How to Identify Invalid Traffic on Overseas Websites Using Access Logs

When overseas website traffic increases but inquiries do not, start by looking for unusual requests in the access logs: which sources are visiting continuously, which pages they request, whether the intervals are regular, and whether they reach conversion points such as forms. Identifying invalid traffic on an overseas website requires multiple pieces of evidence; a foreign IP address, high visit frequency, or lack of inquiries alone is not enough to determine that traffic is invalid. Genuine visits, legitimate crawlers, malicious scans, and ad fraud leave different clues in the logs.

Align the log scope first to avoid mistaking differences in measurement for anomalies

Access logs record requests, not visitors. A single page load can request images, scripts, and stylesheets, while analytics tools rely on script execution and consent settings. Differences between the two sets of figures do not, by themselves, indicate traffic inflation.

When a content delivery network is used, origin server logs may record only requests to the origin, missing visits served from cache. If the real client IP address is not configured correctly, the addresses in the logs may belong to proxy nodes. Before investigating, confirm what the logs cover, and trust client IP addresses only when they are passed by configured proxy sources. Do not automatically trust forwarding fields supplied with arbitrary requests.

At a minimum, retain the request time and time zone, client IP address, request method, path, status code, response size in bytes, referrer, and user agent. If available, also record request duration, edge-node decisions, and request IDs. Query parameters can help track campaign sources, but avoid logging form contents, passwords, or complete identity information.

Similar visit patterns can call for different responses

Each of these clues has limitations. Browser caching reduces requests for static resources, and automated programs can also execute scripts; people in a shared office network may use the same public IP address. Crawler identities can also be spoofed, so verify them against their published IP ranges or by following their documented reverse-DNS and forward-DNS verification procedures.

Break down anomalies into three types of evidence: frequency, paths, and sources

Compare request frequency with the website's own baseline. First review historical request volumes for the same day of the week and a similar time of day, then identify the time window in which the volume rose suddenly. After grouping requests by client IP address, also examine user agents, request paths, and any available session indicators. A large number of product-page requests from one IP address in a short period could indicate bulk scraping, but it could also be normal traffic from users sharing an egress IP. Fixed intervals, repeated sequences, and sustained activity together make automation more likely.

Paths can explain what the traffic is doing. Repeatedly probing nonexistent admin pages has a very different business meaning from visiting category pages, product pages, and contact information. Analyze page requests, static files, and APIs separately; otherwise, image loading can inflate request counts, and API polling can be mistaken for repeated browsing.

Assess sources through cross-checks. The referrer field may be missing or spoofed, and an IP address's geolocation does not prove a visitor's actual location. Visits from outside a campaign's target region may come from proxy networks, forwarded links, or geolocation errors. Increase the risk rating only when these are accompanied by unusual timing patterns, irrelevant paths, or repeated bulk behavior.

Logs can identify suspicious visits, but cannot prove ad fraud on their own

A landing-page request containing ad parameters only indicates that the request carried those markers. Copied links, crawler activity, and page preloading can all generate similar records. To assess paid traffic quality, align landing-page visit times, campaign parameters, click IDs, and ad reports, then link them to form submissions, qualified inquiries, or order records.

When aligning timestamps, use a consistent time zone and distinguish click time, arrival time, and conversion time. If a group of sources visits a single landing page in concentrated bursts but generates no subsequent requests, it can be flagged for review. However, blocked scripts, failed page loads, or interrupted cross-domain tracking can also result in a broken behavioral sequence. First confirm that the page and analytics configuration are working properly, then assess traffic quality.

Logs also cannot provide an accurate dwell time directly. A visitor may continue reading after their last request, and a successful response status does not mean the content was fully displayed. Therefore, “only one request” or “no conversion” can be used as screening criteria, but not as grounds for blocking.

Validate rules before expanding the scope of blocking

Start by setting monitoring rules for clearly identified scan paths or sustained abnormal request frequency. Record matching requests, then decide whether to apply rate limiting, an access challenge, or blocking. For suspected traffic inflation, retain the time window, request samples, and associated IDs so they can be reviewed against campaign records. Do not block an entire region simply because conversion rates are low in a particular country or area.

After rules take effect, monitor whether suspicious requests have decreased, normal pages remain accessible, verified crawlers can still crawl the site, and form submissions continue to work. If request volume falls but qualified inquiries also decline, review the rules for false positives. Keep a rollback option for new rules so every action can be traced to specific evidence.