ChatGPT impersonators reveal security vulnerability
ChatGPT, the popular AI-based large language model (LLM) app from OpenAI, has seen levels of user growth unique for many reasons. For one, it reached over a million users in five days of its release, a mark unmatched by even the most historically popular apps like Facebook and Spotify. Additionally, ChatGPT has seen near-immediate adoption in business contexts, as organizations seek to gain efficiencies in content creation, code generation, and other functional tasks.
But as businesses rush to take advantage of AI, so too do attackers. One notable way in which they do so is through unethical or malicious LLM apps.
Unfortunately, a recent spate of these malicious apps has introduced risk into an organization’s AI journey. And, the associated risk is not easily addressed with a single policy or solution. To unlock the value of AI without opening doors to data loss, security leaders need to rethink how they approach broader visibility and control of corporate applications.
Types of fraudulent "GPT" and their risk
Malicious LLM applications fall into multiple categories that present different flavors of risk, such as:
Fake apps impersonating real apps in order to trick users into downloading malware is hardly a new attack tactic. Attackers have been manipulating users into doing so for decades. But these ChatGPT-based attacks point to a larger problem.
The larger issue: Lack of application awareness
Lack of visibility into the applications that enter an organization's network results, naturally, in a lack of control — leaving companies vulnerable to fraudulent apps.
Almost any software can be distributed over the Internet or accessed through the cloud; this is the new normal. Employees are typically able to install non-approved applications on company devices in a matter of seconds.
Employees are also able to use all manner of cloud-hosted software-as-a-service (SaaS) apps. The use of unauthorized cloud-based services runs rampant throughout most large organizations; this phenomenon is known as shadow IT. Shadow IT is so prevalent that in one survey, 80% of employees reported using non-approved SaaS applications.
These risks are ongoing, but the danger increases when one particular type of app — in this case, AI-based LLMs — has so firmly entered the corporate zeitgeist. Well-meaning employees seeking to increase their efficiency may end up providing a foothold for attackers to enter their organizations' networks.
Solving application control
Cyber security awareness training has become core to organizational cyber resilience, but this is a technical problem and requires a technical solution.
For many years, firewalls inspected network traffic at layer 4, the transport layer. These firewalls were able to block traffic going to or coming from non-approved IP addresses or ports, and this prevented many attacks. However, classic firewalls are demonstrably insufficient for the modern era, since they lack awareness of layer 7, the application layer, and thus cannot determine which applications traffic is coming from.
Next-generation firewalls (NGFW) have this capability. They inspect traffic at layer 7 and can allow or deny based on the application of origin. This application awareness allows administrators to block potentially risky applications. If an application's data cannot get past the firewall, then it cannot introduce threats into the network.
However, like traditional firewalls, next-generation firewalls assume a self-contained, private internal network — not the IT environment of today, with applications and data spread across internal networks, private clouds, and public clouds. Modern networks are distributed and encompass SaaS applications, web applications, and remote use.
Therefore, organizations need cloud-based NGFW capabilities that can sit in front of both on-premise networks and the cloud.
But NGFWs on their own cannot deal with shadow IT. And by the time an NGFW detects malicious application usage, it may be too late. Application control has to be integrated with a cloud access security broker (CASB) to truly secure networks, devices, and users.
Along with other capabilities, CASBs discover shadow IT and give administrators the ability to remediate it. They can deploy URL filtering to ensure phishing sites and applications are not loaded, and that malware cannot connect to known bad web addresses for instructions from a command and control server. They can add approved applications to an allowlist, blocking all others. They can use anti-malware to identify malicious imitation software as it enters a network (whether on-premise or in the cloud).
Securing application use — today and tomorrow
ChatGPT started trending in 2023 and AI tools are likely to be released for years to come.
SaaS applications are mission-critical for workforce collaboration, however they are hard to keep secure. Cloudflare's CASB service gives comprehensive visibility and control over SaaS apps, so you can easily prevent data leaks and compliance violations. With Zero Trust security, block insider threats, Shadow IT, risky data sharing, and bad actors.
This article is part of a series on the latest trends and topics impacting today’s technology decision-makers.
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Learn more about how CASB works with the Simplifying the way we protect SaaS applications whitepaper.
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