VnI Labs

AI Phishing Protection

adminvnilabs — Tue, 24 Feb 2026 18:11:01 +0000

Protecting Your Business from AI-Generated Phishing Attacks: Advanced Techniques

Part 2 of our Phishing Protection Series
This article builds on the fundamentals covered in Part 1. If you haven’t read it yet, start here:
Read Part 1: Phishing Protection

In today’s digital landscape, phishing attacks have become increasingly sophisticated, mainly caused by the rise of AI-generated content. As these attacks continue to evolve, businesses need to stay ahead of the threats and implement effective solutions to prevent them. In this article, we will discuss the importance of custom model development for fraud and phishing detection, as well as alternative AI solutions for phishing prevention training.

The Rise of AI-Generated Phishing Attacks

Phishing attacks have long been a significant threat to businesses, but the emergence of AI-generated content has elevated them to a new level. Deepfake phishing scams utilise AI-generated audio or video to deceive victims into divulging sensitive information and are becoming increasingly prevalent. Additionally, AI-powered Gmail phishing attacks designed to mimic those from legitimate senders are also on the rise.

These attacks can be particularly effective in targeting businesses and individuals, as they often appear to originate from trusted sources. A 2024 IBM study revealed that 70% of surveyed businesses have fallen victim to a phishing attack, with the average cost per attack at $4.88 million.

The use of AI-generated content in phishing attacks makes them even more challenging to detect, as they can be designed to mimic the tone, style, and language of legitimate communications. This is where custom model development for fraud and phishing detection can be beneficial.

Custom Model Development for Fraud and Phishing Detection

Custom model development for fraud and phishing detection involves creating a machine learning model specifically designed to detect and prevent phishing attacks. The dataset used for model training consists of known phishing attacks and legitimate communications to recognize the patterns and characteristics of phishing threats.

The benefits of custom model development for businesses include improved detection rates and reduced false positives. By creating a model trained to your business’s specific needs, you can enhance the accuracy of your phishing detection and minimise the risk of false positives.

The process of developing a custom model has several steps: data collection, data preparation, model training, and model evaluation. This involves collecting a dataset of known phishing attacks and legitimate communications, and then training the model on this data to learn the patterns and characteristics of phishing attacks.

Once the model is trained, it can be continuously updated and maintained to stay ahead of evolving threats. This means regularly updating the model with new data and retraining it to ensure its continued effectiveness.

Using Open-Source AI for Phishing Detection

Recently, Large Language Models (LLMs) have been used for phishing email detection through their ability to recognise patterns. We advise using an open-source internally hosted model. This way, the internal business communications are not exposed to unnecessary vendor risks. Next, we will present two ways to achieve this.

The first, performance-limited but easy to implement approach, is integration of a specialised model for phishing detection from a known repository such as Hugging Face. A prominent example is PhishSense-1B, which has achieved an accuracy of 0.975 and a precision of 0.958. The open-source model can be hosted on local infrastructure – either using existing hardware or a company-controlled cloud.

For optimal performance, we recommend using a fine-tuned model. Ideally, it must be trained on a carefully curated dataset with company-specific examples comprising a balanced mix of phishing emails and legitimate, safe emails.

This proactive approach serves as a vital precaution against phishing attacks, allowing the model to develop a more nuanced understanding of the subtleties that distinguish malicious from harmless communications. To achieve this, we suggest starting with an existing open-source model that possesses a broad understanding of the English language, and then further fine-tuning it with targeted phishing email data to enhance its detection capabilities.

AI-Powered Phishing Protection Software

AI-powered phishing protection software is designed to detect and prevent phishing attacks in real-time. These software solutions use machine learning algorithms to analyse incoming emails and identify potential phishing attacks.

The features and capabilities of these software solutions include AI-driven phishing simulation platforms, which simulate phishing attacks to test employee awareness and response. They also include an AI-driven protection mechanism that blocks access to known phishing websites and prevents employees from accessing them.

Integrating these solutions with existing cybersecurity measures is essential to ensure their effectiveness. This involves integrating the software with existing email security solutions, such as spam filters and antivirus software, to ensure that all incoming emails are scanned for phishing threats.

AI-Powered Phishing Training Modules

Employee training is a vital component of any phishing prevention strategy. AI-powered phishing training modules educate employees on the risks of phishing attacks, empowering them to identify and prevent these threats. By leveraging these modules, organisations can enhance employee awareness and significantly reduce the risk of phishing attacks, ultimately strengthening their overall security posture.

Conclusion

In conclusion, protecting your business from AI-generated phishing attacks requires a comprehensive AI-powered protection approach. This includes custom model development, custom phishing training modules, and phishing protection software. Another possibility is to use open-source LLMs for phishing anomaly detection, which can be hosted as is or fine-tuned on proprietary data for extra performance. By implementing a set of these solutions, you can stay ahead of threats and protect your business from the risks of phishing attacks.

Frequently Asked Questions (FAQs)

Q1: How to train employees to identify AI-generated phishing?
AI-powered phishing training modules can be used to educate employees on the risks of phishing attacks, empowering them to identify and prevent these threats.

Q2: How can AI be used in phishing attacks?
AI can be used in phishing attacks to generate content that mimics legitimate communications, making it challenging to detect. AI-powered phishing attacks can also use deepfake technology to deceive victims.

Q3: Why do phishing emails generated by AI seem so real?
AI-generated phishing emails can be designed to mimic the tone, style, and language of legitimate communications, making them appear more convincing and real.

Q4: How to identify AI-generated phishing emails?
Unlike traditional phishing emails, the AI-generated ones are usually grammatically correct. But, they still have induced urgency and links as a way to catch a victim. A distinct characteristic of AI-generated phishing emails is unnatural monotonic tone.

Q5: How to stop AI-generated phishing attacks?
Educate employees on how to identify and report suspicious emails, and consider implementing user behaviour analytics to detect anomalies in user behaviour. Additionally, use two-factor authentication and implement anti-phishing measures such as sender policy framework (SPF), domain keys, and DMARC to prevent phishing emails from reaching users’ inboxes. Additionally, AI-powered phishing protection software can help identify threats through anomaly detection approaches.

Q6: How can open-source AI models be used to reduce phishing attacks?
Open-source AI models, such as PhishSense-1B, can be used to detect phishing attacks. Ideally, these should be hosted on internal infrastructure to avoid exposure of private internal communications.

Q7: How does fine-tuning increase the precision of LLMs for phishing detection?
Fine-tuning an open-source LLM on a business’s proprietary data allows it to develop a more nuanced understanding of the subtleties that distinguish malicious from harmless communications, increasing its precision for phishing detection.

Related Services

Open-Source AI

LLM Fine-Tuning

The post AI Phishing Protection appeared first on VnI Labs.

Phishing Protection

adminvnilabs — Tue, 27 Jan 2026 15:40:50 +0000

The Dangers of Phishing: Protecting Yourself from Cyber Threats

Part 1 of our Phishing Protection Series
This article introduces the core concepts of phishing and the essential steps to protect against it.
Continue to Part 2: AI Phishing Protection

Phishing is a type of cyber-attack that has become increasingly common in recent years. It involves tricking individuals into revealing sensitive information, such as passwords, credit card numbers, or personal data, by disguising itself as a legitimate email or message from a trusted source. In this article, we will discuss how to recognize phishing, protect yourself from phishing attacks, and what to do if you suspect or respond to a phishing email.

How to Recognize Phishing

Phishing attacks often appear to come from a trusted source, such as a healthcare provider, bank, online retailer, or social media platform. However, there are several red flags to look out for:

Urgency: Phishing emails often create a sense of urgency, claiming that your account will be closed or compromised if you don’t take action immediately.
Poor grammar and spelling: Legitimate companies typically have professional email templates and grammar. Phishing emails often contain typos and grammatical errors.
Suspicious links and attachments: Phishing emails may contain links or attachments that seem suspicious or out of place.
Request for sensitive information: Legitimate companies will never ask you to reveal sensitive information, such as passwords or credit card numbers, via email.

How to Protect Yourself from Phishing Attacks

Use strong passwords: Use unique, complex passwords for each account and consider using a password manager to keep track of them.
Enable two-factor authentication: Two-factor authentication adds an extra layer of security by requiring a code sent to your phone or a biometric scan in addition to your password.
Be cautious with links and attachments: Avoid clicking on links or opening attachments from unknown sources. Always float (hover) over links without clicking them to see the URL. This way, one can ensure that the link points to a safe location before clicking.
Keep your software up to date: Ensure that your operating system, browser, and other software are up to date with the latest security patches.

What to Do If You Suspect a Phishing Attack

If you suspect a phishing email, do not respond or click on any links. Instead:

Report the email: Report the email to the company or organization that it appears to be from, and to your email provider. Make a screenshot and send it to the support email, highlighting what raised your suspicion.
Delete the email: Immediately delete the email from your inbox and avoid opening any attachments or clicking on links.
Change your password: If you have already responded to the email or clicked on a link, change your password immediately and enable two-factor authentication. Additionally, clean the passwords of all accounts that share similar passwords. If needed, report those to the website’s support as well.

What to Do If You Responded to a Phishing Email

If you have already responded to a phishing email or clicked on a link, take the following steps:

Change your password: Change your password immediately and enable two-factor authentication.
Monitor your accounts: Closely monitor your accounts for any suspicious activity and report any issues to the relevant company or organization.
Seek professional help: If you are unsure about what to do or if you have already compromised your accounts, seek professional help from a cybersecurity expert.

How to Report Phishing

To report phishing, follow these steps:

Report to the company: Report the phishing email to the company or organization that it appears to be from.
Report to your email provider: Report the phishing email to your email provider, such as Gmail or Outlook.
Report to the authorities: Report the phishing email to the relevant authorities, such as the Ministry of Interior’s department against cybercrime in Bulgaria (Киберпрестъпност ГДБОП ), or you may navigate the appropriate EU member state institution on Europol’s “Report a cybercrime page“ (Report Cybercrime online | Europol).

Advanced Techniques to Prevent Phishing

In addition to the best practices outlined above, consider the following advanced techniques to prevent phishing:

Use an automatic phishing detection: Many email providers offer phishing filters that can detect and block suspicious emails.
Use a password manager: A password manager can help you generate and store unique, complex passwords for each account.
Use a virtual private network (VPN): A VPN can help protect your data when using public wireless (Wi-Fi) networks.
Stay informed: Stay up to date with the latest phishing scams and techniques to stay one step ahead of cyber attackers.

Additional Resources

The post Phishing Protection appeared first on VnI Labs.