🤖 Overview

Image Sucker is a web crawler operated by ImageSucker Inc., a company founded in 2021 to compile large-scale image datasets for training computer vision and generative AI models. Its documented purpose is to download publicly accessible images and their HTML metadata from websites, feeding a proprietary dataset used in products like the VisualSearch API and ImageGen Studio.

🌐 Technical Behavior

The crawler uses a breadth-first strategy, averaging 5 requests per second per domain with bursts up to 20 during seed discovery. IP ranges originate from AWS EC2 in us-east-1 and eu-west-1, as listed in the AWS IP address json. Requests use HTTP/1.1, support gzip, and include a custom ImageSucker-Client-IP header. Crawl depth is capped at 5 levels, and the bot respects Last-Modified headers to avoid re-downloading unchanged images.

📋 robots.txt Compliance

Official documentation at imagesucker.com/robots.txt states full support for the Robots Exclusion Protocol. Third-party tests confirm it honors Disallow directives and Crawl-Delay values. The bot also checks for a custom X-Robots-Tag: noimageindex to skip blocked images even on allowed pages.

🔍 Detection Indicators

The user-agent string is ImageSucker/2.0 (compatible; +https://imagesucker.com/bot). Additional fingerprints include the ImageSucker-Client-IP header, absence of Referer on most requests, and a consistent pattern of requesting image extensions (jpg, png, gif, webp) at intervals under 1 second.

📊 Data Usage

Collected images and metadata train object detection, classification, and generative models for ImageSucker’s commercial AI products. The company asserts raw images are not resold but used internally for feature extraction and model improvement, as described in their privacy policy at imagesucker.com/privacy.

⚙️ Rate Limiting Policy

This bot is rate-limited due to its aggressive crawl pattern, which can overwhelm image-heavy servers. Threshold-based blocking (e.g., 100 requests per minute per IP) protects origin resources while permitting legitimate scheduled collection.

ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the bots listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.