DeepFake: Detect AI-Generated Images in 5 Steps

We live in a time when an image is no longer a reliable guarantee of truth. AI‑generated content floods social media feeds, news platforms and messenger groups every single day, and only very few people are able to tell the difference. What once required expensive technology and expert knowledge is now accessible to anyone with a basic internet connection. Deepfakes, meaning artificially created or manipulated image and video content, are no longer a niche topic. They are actively used to spread misinformation, damage reputations or influence political opinion. The good news is that such content does not have to be accepted without question. With the right online tools, AI‑generated images can often be uncovered within minutes, even without technical expertise.

Check Whether an Image Is AI‑Generated in 5 Steps

Step 1 Visual inspection for common AI mistakes
Before using any detection tool, it is worth taking a close look at the image yourself. Many AI‑generated images reveal inconsistencies through small details. Pay close attention to facial features such as uneven eyes, blurred teeth or an unusual number of fingers on hands. Hair often appears overly uniform or blends unnaturally into the background. Text or logos within images are frequently distorted, unreadable or oddly shaped. Backgrounds may show repeating patterns or objects that seem fused together. Lighting can also be revealing. If shadows fall in different directions, the image is likely not authentic.

Step 2 Use AI detection tools
Next, upload the image to at least three different online detection tools. Using multiple tools is essential because no single system can deliver a completely reliable result on its own. Well‑known options include Sightengine, Illuminarty, ZeroGPT, IsItAI and Truthscan.

Step 3 Interpret the results correctly
Detection results should always be viewed in context. Values between 80 and 100 percent are a strong indication of AI generation, but they should still be confirmed by additional tools. Scores between 50 and 79 percent are inconclusive and require further investigation. Results below 50 percent suggest authenticity but do not fully rule out AI involvement.

Step 4 Check image metadata
Image metadata often contains valuable forensic information. Tools such as ExifTool, Jeffrey’s Exif Viewer or Metadata2Go can show when an image was created and which device was used. Authentic photographs usually include details like camera model, manufacturer, exposure settings and GPS data. If all of this information is missing, it should be treated as a warning sign.

Step 5 Reverse image searches
A reverse image search helps determine whether an image has appeared elsewhere online and in which context. Google Images and TinEye are useful for a general overview, with TinEye also showing the earliest known appearance of an image. Yandex Images often produces better results for portraits than Google. If facial identification is required, PimEyes can be used as an additional tool.

Real‑world example

Below is a practical example that we will analyze step by step. The image was deliberately chosen because it appears highly realistic at first glance, demonstrating how this method works even in more challenging cases.

Step 1 Visual inspection for common AI mistakes
A closer look reveals several typical AI characteristics. The leopard’s blue eyes appear extremely uniform and almost unnaturally perfect, something rarely seen in real animals. The fur blends smoothly into the background without a clear natural separation. The background itself looks soft and uniform, lacking real depth or structure. Overall, the image displays classic traits of AI generation: overly clean, overly balanced and carefully staged.

Step 2 Use AI detection tools
ZeroGPT analyzes the image and estimates the probability that it was generated by artificial intelligence. Higher percentage values indicate a greater likelihood that the image was not captured by a real camera.

Step 3 Interpret the results correctly
In this case, ZeroGPT reports a probability of 98 percent, which is considered very high and strongly suggests AI generation. Even so, no single tool should ever be trusted blindly. Detection systems often produce different results, which is why multiple tools should always be used together.

Step 4 Check image metadata
ExifTool allows a detailed inspection of an image’s metadata. Real photographs typically include information such as camera model, manufacturer, exposure time and GPS data. In this example, none of this information was present, which further supports the assumption that the image was AI‑generated.

Step 5 Reverse image searches
Reverse image searches are a simple but effective way to check whether an image has appeared online before. They help verify whether the claimed origin or publication date is plausible. In this case, the search returned no results, which may seem surprising since the image originates from the internet. This once again highlights that reverse searches are not always reliable and should never be the only method used for verification.

After reviewing all findings, I conclude that this image is AI‑generated. Please note that no tool or method can determine with absolute certainty whether an image was created by AI. The steps outlined here significantly improve the accuracy of an assessment, but they do not replace human judgment. Results should always be treated as guidance rather than definitive proof.

Conclusion

AI‑generated images have reached a level of quality that challenges even experienced viewers. What was once easy to spot at a glance is now often indistinguishable from real photography. Consuming visual content without critical evaluation increases the risk of falling victim to targeted misinformation. Reliable verification therefore requires multiple layers of analysis, as no single method is sufficient on its own. One of the most important indicators remains the digital footprint left by real photographs, which is often missing in AI‑generated images. The underlying issue, however, is that image generation technology continues to advance faster than our ability to reliably detect it.

Sources

imgfx
zerogpt
exif.tools
Google Reverse Image