The Achilles Heel of Large Language Models: FraudGPT, WormGPT and Constella’s Proactive Response to AI-Powered Cyber Threats

The capabilities of large language models (LLMs) have come into sharp focus recently, with applications ranging from generating complex and creative texts to mimicking human-like conversation creating AI-Powered Cyber Threats. However, this power isn’t without its shortcomings. The Achilles heel of these advanced AI models appears to be their potential misuse for scam creation, underlining the necessity of robust cybersecurity measures.

Emerging AI-driven threats, such as WormGPT and FraudGPT, have leveraged the capabilities of LLMs to aid in phishing and malware creation, posing new challenges to cybersecurity efforts. While these models usher in a new age of technological marvels, their potential exploitation by threat actors highlights the criticality of countering the threats they pose and protecting users from their misuse.

New Threat Landscape

Recent reports from cybersecurity forums and platforms, including the Security Boulevard, have detailed the use of models like WormGPT and FraudGPT. These LLMs are utilized to generate phishing emails and potentially malicious code, indicating a worrying trend towards the weaponization of AI for harmful purposes. The WormGPT model, purportedly based on the GPT-J architecture by EleutherAI, is believed to be trained on a wide array of data sources, with a focus on malware-related data.

Another threat, FraudGPT, is described as a tool capable of creating “undetectable malware” and uncovering websites vulnerable to credit card fraud. However, experts believe that the actual capabilities of these models may not be as high as advertised, and they may indeed be used more as tools to deceive less tech-savvy individuals.

Constella’s Response

In response to this concerning development, Constella is taking proactive steps to safeguard its user base. We are currently testing various LLMs, aiming to reproduce these potentially harmful tools in a controlled and secure environment. This approach enables us to gain deep insights into the mechanics of these AI models and understand how they may be employed for malicious purposes.

By replicating the potential threats, Constella aims to improve our security systems’ responsiveness and effectiveness. This initiative aligns with our commitment to staying one step ahead of cybercriminals, continually innovating, and reinforcing our users’ security.

The Way Forward

Understanding the dynamics of these new AI threats allows Constella to devise advanced protective strategies and reinforce our existing cybersecurity infrastructure. As a part of our continuous effort to ensure the safety of our users, we are investing in research and development to advance our AI-powered security measures.

While the current threat level from AI-powered tools like WormGPT and FraudGPT may not be as severe as some believe, it’s critical to anticipate and prepare for the potential advancements in this field. As such, Constella is committed to developing cutting-edge solutions to combat the evolving threats in the cyber landscape, upholding our promise to offer secure and reliable services to our users.

In conclusion, the potential misuse of LLMs for scam creation underscores the need for vigilance in the face of evolving cybersecurity threats. As AI continues to play a dual role as a cybersecurity tool and potential cyber threat, Constella remains committed to protecting our users, staying vigilant and prepared for whatever the future may hold.

Julio Casal

CIO & Founder

Identity Theft Botnet Infostealer Exposures Vs. Breach Exposures: A Comparative Analysis

In the realm of identity theft, a deep understanding of the types of threats and their unique implications is critical. Among these threats, two types of exposures frequently rise to prominence because of their capacity to cause substantial harm – Botnet Infostealer exposures and Identity data compromised following a Breach.

While both pose a considerable risk, there are key differences between them. This article delves into a comparative analysis based on four main distinguishing aspects: the target of the exposure, the inclusion of cookie theft, the scope of compromised credentials, and the distinction between risk and incident in device control.

1. Risk of Exposure: Essential Services Vs. Specific Platforms

Firstly, the nature of services compromised during an exposure significantly influences the risk and potential consequences.

In the case of Botnet Infostealer exposures, the targets often include essential services. These encompass institutions like Banks, payment platforms such as PayPal, and important authentication services like Google and Microsoft. The compromise of these services can lead to severe outcomes as they handle highly sensitive data and provide critical functions. For example, an attacker gaining access to a Google account could control a user’s email, cloud storage, location history, and linked devices.

On the contrary, Breach exposures usually pertain to services of lesser criticality. In recent years, we have not witnessed major leaks involving banking or payment systems such as Wells Fargo or PayPal being trafficked in the Dark Web. The same holds true for credentials from industry giants such as Google, Apple, or Facebook. Despite their immense user base and potential for misuse, substantial breaches involving these services have, thankfully, remained absent from darknet trading circles.

When inspecting the compromised data within a Botnet Infostealer package, one is struck by the prevalence of crucial services that are central to our financial wellbeing and digital lives. Such a package will typically include a number of credentials pertaining to various banking institutions and payment systems, alongside almost invariably present credentials from major platforms like Google, Facebook, or Apple. These constitute key components of our digital identities, underlining futher the severity of Botnet Infostealer exposures.

2. Inclusion of Cookie Theft: Circumventing Two-Factor Authentication

The second distinguishing feature lies in the method of access. Botnet Infostealers often incorporate cookie theft as part of their operations. Cookies can hold session tokens or other data that authenticate the user’s identity. If these cookies are stolen, an attacker can impersonate the user and bypass two-factor authentication systems. This opens up a potent avenue for unauthorized access to accounts, even those secured with extra precautions.

In contrast, conventional data breaches almost never involve cookie theft. The information exposed in these cases often includes usernames, passwords, and other personal details but does not usually provide a method to bypass two-factor authentication.

3. Volume of Compromised Credentials: Multiple Vs. Single

The number of credentials exposed in an attack is another key factor in assessing the potential impact. Botnet Infostealer exposures are more expansive, often compromising dozens of credentials from the same computer and, likely, the same person. This means that the attacker could gain access to multiple accounts across a range of services, significantly expanding the potential for damage.

In contrast, Breach exposures are more likely to result in the compromise of a single set of credentials for each user. Although this can still have serious implications, particularly if the exposed credentials are used across multiple services, the immediate impact is typically limited to the specific breached service.

4. Infostealer: A Manifested Incident vs. Breach Exposure: A Latent Risk

An Infostealer exposure is an infection that signifies an incident – a system has been actively compromised. In contrast, a breach exposure represents a risk, posing a potential threat of compromise but not inherently indicating an already occurred intrusion.

In a Botnet Infostealer scenario, the malware often provides the attacker with remote control over the compromised computer. This means that the criminal has the ability to not only steal sensitive data but also manipulate the infected device in various ways, potentially launching further attacks, installing more malware, or even using the infected device as a launchpad for attacks on other systems. Importantly, a Botnet Infostealer infection is not just a risk but an actual incident.

Risk, in this context, refers to the probability of a particular adverse event occurring and its potential impact. An incident, however, is the realization of that risk – the adverse event actually happening. Therefore, when a Botnet Infostealer compromises a system, it’s not a mere possibility of adverse impact; the adverse event has already occurred.

In contrast, conventional data breach scenarios do not typically result in the attacker gaining remote control over affected systems. Instead, these exposures often involve unauthorized access to data stored on a system, but without the ability to directly control or manipulate that system. Here, the risk primarily lies in the potential misuse of exposed data rather than active control of the system.

Conclusion: A Comparative Perspective

While both Botnet Infostealer exposures and Breach exposures pose considerable threats, the potential implications of the former are more profound. The compromise of essential services, cookie theft enabling the circumvention of two-factor authentication, exposure of multiple credentials, and the remote control of the device make Botnet Infostealer exposures an alarming cybersecurity concern.

Nonetheless, the comparison does not diminish the significance of breach exposures. Each type of exposure carries its own unique risks and requires a distinct approach to mitigation and prevention. Therefore, recognizing the differences and understanding the unique dynamics of each threat type is crucial for crafting effective cybersecurity strategies.

Julio Casal

CEO & Founder