Table Of Contents
What’s new
We’re excited to announce Image Details for Optical Character Recognition (OCR) is now available in Flashpoint Cyber Threat Intelligence. This update gives customers a deeper understanding of visual content and extracts useful insights.
With image details, you can drill into the context behind images posted in our collections with access to detailed information, including:
- Times Posted: See how often the image appears in our collections.
- First Observed: Find out when the image first appeared.
- Last Observed: Check the most recent date the image was posted.
- Post History: Explore recent posts containing the image, with a link to view all related posts.
- Text: Clearly read the text found within the image.
- Logos: Identify logos within the image.
- Classifications: Understand the characteristics of the image determined by OCR.
Why it matters
It helps to simplify the process of understanding image context and its relevance within communities. You can easily determine where a particular image is posted and by whom, check the freshness of an image, and explore the sentiments expressed within the communities where the image is shared.
When conducting investigations, starting with an image search can help you uncover instances of fraud, such as financial fraud or telecommunications fraud. Looking at the ‘Classifications’ of a specific image can also help you refine your search to find similar images with the same classifications. For example, images that contain ‘handwriting’ or ‘device screen’.
How it works
- Start with an image search: Launch a search in the ‘Images’ tab, which will leverage our OCR capabilities.
- Explore image details: From the results, click on an image to access a side panel of detailed information, including text, logos, classifications, and more.
- Navigate to related posts: Find related content by exploring more posts that contain the image.
- Refine your search: Use ‘Classifications’ (or any other image detail) to refine your searches and discover similar images based on shared details.
