The Dark Side of Artificial Intelligence: The Threat of Unrestricted Language Models to the Encryption Industry

With the rapid development of artificial intelligence technology, advanced models from the GPT series to Gemini are profoundly changing our way of life. However, this technological advancement also brings potential risks, especially with the emergence of unrestricted or malicious large language models.

Unrestricted language models refer to those specifically designed or modified to bypass the built-in safety mechanisms and ethical constraints of mainstream models. Although mainstream model developers invest significant resources to prevent misuse, some individuals or organizations, driven by malicious intent, begin to seek or develop unrestricted models. This article will explore the potential threats posed by such models in the encryption industry, as well as the associated security challenges and response strategies.

The Dangers of Unrestricted Language Models

These models make it easy to implement malicious tasks that originally required specialized skills. Attackers can obtain the weights and code of open-source models, and then fine-tune them using datasets containing malicious content, thereby creating customized attack tools. This practice brings multiple risks:

1. Attackers can customize models targeting specific goals to generate more deceptive content.
2. The model can be used to quickly generate variants of phishing website code and customize scam copy.
3. The accessibility of open-source models has fostered the formation of an underground AI ecosystem, providing a breeding ground for illegal activities.

Typical Unrestricted Language Model

WormGPT: Dark version of GPT

WormGPT is a malicious language model available for public sale, claiming to have no ethical constraints. It is based on an open-source model and trained on a large dataset related to malware. Its main uses include generating realistic business email intrusion attacks and phishing emails. In the encryption field, it may be used for:

• Generate phishing information, impersonating exchanges or project parties to induce users to disclose their private keys.
• Assist in writing malicious code for stealing wallet files, monitoring clipboard, etc.
• Drive automated scams, guiding victims to participate in false projects.

DarkBERT: Dark Web Content Analysis Tool

DarkBERT is a language model trained on dark web data, originally intended to help researchers and law enforcement agencies analyze dark web activities. However, if misused, it could pose serious threats:

• Implement precise scams by utilizing collected user and project information.
• Copy the coin theft and money laundering strategies from the dark web.

FraudGPT: Online Fraud Tool

FraudGPT is referred to as the upgraded version of WormGPT, with more comprehensive features. In the encryption field, it may be used for:

• Counterfeit encryption projects, generating fake white papers and marketing materials.
• Batch generate phishing pages that mimic the interfaces of well-known exchanges and wallets.
• Engage in social media shill activities to promote scam tokens or discredit competing projects.
• Implement social engineering attacks to induce users to leak sensitive information.

GhostGPT: An AI assistant without ethical constraints

GhostGPT is explicitly positioned as a chat bot without ethical restrictions. In the encryption field, it may be used for:

• Generate highly realistic phishing emails that impersonate exchanges to issue false notices.
• Generate smart contract code with hidden backdoors for fraud or attacks on DeFi protocols.
• Create malware with morphing capabilities to steal wallet information.
• Deploy social platform bots to lure users into participating in false projects.
• Combine with other AI tools to generate deepfake content for fraud.

Venice.ai: Potential uncensored access risks

Venice.ai provides access to various language models, including some with fewer restrictions. While it aims to offer an open AI experience, it may also be subject to misuse:

• Bypass censorship to generate malicious content.
• Lower the threshold for prompt engineering, making it easier for attackers to obtain restricted outputs.
• Accelerate the iteration and optimization of attack scripts.

Coping Strategies

In the face of the threats posed by unrestricted language models, all parties in the security ecosystem need to work together.

1. Increase investment in detection technology and develop tools that can identify and intercept AI-generated malicious content.
2. Enhance the model's anti-jailbreak capabilities and explore watermarking and tracing mechanisms.
3. Establish sound ethical standards and regulatory mechanisms to limit the development and use of malicious models from the source.

The emergence of unrestricted language models marks a new challenge for cybersecurity. Only through joint efforts from all parties can we effectively address these emerging threats and ensure the healthy development of the encryption industry.