By exploiting a flaw in OpenAI's code interpreter, a user managed to bypass restrictions and execute C and JavaScript code directly. This was achieved by crafting prompts that tricked the system into interpreting uploaded files as executable code, rather than just data. Essentially, the user disguised the code within specially formatted files, effectively hiding it from OpenAI's initial safety checks. This demonstrated a vulnerability in the interpreter's handling of uploaded files and its ability to distinguish between data and executable code. While the user demonstrated this with C and Javascript, the method theoretically could be extended to other languages, raising concerns about the security and control mechanisms within such AI coding environments.
The blog post details a vulnerability in the "todesktop" protocol handler, used by numerous applications and websites to open links directly in desktop applications. By crafting malicious links using this protocol, an attacker can execute arbitrary commands on a victim's machine simply by getting them to click the link. This affects any application that registers a custom todesktop handler without properly sanitizing user-supplied input, including popular chat platforms, email clients, and web browsers. This vulnerability exposes hundreds of millions of users to potential remote code execution attacks. The author demonstrates practical exploits against several popular applications, emphasizing the severity and widespread nature of this issue. They urge developers to immediately review and secure their implementations of the todesktop protocol handler.
Hacker News users discussed the practicality and ethics of the "todesktop" protocol, which allows websites to launch desktop apps. Several commenters pointed out existing similar functionalities like URL schemes and Progressive Web Apps (PWAs), questioning the novelty and necessity of todesktop. Concerns were raised about security implications, particularly the potential for malicious websites to exploit the protocol for unauthorized app launches. Some suggested that proper sandboxing and user confirmation could mitigate these risks, while others remained skeptical about the overall benefit outweighing the security concerns. The discussion also touched upon the potential for abuse by advertisers and the lack of clear benefits compared to existing solutions. A few commenters expressed interest in legitimate use cases, like streamlining workflows, but overall the sentiment leaned towards caution and skepticism due to the potential for malicious exploitation.
ForeverVM allows users to run AI-generated code persistently in isolated, stateful sandboxes called "Forever VMs." These VMs provide a dedicated execution environment that retains data and state between runs, enabling continuous operation and the development of dynamic, long-running AI agents. The platform simplifies the deployment and management of AI agents by abstracting away infrastructure complexities, offering a web interface for control, and providing features like scheduling, background execution, and API access. This allows developers to focus on building and interacting with their agents rather than managing server infrastructure.
HN commenters are generally skeptical of ForeverVM's practicality and security. Several question the feasibility and utility of "forever" VMs, citing the inevitable need for updates, dependency management, and the accumulation of technical debt. Concerns around sandboxing and security vulnerabilities are prevalent, with users pointing to the potential for exploits within the sandboxed environment, especially when dealing with AI-generated code. Others question the target audience and use cases, wondering if the complexity outweighs the benefits compared to existing serverless solutions. Some suggest that ForeverVM's current implementation is too focused on a specific niche and might struggle to gain wider adoption. The claim of VMs running "forever" is met with significant doubt, viewed as more of a marketing gimmick than a realistic feature.
Summary of Comments ( 36 )
https://news.ycombinator.com/item?id=43344673
HN commenters were generally impressed with the hack, calling it "clever" and "ingenious." Some expressed concern about the security implications of being able to execute arbitrary code within OpenAI's models, particularly as models become more powerful. Others discussed the potential for this technique to be used for beneficial purposes, such as running specialized calculations or interacting with external APIs. There was also debate about whether this constituted "true" code execution or was simply manipulating the model's existing capabilities. Several users highlighted the ongoing cat-and-mouse game between prompt injection attacks and defenses, suggesting this was a significant development in that ongoing battle. A few pointed out the limitations, noting it's not truly compiling or running code but rather coaxing the model into simulating the desired behavior.
The Hacker News post titled "Reverse Engineering OpenAI Code Execution to make it run C and JavaScript" (linking to a Twitter thread describing the process) sparked a discussion with several interesting comments.
Many commenters expressed fascination with the ingenuity and persistence demonstrated by the author of the Twitter thread. They admired the "clever hack" and the detailed breakdown of the reverse engineering process. The ability to essentially trick the system into executing arbitrary code was seen as a significant achievement, showcasing the potential vulnerabilities and unexpected capabilities of these large language models.
Some users discussed the implications of this discovery for security. Concerns were raised about the possibility of malicious code injection and the potential for misuse of such techniques. The discussion touched on the broader challenges of securing AI systems and the need for robust safeguards against these kinds of exploits.
A few comments delved into the technical aspects of the exploit, discussing the specific methods used and the underlying mechanisms that made it possible. They analyzed the author's approach and speculated about potential improvements or alternative techniques. There was some debate about the practical applications of this specific exploit, with some arguing that its limitations made it more of a proof-of-concept than a readily usable tool.
The ethical implications of reverse engineering and exploiting AI systems were also briefly touched upon. While some viewed it as a valuable exercise in understanding and improving these systems, others expressed reservations about the potential for misuse and the importance of responsible disclosure.
Several commenters shared related examples of unexpected behavior and emergent capabilities in large language models, highlighting the ongoing evolution and unpredictable nature of these systems. The discussion reflected a sense of both excitement and caution regarding the future of AI and the need for careful consideration of its potential implications. The overall tone was one of impressed curiosity mixed with a healthy dose of concern about the security implications.