Distributed Crawler Poses as Human Visitor to Evade Analytics and Ad Filters

A detailed investigation revealed a sophisticated distributed crawler that successfully mimicked legitimate human browsing behavior across multiple unrelated websites. The crawler generated realistic events in Google Analytics while avoiding ad script loading and resource chains that would confirm genuine user sessions. Server logs showed consistent patterns of fake search engine referrers, internal navigation with fabricated Referer headers, and selective requests limited mostly to images returning 404 errors. Analysts built a graph-based detection system that correlated events across sites to expose the coordinated activity despite individual requests appearing benign. The campaign rotated browser signatures and IP addresses frequently, making single-site rate limiting ineffective. The case demonstrates how modern crawlers can exploit Measurement Protocol and incomplete bot detection to consume server resources without contributing to revenue.

HabrAugust 2, 2026Translated from Russian

Read at source

A site owner watching traffic graphs climb while advertising revenue stayed flat would normally celebrate algorithmic success. In this case the numbers told a different story: Google Analytics recorded new sessions, the server performed full TLS handshakes and dynamic page generation, yet no corresponding ad impressions were billed.

The discrepancy arises because GA4 accepts events via the Measurement Protocol, a server-to-server channel originally intended for offline interactions. A crawler that crafts the correct payload can register a session without ever rendering advertisements or executing the full browser resource chain of CSS, JavaScript, fonts and favicons.

Operators of a network of unrelated sites noticed the same subtle footprint on each property. Individual requests carried ordinary modern browser strings, arrived from search-engine referrers, and followed internal links at a human-like pace. Only when events were aggregated into a cross-site graph did the coordinated pattern emerge: dozens of IP addresses replaying nearly identical sequences while rotating User-Agent strings and never loading supporting page assets.

One particularly convincing candidate, masked as 203.0.113.0/24, produced roughly one hundred events over eight days. Its profile included search transitions, internal navigation, and a modest set of static resources. Raw logs, however, showed that almost half the requests openly declared themselves with the string “crawler” and that the supposed resources were exclusively images returning 404 responses without Referer headers.

Further examination of referrer data exposed additional contradictions. The same addresses claimed simultaneous arrivals from Google, Yandex, Bing and Baidu within minutes, an impossible sequence for any single human reader. Internal-link Referers were fabricated to simulate article-to-article reading, yet no stylesheets, scripts or actual page images were ever requested.

The investigation relied on a continuously updated graph whose vertices represented addresses, network blocks, browser masks and requested resources. Edges captured temporal and causal relationships, allowing analysts to test whether short, seemingly natural sessions on separate sites actually belonged to the same automated actor. GPU-accelerated processing made parallel comparison of hundreds of candidate biographies feasible.

The episode illustrates that server logs remain the only immutable record when analytics platforms and advertising systems can be fed synthetic events. By focusing on missing resource chains and contradictory origin stories rather than any single IP or country, defenders can surface distributed crawlers that have studied human browsing patterns in detail.

WordPress Google Analytics Measurement Protocol RDAP

ShareX Facebook LinkedIn Reddit

Meridian digestThe week's most consequential security stories, distilled into one briefing.See the digest

More in Malware & Botnets

Malware & Botnets

Yoba Campaign Uses Signed ChatGPT and Claude Binaries for DLL Sideloading and XMRig Deployment

Researchers at Check Point Research have uncovered the Yoba malware campaign that distributes fake desktop clients for ChatGPT and Claude through GitHub repositories. The attackers bundle legitimate signed executables from OpenAI and Anthropic with a malicious DLL that gets loaded via classic sideloading. Once executed, the loader establishes persistence using the Windows Task Scheduler and retrieves additional payloads through Telegram, DNS over HTTPS, and the Catbox file hosting service. The campaign ultimately deploys the XMRig cryptominer, which pauses mining activity when user interaction is detected to avoid detection. No compromise of OpenAI or Anthropic infrastructure was found; the attackers simply repurpose the companies' signed binaries and reputation. The operation primarily targets home users and small-to-medium businesses with Windows systems.

AntiMalwareOct 28, 2026Translated from Russian

Malware & Botnets

uCreator Spyware Infiltrates Modified Telegram, WeChat and GCash Builds on Android

Security researcher Ovi has published a detailed analysis of uCreator, also known as YingGai, a commercial Android spyware platform designed for surveillance and remote app control. The malware intercepts messages, verification codes and account data directly inside legitimate applications without requiring root privileges. Infection vectors include tampered Telegram, WeChat and GCash APKs distributed through unofficial sources, as well as the Onion Box container that launches the target app inside a controlled environment. Once active, uCreator hooks into the host process, reads Telegram’s local message database through client interfaces, captures two-factor authentication passwords and hides its own session from the user. The operation is supported by cloud-based command panels and exposed GitLab repositories that revealed server-side code and development history. Compatibility problems have been noted on Android 17, and the total number of victims remains unknown.

AntiMalwareOct 26, 2026Translated from Russian

Malware & Botnets

Researchers Deploy Cowrie Honeypot Disguised as NVIDIA H100 Server to Study SSH Botnet Tactics

A cybersecurity team set up a realistic Cowrie honeypot on a fake server equipped with four NVIDIA H100 GPUs, 128 AMD EPYC cores, and terabytes of storage to observe what SSH brute-force bots actually do after gaining access. The trap used a custom StickyAuth module that allowed entry only after several failed attempts and locked in the successful credential pair per IP address. Over the first 12.5 hours the system recorded 1,846 connections from 126 unique IPs, 175 successful logins, and 1,524 commands executed, with the majority of activity traced to a single botnet linked to the Outlaw group. The attackers deployed SSH keys signed mdrfckr, changed the root password, killed competing processes, installed cron jobs, and downloaded a mining archive called dota3 containing an IRC backdoor and its own SSH scanner. The researchers also identified three realism issues in the base Cowrie setup—limited grep flags, outdated filesystem paths in Debian 12, and inconsistent hostname reporting—and patched them to keep sophisticated bots engaged longer. An auxiliary LLM service later summarized each session in Telegram for easier analysis.

HabrOct 25, 2026Translated from Russian