Security experts have identified a new kind of cyber attack that hides instructions inside ordinary pictures. These commands do not appear in the full image but become visible only when the photo is automatically resized by artificial intelligence (AI) systems.
The attack works by adjusting specific pixels in a large picture. To the human eye, the image looks normal. But once an AI platform scales it down, those tiny adjustments blend together into readable text. If the system interprets that text as a command, it may carry out harmful actions without the user’s consent.
Researchers tested this method on several AI tools, including interfaces that connect with services like calendars and emails. In one demonstration, a seemingly harmless image was uploaded to an AI command-line tool. Because the tool automatically approved external requests, the hidden message forced it to send calendar data to an attacker’s email account.
The root of the problem lies in how computers shrink images. When reducing a picture, algorithms merge many pixels into fewer ones. Popular methods include nearest neighbor, bilinear, and bicubic interpolation. Each creates different patterns when compressing images. Attackers can take advantage of these predictable patterns by designing images that reveal commands only after scaling.
To prove this, the researchers released Anamorpher, an open-source tool that generates such images. The tool can tailor pictures for different scaling methods and software libraries like TensorFlow, OpenCV, PyTorch, or Pillow. By hiding adjustments in dark parts of an image, attackers can make subtle brightness shifts that only show up when downscaled, turning backgrounds into letters or symbols.
Mobile phones and edge devices are at particular risk. These systems often force images into fixed sizes and rely on compression to save processing power. That makes them more likely to expose hidden content.
The researchers also built a way to identify which scaling method a system uses. They uploaded test images with patterns like checkerboards, circles, and stripes. The artifacts such as blurring, ringing, or color shifts revealed which algorithm was at play.
This discovery also connects to core ideas in signal processing, particularly the Nyquist-Shannon sampling theorem. When data is compressed below a certain threshold, distortions called aliasing appear. Attackers use this effect to create new patterns that were not visible in the original photo.
According to the researchers, simply switching scaling methods is not a fix. Instead, they suggest avoiding automatic resizing altogether by setting strict upload limits. Where resizing is necessary, platforms should show users a preview of what the AI system will actually process. They also advise requiring explicit user confirmation before any text detected inside an image can trigger sensitive operations.
This new attack builds on past research into adversarial images and prompt injection. While earlier studies focused on fooling image-recognition models, today’s risks are greater because modern AI systems are connected to real-world tools and services. Without stronger safeguards, even an innocent-looking photo could become a gateway for data theft.
Flashpoint’s Global Threat Intelligence Index report is based on more than 3.6 petabytes of data studied by the experts. Hackers stole credentials from 5.8 million compromised devices, according to the report. The significant rise is problematic as stolen credentials can give hackers access to organizational data, even when the accounts are protected by multi-factor authentication (MFA).
The report also includes details that concern security teams.
Until June 2025, the firm has found over 20,000 exposed bugs, 12,200 of which haven’t been reported in the National Vulnerability Database (NVD). This means that security teams are not informed. 7000 of these have public exploits available, exposing organizations to severe threats.
According to experts, “The digital attack surface continues to expand, and the volume of disclosed vulnerabilities is growing at a record pace – up by a staggering 246% since February 2025.” “This explosion, coupled with a 179% increase in publicly available exploit code, intensifies the pressure on security teams. It’s no longer feasible to triage and remediate every vulnerability.”
Both these trends can cause ransomware attacks, as early access mostly comes through vulnerability exploitation or credential hacking. Total reports of breaches have increased by 179% since 2024, manufacturing (22%), technology (18%), and retail (13%) have been hit the most. The report has also disclosed 3104 data breaches in the first half of this year, linked to 9.5 billion hacked records.
Flashpoint reports that “Over the past four months, data breaches surged by 235%, with unauthorized access accounting for nearly 78% of all reported incidents. Data breaches are both the genesis and culmination of threat actor campaigns, serving as a source of continuous fuel for cybercrime activity.”
In June, the Identity Theft Resource Center (ITRC) warned that 2025 could become a record year for data cyberattacks in the US.