Image Prompt: How to Identify AI-Generated Images in 6 Steps

A photo of a flooded railway platform is shared across group chats on Monday morning.

The lighting is dramatic, the crowd looks realistic, and the caption mentions a real city. Is this image real?

An image like this can now be created with just one typed sentence.

That sentence, known as an image prompt, shapes the final image, including any clues that may reveal it’s not real. Here are six steps, in the order that saves the most time.

Table of Contents

• Step 1: Trace the Source First
• Step 2: Look for Content Credentials
• Step 3: Check for an Invisible Watermark
• Step 4: Inspect the Picture Closely
• Step 5: Reverse-Engineer the Image Prompt
• Step 6: Treat Detectors as a Clue
• Putting the Checks Together

Step 1: Trace the Source First

Use a reverse image search tool like Google Lens or TinEye to find the earliest version of the image.

Real photos often have a history photos from different angles, local news coverage, and posts from people who were there.

An image with no history and a vague caption should raise suspicion before you examine any single detail.

Also, check whether the weather and signs match the place and date mentioned in the caption.

Step 2: Look for Content Credentials

Content Credentials, based on the C2PA standard, are a signed record of an image’s origin and any edits made.

OpenAI claims that images generated by ChatGPT, Codex, and its API include both C2PA metadata and SynthID watermarks.

You can review this information by uploading a file to the Verify tool at contentcredentials.org.

However, note that a screenshot often removes the manifest, and missing credentials don’t automatically mean the image is fake.

Finding credentials is useful, but missing them tells you very little.

Step 3: Check for an Invisible Watermark

SynthID is Google’s invisible watermark, embedded into the pixels of images generated by certain tools.

One report claims that Google made SynthID available worldwide on October 7, 2026, at synthid.com.

Google has also announced that SynthID and C2PA checks are coming to Chrome and Google Search, so features might change.

Still, there are limits to this.

Detection only works on images from tools that include these signals, and a missing watermark doesn’t prove anything either way.

Finding a watermark also means the image might have been only partially AI-generated.

Step 4: Inspect the Picture Closely

If the source checks don’t show anything, look for visible errors:

• Text: Signs and labels that become nonsensical when viewed up close.
• Hands: Fingers grabbing cups, tools, or phones.
• Lighting: Shadows or reflections that don’t match the scene.
• Crowds: Repeated or nearly identical faces in the background.
• Texture: Skin without pores and no camera noise.

Keep in mind that these flaws can fade over time as AI models improve, and some real photos that are heavily edited can also show similar issues.

Step 5: Reverse-Engineer the Image Prompt

Ask yourself what image prompt could have created this photo.

Prompts usually describe the subject, setting, lighting, lens, and mood. Images generated from such prompts often reflect those elements.

Image Prompt Examples

Try these example prompts in any image generator:

1. “A photorealistic flooded railway platform at dawn, cinematic lighting, 35mm lens, ultra-detailed.”

2. “A blurry phone snapshot of a flooded railway platform, bad framing, slightly overexposed.”

The first type creates a clean, symmetrical image with dramatic lighting.
Real news photos are often messy, with awkward crops and cluttered foregrounds.

The second example reveals a key point: prompts can ask for imperfection, so a rough look doesn’t prove an image is real.

Step 6: Treat Detectors as a Clue

AI image detection tools estimate how likely a picture is to be AI-generated.
Their accuracy varies depending on the tool, the type of image, and how much editing has been done. They can sometimes be wrong.

Use these tools only after steps 1 to 4, and rely more on strong provenance evidence than on detector scores.

Photos that are mostly real but have an AI-generated background are especially likely to be missed.

Putting the Checks Together

Aim for three possible outcomes: likely AI-Generated, verified authentic, or unverified.

Most images fall into the third category, and stating “I can’t confirm this” is better than making a confident guess.

Frequently Asked Questions

1. Does a missing watermark mean an image is real?

Direct answer: No, it proves nothing either way.
Watermarks are only present on images from supporting tools, so you need additional evidence.

2. Can SynthID Detector check any image?

Direct answer: You can upload any image, but it only identifies watermarks from supporting tools.
A “not detected” result does not confirm the image is real.

3. Do screenshots remove Content Credentials?

Direct answer: Yes, a screenshot usually removes the C2PA manifest because it creates a new file without the original metadata.

4. Are AI image detectors accurate enough to trust?

Direct answer: Not on their own.
They can give false positives and false negatives, so use them together with source tracing and provenance checks.

5. Do detailed image prompts make AI images harder to detect?

Direct answer: Yes, detailed prompts can reduce obvious flaws and even mimic amateur photography, which is why visual inspection alone is not reliable.

Conclusion

No single test can determine the truth.

Build a case: trace the source, check credentials and watermarks, examine the image, consider the prompt, and treat detectors as just one part of the overall picture.

Next step: create two images using different prompts and run these checks on your own results to see what each one shows.

If an unverified image went viral in your team’s chat, which check would you do first, and what evidence would make you comfortable sharing it?

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