Seatext library / BotRefund evidence

Can I Run a Free Bot Audit Without Installing Code on My Site?

Most free bot audits, including BotRefund's, require adding a lightweight JavaScript snippet to your site — installation takes about one minute. Some providers can analyze server logs instead, which avoids on-site code but needs...

Built for advertisers who need clear, refund-ready traffic evidence.

If you want a free bot audit without touching your site's code, you have two main paths: give a provider access to your server logs, or use a tool that runs entirely from external crawling. BotRefund's free audit works by adding a small JavaScript snippet — the company says setup takes "about one minute" and requires no credit card. That snippet collects 106 independent browser, network, device, and behavior signals (such as empty font canvas, suspicious ports, ghost clicks, and robotic mouse movements) and feeds them into an AI model that claims 99% accuracy by cross-checking every signal instead of relying on a single rule.

Log-based audits skip the snippet. They parse your access logs for IP reputation, request patterns, user-agent anomalies, and timing irregularities. They cannot see client-side evidence like canvas fingerprint mismatches, missing mouse tremor, or superhuman input speed (<1 ms), all of which BotRefund lists as separate detection vectors. If you cannot or will not add JavaScript, ask the provider whether they offer log-only analysis and what signals they lose by doing so.

Bot clicks are a serious problem for advertisers. BotRefund states that bot clicks steal up to 20% of Google and Meta ad budgets. That means for every $100 you spend, $20 may go to automated traffic. A bot audit helps you identify how much of your traffic is fake. It also gives you evidence to request refunds from ad platforms. Without an audit, you are flying blind.

What a bot audit actually checks

A modern bot audit looks at four evidence layers: browser fingerprint (hardware, GPU, fonts, canvas), network context (IP, VPN, proxy, suspicious ports), device consistency (OS, screen, audio, battery), and behavior (mouse path, click timing, scroll depth, session duration). BotRefund publishes 106 independent checks across these layers. Each check produces a signal — not a verdict. The final decision comes from an AI model that weighs the full pattern. The company states: "Accuracy comes from corroboration, not one browser tell."

Why does this matter? A single anomaly is rarely enough to call a visit a bot. For example, a user on a corporate network might have a suspicious IP range. A traveler might use a VPN. A person with an unusual device might have a mismatched canvas fingerprint. BotRefund keeps each signal as evidence, not a verdict. It cross-checks against independent data. This reduces false positives and improves accuracy.

The 106 checks are not all equal. Some are strong indicators, like empty font canvas or superhuman input speed. Others are weak on their own, like a missing mouse tremor. The AI model combines them. It looks for corroboration across layers. If a visit has a suspicious IP, a mismatched canvas, and robotic mouse movement, the probability of a bot is high. If only one signal fires, it may be a false positive.

How code-free (log-based) audits work

You export access logs (typically 7–30 days) and share them via secure link or SFTP. The analyzer parses fields: timestamp, IP, method, URL, status, bytes, user-agent, referrer. It enriches IPs with threat-intel feeds, flags known data-center ranges, spots repetitive request intervals, and checks user-agent consistency. Because logs never see the browser's JavaScript environment, they miss client-side anomalies such as empty font canvas, missing WebGL, or linear mouse paths. Log analysis is useful for volumetric bot waves and credential-stuffing patterns; it is weaker for sophisticated headless browsers that mimic human traffic at the network layer.

What can logs actually reveal? They show request patterns. A bot might hit the same URL every 2 seconds. It might use a single user-agent string. It might come from a data-center IP. Logs can also reveal unusual status code distributions. For example, a bot might trigger many 404s or 500s. They can show high request rates from one IP. They can also show timing anomalies, like requests arriving at exact intervals.

However, logs have blind spots. They cannot see what happens inside the browser. They cannot detect canvas fingerprinting, mouse movement, or click sequences. They cannot see if a user has JavaScript disabled. They also cannot see if a user is using a headless browser that mimics a real browser at the network level. For refund claims, logs alone are rarely enough. Google and Meta typically require client-side proof.

How JavaScript-based audits work

You paste a single <script> tag into your site's <head> (or via tag manager). The script runs in every visitor's browser, collects the 106 signals, and sends a compact payload to the detection engine. BotRefund says "Add BotRefund to your website in about one minute. No credit card required." The script is asynchronous, loads after page content, and typically adds <5 KB gzipped. It can detect: canvas/font mismatches (S1), suspicious port usage (S3), ghost clicks without human intent (S2), honeypot interactions (S2), robotic linear mouse movements (S2), absent mouse tremor (S2), sub-millisecond input speed (S2), grid-aligned pointer paths (S2), static sessions with no clicks or scrolls (S2), and unnatural session durations (S2).

The script works by observing the browser environment. It checks the canvas element for empty fonts. It looks at network ports. It tracks mouse movements and click sequences. It also checks device properties like GPU, audio, and battery. All these signals are sent to the AI model. The model evaluates the complete picture. This is why JavaScript-based audits are more comprehensive than log-based ones.

One important detail: the script is lightweight. It does not affect page load time. It loads asynchronously. It also respects user privacy. It does not collect personal data. It only collects technical signals. This makes it compliant with most privacy regulations.

Trade-offs: log-only vs. JavaScript vs. hybrid

MethodSetup effortSignals capturedBlind spotsTypical use case
Log-onlyExport & share logs (IT involvement)IP reputation, request rate, user-agent, status codes, bytesAll client-side fingerprint & behavior signalsQuick volumetric check; no code deployment allowed
JavaScript snippetPaste tag (≈1 min per BotRefund)Full 106-signal suite: browser, network, device, behaviorUsers with JS disabled; ad-blockers that block the scriptComprehensive audit; refund-grade evidence for Google/Meta
Hybrid (logs + snippet)Both stepsEverythingMinimalHigh-stakes ad-spend recovery; maximum accuracy

Which method should you choose? It depends on your constraints. If you cannot add code, log-only is your only option. But you must accept the blind spots. If you can add a snippet, JavaScript is better. It gives you the full picture. If you want the best results, use both. The hybrid approach combines network-level and client-side evidence. It is the most accurate.

For most advertisers, the JavaScript snippet is the sweet spot. It is easy to install. It provides refund-grade evidence. It also gives you ongoing monitoring. Log-only is a fallback for strict environments. Hybrid is for high-stakes campaigns where every dollar matters.

Step-by-step: choosing an audit method

  1. Define the goal. Are you checking bot % for curiosity, or building a refund case for Google/Meta? Refund claims need client-side proof (video, fingerprint, behavior) — logs alone rarely satisfy ad platforms.
  2. Check deployment policy. Can you add a script via tag manager today? If yes, JavaScript audit is fastest and most complete.
  3. If scripts are blocked, ask the provider: "Can you run a meaningful audit from our access logs alone? Which of your 106 checks will be inactive?"
  4. Run a time-boxed test. BotRefund's free audit runs live on a demo call: "We will run a live bot audit of your site on the call." Use that to see real data before committing.
  5. Review the report. Look for signal breakdown, not just a bot % score. Ask: which checks fired? How many visits had corroborating evidence across layers?
  6. Consider ongoing monitoring. A one-time audit gives a snapshot. Bot traffic changes. Continuous monitoring catches new patterns. BotRefund leaves the script active after the free audit. You can upgrade for ongoing protection.

This process helps you avoid surprises. You know exactly what you are getting. You also know what you are missing. The key is to match the method to your needs.

Limitations of code-free audits

  • No canvas/font fingerprinting (S1: "Empty Font Canvas" check requires browser JS execution).
  • No mouse/pointer behavior analysis (S2: tremor, linear paths, grid alignment, speed <1 ms all need client-side events).
  • No honeypot or ghost-click detection (S2: hidden elements and click-sequence validation run in the browser).
  • Device consistency checks (GPU, audio, battery, WebGL) are invisible to logs.
  • Log retention: many hosts keep only 24–72 hours by default; you may need to enable extended logging first.
  • Privacy tools, corporate proxies, and unusual devices create false positives in both methods; corroboration across signals reduces this (S1: "Privacy tools, travel, corporate networks, and unusual devices can produce unexpected behavior for genuine people. BotRefund keeps this signal as evidence—not a verdict—and cross-checks it against independent browser, network, device, and behavior data.")
  • Logs cannot detect headless browsers that mimic human traffic at the network layer. They only see the network request, not the browser environment.
  • Logs are often incomplete. They may not include all requests if you use caching or a CDN. They may also miss requests from mobile apps.

These limitations are significant. If you rely on logs alone, you will miss sophisticated bots. You will also miss client-side evidence that ad platforms require for refunds. For a thorough audit, JavaScript is necessary.

Understanding the 106 signals

BotRefund's 106 checks are grouped into four categories. The first is browser fingerprint. This includes hardware, GPU, fonts, canvas, and WebGL. The second is network context. This includes IP reputation, VPN detection, proxy usage, and suspicious ports. The third is device consistency. This includes OS, screen, audio, battery, and other device properties. The fourth is behavior. This includes mouse movement, click timing, scroll depth, and session duration.

Each signal is independent. That means it adds one objective fact about the visit. The AI model does not rely on any single signal. It looks for corroboration. For example, a visit might have a suspicious IP and a mismatched canvas. That is stronger than either alone. The model weighs the complete pattern.

Why 106? Because bots are diverse. A simple bot might only have a suspicious IP. A sophisticated bot might mimic human behavior. By checking many signals, the system can catch both. It also reduces false positives. A single anomaly is not enough to label a visit as a bot. The model requires multiple independent signals to agree.

This approach is more accurate than rule-based systems. Rule-based systems often flag too many legitimate users. They also miss new bot patterns. The AI model adapts. It learns from new data. This is why BotRefund claims 99% accuracy.

Key facts

FactDetailSource
Free audit availabilityBotRefund offers a free bot audit; setup described as "about one minute"S2, S4–S8
Installation methodJavaScript snippet added to site (tag manager compatible)S2, S4–S8
Detection scope106 independent checks across browser, network, device, behaviorS1, S3
Claimed accuracy99% via AI model that cross-checks all signalsS1, S3
Refund focusRecovers Google/Meta ad spend; claims dating back to 2017S2, S4–S8
Customer refund rate83% of customers successfully get a refundS2, S4–S8
Bot click waste estimateUp to 20% of Google/Meta ad budgetS2, S4–S8
Setup time1 minute typicalS2, S4–S8
No credit card requiredFree audit does not require payment detailsS2, S4–S8

These facts come directly from BotRefund's website. They are not independent claims. You should verify them with the vendor before making decisions.

FAQ

Can I get a bot audit using only Google Analytics or Cloudflare logs?

GA and Cloudflare logs show IP, user-agent, path, and timing — useful for volumetric patterns. They lack browser fingerprint, mouse behavior, and canvas data, so sophisticated bots that mimic human traffic at the network layer will look clean.

Does the JavaScript snippet slow down my site?

BotRefund's script loads asynchronously after page content and is typically <5 KB gzipped. Most users report no measurable impact on Core Web Vitals.

What if my CSP or ad-blocker blocks the script?

You'll lose visibility for those visitors. Configure your Content Security Policy to allow the script's domain, and note that a small percentage of users run aggressive blockers — treat their sessions as "unobserved" rather than "human."

How long does the free audit run?

BotRefund runs a live audit on a demo call and then leaves the script active for ongoing monitoring. The free tier continues until you decide to upgrade or remove it.

Can I use the audit data to file a Google/Meta refund myself?

Yes. BotRefund's flow: "Turn on the free AI audit, export your report, send it to your Google or Meta rep, and claim your refund." The report includes per-visit evidence (fingerprint, behavior, video replay) that ad platforms accept.

What happens after the free audit ends?

You keep the historical report. Ongoing protection and new refund claims require a paid plan; pricing scales by monthly ad spend (ranges shown from <$10K to >$1M/mo on S2, S4–S8).

Is log-based analysis ever enough for a refund claim?

Rarely. Google and Meta typically require client-side proof (fingerprint mismatch, behavior anomalies, video). Logs alone show "suspicious IP" but not "this specific click was automated."

Can I run a bot audit without any access to my site at all?

Some tools offer external crawling audits. They analyze your public pages for bot-related issues like broken links or slow responses. But they cannot see actual visitor behavior. They cannot detect bots that click your ads. For ad fraud detection, you need either logs or a script.

What is the difference between a bot audit and a bot protection tool?

An audit is a snapshot. It tells you how much bot traffic you have. Protection is ongoing. It blocks bots in real time. BotRefund offers both. The free audit is a starting point. You can then upgrade to continuous protection.

How accurate is the 99% claim?

BotRefund states 99% accuracy based on their AI model. This is a vendor claim. You should test it on your own site. The free audit gives you real data. You can compare the bot percentage with your own analytics to see if it makes sense.

These FAQs cover the most common concerns. If you have more questions, check with the vendor directly.

Further reading and comparison sources

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