic phishing simulations that adapt to user behavior patterns for more effective training.
• Build more sophisticated threat hunting queries by translating natural language into complex search syntax.
• Generate secure code samples that follow best practices and avoid common vulnerabilities.

"Security teams need AI-driven tools that can help them focus on high-value tasks and strategic work, rather than getting bogged down in repetitive, low-value activities" - Petri Kuivala (CISO Advisor, Hoxhunt)

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Where does traditional cybersecurity training fall short?

Every company faces the same challenge...

How do you train employees on cybersecurity practices without losing attention?

Security awareness training usually follows one of two paths:

• 'Off-the-shelf' training modules: Generic, outdated, and often misaligned with company policies.
• Custom-built training: Time-consuming, expensive, and hard to scale.

Most cybersecurity training programs tend to miss the mark.

Content often ends up being too generic and causes employees to tune out because it’s not engaging.

Generative AI fixes these problems by making security awareness training adaptive, personalized, and instantly customizable.

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How generative AI can be used in your cybersecurity training

The cybersecurity landscape is evolving at a rapid pace.

This leaves organizations facing an unprecedented challenge: how do you stay ahead of sophisticated threats and ensuring their teams are adequately trained to respond to them?

This is why we use AI - to make training more personalized, engaging, and up-to-date with ever-evolving threats.

In this section, we'll look at in-house AI strategies and tools without having to switch to a new vendor.

Creating content

• Infographics: Tools like Piktochart can help create professional-looking infographics quickly, making complex cybersecurity concepts more engaging and accessible1.
• Audio content: Use tools like Suno to create catchy security awareness songs. This can be an innovative way to engage employees and make training more memorable1.
• Video production: AI-powered video creation tools such as Synthesia or HeyGen allow you to turn scripts into videos without needing a studio. These tools also support video translation and voice-overs with platforms like ElevenLabs.
• Use existing data analytics tools to identify areas where employees need more training. Then, manually create personalized modules based on these insights, incorporating AI-generated content where possible.

Structuring and writing training content

• Large Language Models (LLMs) like ChatGPT are invaluable for structuring lessons and crafting content.
• They can help set learning objectives, flesh out training materials, and even assist in writing internal communication posts for platforms like Slack or Teams.
• The key is to use these tools to enhance human creativity rather than replace it.

Improving and personalizing simulations

• Simulated scenarios: Use AI to generate realistic phishing emails or scenarios that mimic real-world threats. This can be done by creating scripts that mimic real phishing attempts and testing employees' responses.
• Personalized training: AI can help tailor training content to individual employees based on their roles or past performance, making training more effective and relevant.
• Phishing simulator: You could even create your own phishing simulator tool using a platform like ChatGPT to generate more personalized, up-to-date simulations to send to employees. Or, look at developing in-house scripts or tools that can generate these scenarios based on real-world threats. This can be done by leveraging open-source AI frameworks or by collaborating with internal AI teams.

Note: Given the rapid pace of AI advancements, you'll want to regularly revisit and reassess AI tools to get the most out of their latest capabilities.

Threat intelligence and analysis

• AI can be used to analyze and generate threat intelligence reports, highlighting emerging threats and vulnerabilities.
• This information can be used to create targeted training content that addresses current security challenges.
  

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Implementation steps

1. Identify training needs: Use existing data to pinpoint areas where employees need more training.
2. Develop scenarios: Create realistic attack scenarios manually or using open-source AI tools.
3. Implement feedback loop: Set up a system for providing real-time feedback during training exercises.
4. Simulate threats: Use controlled environments to simulate complex cyber threats.
5. Streamline tasks: Use AI insights to prioritize and streamline routine security tasks manually.

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What can you expect from an AI-driven cybersecurity training solution?

AI-generated, custom security modules

Every company has unique security policies.

But training materials often fail to reflect specific security operations and attack patterns that employees should recognize.

With non-customizable content, you run the risk of confusing employees with mixed messages about security that don’t align with policies or the work environment.

AI-powered tools can create relevant, interactive training modules in minutes so that security teams don't need to manually edit training modules.

How it works:

• AI analyzes cybersecurity systems, policies, and previous security incidents.
• It generates real-time analysis of threat landscape trends.
• It creates tailored recommendations based on human analysts' insights and actual datasets.
• With Generative AI models, you can modify existing content and align it with company policies in seconds.

How we do this at Hoxhunt:

• Plug in existing policies to generate content.
• Employees receive accurate, relevant, and company-specific training.
• Training modules reinforce company security posture.
• Security teams can focus on proactive measures instead of repetitive tasks.

Adaptive phishing simulations based on employee behavior

Phishing remains one of the biggest cyber threats.

Your standard phishing training, however, usually follows a static format.

Employees receive generic phishing attempts that don’t reflect real-world attacks.

With AI-driven security solutions, phishing simulations can adapt to the latest cyber threats in real time.

How it works:

• AI analyzes employee behavior during phishing attack simulations.
• If an employee falls for a phishing email, AI automatically adjusts future training.
• AI-generated simulations mimic real-life phishing attempts based on advanced threat detection.

How we do this at Hoxhunt:

• AI analyzes real phishing attempts - looking at things like sender behavior and attack vectors.
• Personalized, relevant simulations get sent to employees based in their role, location etc
• Training modules adapt based on how employees react to simulations.
• When employees miss or click phishing simulations, AI customizes future training to match their weak points.
• Security teams can automate their simulated phishing campaigns so that it runs on autopilot.
• Employees are always being tested at the edge of their ability - not too hard, not too easy - to prepare them for real threats.

AI-generated training in multiple languages

Global companies face another major challenge...

How do you train employees in different languages while keeping security messaging consistent?

Traditional cybersecurity training requires manual translation, which is slow and expensive.

AI translations aren't just fast - they ensure that the message stays consistent across regions, so all employees receive localized security training that matches company policies

How it works:

• AI automates language translations using neural networks and natural language processing.
• It maintains context across different languages without losing accuracy.
• Employees receive training content in their preferred language.

How we do this at Hoxhunt:

• AI translates training into 35+ languages instantly.
• Employees receive company-specific cybersecurity training in their own language.
• Hoxhunt's AI-powered systems can add language variants in minutes instead of weeks.

AI-powered security incident response training

A cyber attack can happen at any moment.

The faster a company responds to a breach, the less damage it suffers.

But security teams often struggle with slow response times, a lack of automated attack simulations and heavy reliance on human intervention.

AI-driven automation allows us to automate the creation of real-time incident response training, which can simulate the latest attack methods to ensure employees are always prepared for future threats

How it works:

• AI analyzes previous security incidents to generate attack simulations.
• It teaches employees how to respond to zero-day attacks and advanced techniques.
• AI creates interactive training scenarios based on real threats.

How we do this at Hoxhunt:

• AI-generated attack simulations test employees on threat detection, response strategies, and cybersecurity defenses.
• Simulations constantly adapt to the 100,000+ real threats reported through the Hoxhunt network to keep your employees ahead of the latest attack methods.
• Hoxhunt takes existing training, modifies it instantly, and creates new attack scenarios based on real-world attacker behavior.

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The future of AI-powered training

Generative AI is redefining security awareness and phishing training.

Companies that embrace AI-driven security solutions will:

• Automate routine tasks in cybersecurity training
• Reduce false positives in phishing detection
• Enhance their cybersecurity strategy with real-world attack simulations
• Quickly adapt to evolving threats

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Generative AI for cybersecurity FAQs

What is Generative AI, and how does it apply to cybersecurity training?

Generative AI refers to AI models that can create new content such as text, images, or code, based on patterns learned from large datasets.

In cybersecurity training, it can be used to create dynamic, tailored content for training modules, generate realistic phishing simulations, and automate responses to evolving threats, making training more relevant and personalized.

Will Generative AI replace human cybersecurity professionals?

No, generative AI is not designed to replace human expertise.

Instead, it serves as a critical tool to assist cybersecurity professionals by automating time-consuming tasks, allowing them to focus on more strategic responsibilities.

The role of human cybersecurity professionals is still essential for interpreting AI-generated data and making informed decisions to mitigate risks. AI today is like an intern or junior developer, you need to review the work!

Can Generative AI detect new threats or vulnerabilities?

Yes, generative AI can analyze vast datasets of cybersecurity incidents and network traffic to identify potential attack vectors and vulnerabilities that may be overlooked by traditional methods.

How does Generative AI improve cybersecurity training over traditional methods?

Traditional cybersecurity training often uses static, one-size-fits-all modules that can become outdated and irrelevant to real-time threats.

Generative AI allows for adaptive learning, where training content evolves based on employee behavior, their role and job environment, industry-specific threats, and real-world attack data.

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_Sources

^{GenAI as a Cybersecurity Tool – US Signal
Threat Intelligence Report – IBM
AI vs. AI: Battle for Cybersecurity’s Future – Bank Info Security
76% of Enterprises Prioritize AI and Machine Learning in IT Budgets – Forbes
The Latest Phishing Statistics – AAG IT
Study Finds Increase in Cybersecurity Attacks Fueled by Generative AI – Security Magazine}