CVE-2024-27564: The Silent Backdoor That Let Hackers Exploit a ChatGPT Image Tool

Image Credit, WELC0MEИ0

In early 2024, a hidden vulnerability was discovered in an image-handling tool within a public version of a ChatGPT-like application. The vulnerability, now cataloged as CVE-2024-27564, may sound like a jumble of numbers and letters, but it represents a real-world threat that has already been used to quietly probe and infiltrate networks around the world. From hospitals to banks, this flaw gave hackers a way to sneak into places they shouldn’t have access to—all without ever needing a password.

At the center of this issue is a simple script known as “pictureproxy.php.” Its job is straightforward: it fetches images from the internet when a user wants to display them inside a chat interface. This is common functionality in modern web apps. However, this particular script had one major weakness—it didn’t check where the image was coming from. This means a hacker could trick the system into requesting not just an image, but potentially sensitive content from other parts of the internet or even internal systems that were never meant to be exposed to the outside world.

This kind of flaw is called a Server-Side Request Forgery, or SSRF for short. In simple terms, it lets attackers use the server like a puppet, making it request information from other websites or services, including hidden, internal systems. Think of it like convincing the mailroom clerk at a company to send letters to the CEO’s private office or to other secret departments, even though you’re an outsider. Once inside, attackers can start poking around, gathering information, and preparing for more serious attacks.

What made CVE-2024-27564 especially dangerous was how easy it was to exploit. No special tools were needed. No login was required. A simple web request with a carefully crafted link was enough to trigger the flaw. In cybersecurity terms, that’s a red flag. Open doors like this are rare, and when found, they tend to be abused quickly and repeatedly.

Security researchers began noticing thousands of suspicious requests targeting this exact weakness—more than 10,000 attempts traced to just one internet address. These probes were not random. They were highly focused and persistent, aimed at organizations across the globe, from financial services to healthcare providers. In some cases, attackers used the flaw to access internal documents, cloud storage metadata, and even configuration files that could lead to further compromises.

The reason these attacks are hard to detect is because they happen from within. The compromised server itself is doing the exploring, not the hacker’s own machine. To the rest of the network, it looks like legitimate activity. But it’s not. It’s more like someone hijacking a security guard’s badge and roaming through a building, unchecked.

Thankfully, this vulnerability was not part of OpenAI’s official ChatGPT product. Instead, it affected a related open-source version that developers had cloned or customized from public repositories. Still, the impact was serious. These systems were often used in corporate or research environments and, once compromised, could give attackers a foothold into broader infrastructure.

Fixing the issue is relatively straightforward—developers need to update or remove the faulty script and implement better validation for any user-submitted URLs. It’s also a reminder of the importance of network boundaries. Servers that fetch outside content should not have access to sensitive internal resources. Simple segmentation can make a big difference.

The bigger lesson, though, is about trust and complexity. As AI tools and chat platforms grow more powerful, so do the systems that support them. With more features come more risks, especially when open-source code is integrated without full security reviews. Even a small feature like image retrieval can open the door to massive consequences if left unchecked.

CVE-2024-27564 is a wake-up call. It’s not just about lines of code—it’s about understanding how even the most helpful features can be misused. In the race to build smarter tools, we can’t forget the basics of keeping them secure. Because sometimes, the smallest hole in the system can lead to the biggest breach.