## 1 Introduction  
Organizations are increasingly utilizing online social networks (OSNs) as part of their communication and marketing strategies [1, 2]. Organizations create official public spaces, such as pages or groups, on OSN platforms. Members participate in these spaces and engage with the content. They may share posts, images, and location data on their personal accounts and add the organization's name or hashtag to their posts. When someone searches for the organization's name or hashtag on an OSN, sensitive information may be leaked and end up in unauthorized hands [3, 4, 5, 6]. An intelligent attacker can exploit the information published via OSNs to collect information about a target organization to conduct industrial espionage or launch a targeted attack [7, 8]. They can use this information to provide a comprehensive view of the organization's membership, groups, posts, and locations. They can reconstruct the organization's structure, identify its leadership and technologies, obtain contact information not available on its official website, and locate specialized branch offices [7, 9, 10]. Posting an image of an organization member in an office, for example, can reveal information about the premises, layout, or infrastructure. With this information, attackers can gain access to even more sensitive information and then proceed to attack the organization [7, 9, 11]. Organizations around the world face the challenge of preventing data leakage, which is defined as the disclosure of information to unauthorized entities or individuals [12, 13]. Data leaks can result in substantial losses, whether financial or non-financial [14]. The primary cause of data leakage, whether intentional or not [15, 16], is action by an organization's members, a phenomenon referred to as an insider threat [17]. On the one hand, members of an organization may intentionally share images online containing sensitive information. As an example ([[https://www.bbc.com/news/world-us-canada-68473868](https://www.bbc.com/news/world-us-canada-68473868)]([https://www.bbc.com/news/world-us-canada-68473868](https://www.bbc.com/news/world-us-canada-68473868)) (accessed on 4 March 2024)), consider the case of an Air National Guard member who pleaded guilty to posting dozens of classified documents online to a platform popular with gamers. Maps, satellite images, and intelligence on U.S. allies were included in the upload documents. On the other hand, organization members may not be aware that they have captured confidential organizational content in their shared images or may not be aware that certain objects contain confidential information. Due to a lack of awareness or context-specific knowledge, seemingly innocuous visual content shared on social media platforms can result in data leakage [18]. A few examples in which sensitive information was unintentionally revealed were presented by [PERSON] [18]. In a YouTube video, a backyard scene reveals the surroundings of a private residence, and a scene where a rain radar map is shown to the camera reveals the house's global positioning system (GPS) location. Furthermore, Twitter images demonstrated a GPS-traced route and implied physical presence. Using Google Maps' 3D mode, an address was located for a car parked in front of a house on the Twitter profile of an Australian web security consultant. Using the address, it was also possible to gather information about alleged relatives, property size, date of purchase, and the telephone numbers of the user. Detecting confidential information poses a unique challenge different from other image-processing tasks. The confidential information in the image may be difficult to detect, since it is not the main focus of the image. It may be small or hidden in the background. Furthermore, confidential information can be highly context-dependent and organization-specific. An object that appears innocuous in one setting may be confidential in another. In addition, identifying confidential objects is challenging as they are likely to be rare in the overall dataset.