> For the complete documentation index, see [llms.txt](https://lance-kenji.gitbook.io/me/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lance-kenji.gitbook.io/me/swimmer-osint-ctf-2026-writeups/tgt_rain/rain_06_ai.md).

# rain\_06\_ai

### Challenge Overview

An image of Tokyo Station was published on rain’s blog. However, visual inspection suggests that the image is AI-generated rather than a real photograph.

The objective of this challenge is to determine which AI tool was used to generate the image, using only lawful OSINT techniques.

Flag format:

```
SWIMMER{TOOL_NAME}
```

Example (not the solution):

```
SWIMMER{Adobe Firefly}
```

***

### Initial Assumptions

Based on the challenge description and prior investigations involving rain, the following assumptions were made:

* The image was uploaded directly to rain’s **WordPress blog**
* The image may not contain standard EXIF metadata
* WordPress often **stores additional metadata** related to uploaded media
* AI-generated images may leave **tool-specific identifiers** in embedded metadata

***

### Investigation Process

#### 1. Locating the Relevant Blog Article

While browsing rain’s blog, the following article was identified as containing the Tokyo Station image:

```
https://brutorain.wordpress.com/2026/01/03/日常を記録する/
```

<figure><img src="/files/Ub7c4v4211owi9n4qKOZ" alt=""><figcaption></figcaption></figure>

Within this article, an image depicting Tokyo Station was observed.

<figure><img src="/files/aLluLIWh3ENxUTXNBuDF" alt=""><figcaption></figcaption></figure>

***

#### 2. Inspecting the Image File

When attempting to download the image, the filename was observed as:

```
tokyo_0003.jpeg
```

This filename strongly suggested that the image referenced in the challenge was this specific file.

***

#### 3. EXIF Metadata Check

The downloaded image was examined for EXIF metadata. No useful or identifying information was found, which is common for images uploaded through content management systems or generated by AI tools.

This led to further inspection of the **WordPress media metadata**.

***

#### 4. Inspecting WordPress Image Metadata

By inspecting the HTML source of the image element on the blog page, detailed metadata stored by WordPress was revealed. The \<img> tag contained a data-image-meta field with embedded JSON-like information.

<figure><img src="/files/bbNQsxSmBtVqKJ8WuXqx" alt=""><figcaption></figcaption></figure>

Relevant excerpt:

```
"aigc_info": {
  "source_info": "dreamina"
},
"data": {
  "product": "dreamina",
  "exportType": "generation"
}
```

This metadata explicitly referenced **dreamina** as the source and product used to generate the image.

***

#### 5. Identifying the Tool

A brief OSINT check confirmed that **Dreamina** is an **AI image and video generation tool**.

<figure><img src="/files/Lz6oWAHnx2qfI6gB5FZW" alt=""><figcaption></figcaption></figure>

This confirms that the Tokyo Station image was AI-generated using **Dreamina**.

***

### Key Findings

* The Tokyo Station image lacked traditional EXIF metadata
* WordPress stored embedded AI generation metadata in the image tag
* The metadata explicitly identified the source as **dreamina**
* Dreamina is a known AI image and video generation tool.

***

### Final Flag / Answer

```
SWIMMER{Dreamina}
```

***

### Notes & Takeaways

* WordPress media metadata can reveal details not present in EXIF data
* AI-generated images may contain **AIGC identifiers** embedded at upload time
* Inspecting HTML source code is a powerful but often overlooked OSINT technique
* Claims involving images should always be validated through provenance and metadata analysis

This challenge demonstrates how platform-level metadata can reliably expose the true origin of AI-generated content using lawful OSINT methods.


---

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