ABOUT / INDEPENDENT ANTI-BOT RESEARCH LAB
Tracing what happens
when the web fights back.
Anti-bot research is the core of ScrapeTrace. We investigate how detection systems observe clients, interpret signals, and decide which requests get through.
One core, connected questions
Anti-bot systems and browser identity. Browser fingerprints, TLS and HTTP identity, automation artifacts, behavioral signals, challenges, and decision layers. The aim is to explain observed behavior within a controlled setup.
Scraping infrastructure and evaluations. Reliability, failure visibility, and cost per valid result matter alongside access. Vendor comparisons belong here when there is a real workload, a documented method, and evidence to support the conclusions.
Extraction challenges. Access is only the start. Scrambled fonts, honeypots, crawler traps, dynamic rendering, hostile DOM, and prompt injection can make a successful response produce an unreliable extraction.
Projects make these questions tangible. TracePrint compares browser and transport evidence across two clients. ShieldFont Decoder explores the gap between source text and font-rendered content.
How we investigate
Start with a precise question. Record the environment and controls. Change variables deliberately. Keep observations separate from explanations, and state what the result cannot establish. Read the research methodology for the full publication standard.
Publish the investigation, not the turnkey bypass.
ScrapeTrace publishes experimental setups, signal categories, observations, failed hypotheses, limitations, and safe reproductions. The goal is to explain the system through evidence. Articles do not package production evasion scripts, exact spoof values, vendor-specific secret techniques, or CAPTCHA-solving recipes.
Disclosure policy
Evaluations disclose sponsorships, affiliate relationships, supplied credits, and vendor involvement in the relevant article. Commercial support must not determine findings or conceal failures. Rankings require a documented comparison; a feature list alone is not performance evidence.
What a result can establish
Findings apply to the tested versions, configurations, targets, and time window. A successful request, an undetected signal, or a failed extraction does not establish the cause or long-term reliability. Unresolved explanations remain hypotheses.
Corrections and contact
Substantive corrections are dated and explained in the affected piece. Share corrections, research questions, or collaboration proposals at contact@scrapetrace.com. Public code is linked from each project; the ScrapeTrace organization is the home for the publication.
