Overview
CAPTCHA and JavaScript both elevate Tobacco's active barrier profile
| Value | |
|---|---|
| WAF | 98% |
| Antibot | 30% |
| CAPTCHA | 52% |
| JavaScript | 38% |
| Rate Limiting | 30% |
| TLS | 15% |
WAF leads at 98%. CAPTCHA (52%) and JavaScript (38%) together form a multi-layer active stack — more than most sectors deploy alongside WAF.
Barrier Landscape
CAPTCHA and JavaScript define Tobacco's layered active defences
| Value | |
|---|---|
| WAF | 98% |
| Antibot | 30% |
| CAPTCHA | 52% |
| JavaScript | 38% |
| Rate Limiting | 30% |
| TLS | 15% |
| Has robots.txt | 76% |
| Blocks AI crawlers | 3% |
WAF leads at 98%. CAPTCHA (52%) and JavaScript (38%) are both well above the cross-sector norm, giving Tobacco a markedly heavier active barrier profile than most sectors.
Two-barrier stacks are Tobacco's most common security posture
| % of sites | |
|---|---|
| 0 barriers | 2% |
| 1 barrier | 18% |
| 2 barriers | 37% |
| 3 barriers | 16% |
| 4 barriers | 13% |
| 5 barriers | 13% |
| 6 barriers | 1% |
37% of Tobacco sites carry exactly 2 barriers. 43% stack three or more. 2% carry none — a low share of unprotected sites for this sector.
Tobacco sites are predominantly Simple to access
| Mean recommended tier | |
|---|---|
| All sites | 1.17 |
A mean recommended tier of 1.17 and a median of Simple place Tobacco among the most accessible sectors surveyed. 86% of sites are Simple to access; 3% require Moderate or above.
Simple tier covers more than three-quarters of Tobacco sites
| % of sites | |
|---|---|
| 1 - Simple | 86% |
| 2 - Easy | 11% |
| 3 - Moderate | 3% |
| 4 - Complex | 0% |
| 5 - Advanced | 0% |
Simple (86%) is the most common tier. Simple and Easy together account for 97% of sites, while 3% land at Moderate and 0% at Complex or Advanced.
robots.txt
Around three-quarters of Tobacco sites publish a robots.txt
| % of sites | |
|---|---|
| Publish a valid robots.txt | 76% |
76% of Tobacco sites have a valid robots.txt. The remaining 24% leave crawl policy entirely undefined — a meaningful gap for a sector of this scale.
Tobacco sites name a handful of agents in robots.txt — few commit to comprehensive policies
| % of sites | |
|---|---|
| 0 | 29% |
| 1 | 37% |
| 2–4 | 7% |
| 5–9 | 23% |
| 10–15 | 3% |
| 16+ | 1% |
The mean of 2.5 named agents reflects limited bot-policy investment in Tobacco. 29% of sites name no agents; 37% name exactly one. Only 1% maintain a list of 16 or more named bots.
SEO audit tools lead Tobacco's robots.txt mentions ahead of AI crawlers
| % of sites | |
|---|---|
| AI crawlers | 4% |
| SEO / search indexing | 1% |
| SEO audit tools | 25% |
| Commercial scrapers | 0% |
| Social / content scrapers | 0% |
| Archive / research crawlers | 0% |
| Monitoring / uptime bots | 0% |
SEO audit tools are mentioned by 25% of Tobacco sites — the leading bot category, ahead of AI crawlers at 4%. Figures are percentages of all 100 sites surveyed.
Uniform per-agent rules dominate Tobacco robots.txt files
| % of sites | |
|---|---|
| Uniform per-agent rules | 55% |
| Path-level mixed rules | 19% |
| Allow-only (no Disallow rules) | 1% |
| Mixed AI posture | 1% |
| Blanket Disallow: / | 0% |
Uniform per-agent rules lead at 55%, with path-level mixed rules at 19%. Mixed AI posture (1%) and blanket Disallow (0%) are minimal.
AhrefsBot leads named Disallow rules in Tobacco robots.txt
| Disallowed | Allowed (whitelisted) | |
|---|---|---|
| * | 70% | 19% |
| AhrefsBot | 22% | 2% |
| AhrefsSiteAudit | 21% | 2% |
| Nutch | 21% | — |
| adsbot-google | 20% | — |
| CCBot | 3% | — |
| GPTBot | 2% | 1% |
| Google-Extended | 2% | 1% |
| AdsBot-Google | 2% | — |
| ClaudeBot | 1% | 1% |
| PerplexityBot | 0% | 2% |
| SBIntuitionsBot | 1% | — |
| BLEXBot | 1% | — |
| FacebookBot | 1% | — |
| Meta-ExternalAgent | 1% | — |
| Meta-WebIndexer | 1% | — |
| SeznamBot | 1% | — |
| AddSearchBot | 1% | — |
| Amazonbot | 1% | — |
| Applebot-Extended | 1% | — |
| Bytespider | 1% | — |
| PetalBot | 1% | — |
| meta-externalagent | 1% | — |
| Yandex | 1% | — |
| Googlebot | 1% | — |
Values are percentages of all 100 Tobacco sites surveyed. The wildcard (*) leads at 70% Disallow. Among named agents, AhrefsBot, AhrefsSiteAudit, Nutch are the most frequently targeted — focused on non-AI crawlers.
Industry Cohort
Tobacco lags the Retail & E-commerce cohort on AI-blocking policy
| WAF | Antibot | CAPTCHA | JavaScript | Rate Limit | TLS | robots.txt | Blocks AI | Tier | |
|---|---|---|---|---|---|---|---|---|---|
| Apparel & Fashion | 91% | 21% | 15% | 49% | 54% | 32% | 69% | 4% | Tier 3 |
| Beauty & Cosmetics | 91% | 30% | 36% | 40% | 31% | 30% | 76% | 13% | Tier 2 |
| Computer & Video Games | 94% | 27% | 26% | 44% | 22% | 13% | 81% | 23% | Tier 1 |
| Computer Hardware | 93% | 30% | 20% | 42% | 33% | 15% | 73% | 13% | Tier 2 |
| Computers & Electronics | 86% | 13% | 17% | 34% | 18% | 15% | 73% | 9% | Tier 2 |
| Consumer Electronics | 92% | 27% | 27% | 46% | 29% | 20% | 83% | 9% | Tier 2 |
| Equipment & Supplies | 96% | 27% | 31% | 41% | 26% | 14% | 68% | 8% | Tier 2 |
| Food & Beverages | 92% | 24% | 26% | 51% | 31% | 11% | 68% | 23% | Tier 2 |
| Furniture | 97% | 33% | 28% | 49% | 40% | 21% | 67% | 5% | Tier 2 |
| Jewelry & Luxury | 83% | 28% | 23% | 41% | 42% | 34% | 80% | 9% | Tier 2 |
| Packaging & Containers | 95% | 18% | 35% | 42% | 17% | 11% | 80% | 6% | Tier 1 |
| Retail | 96% | 19% | 15% | 51% | 33% | 20% | 85% | 29% | Tier 2 |
| Sporting Goods | 89% | 26% | 24% | 41% | 49% | 32% | 78% | 7% | Tier 2 |
| Sports | 98% | 11% | 15% | 61% | 23% | 11% | 89% | 33% | Tier 1 |
| Textiles & Nonwovens | 92% | 6% | 38% | 35% | 17% | 14% | 78% | 7% | Tier 1 |
| Tobacco | 98% | 30% | 52% | 38% | 30% | 15% | 76% | 3% | Tier 1 |
| Wholesalers & Liquidators | 94% | 24% | 22% | 44% | 30% | 13% | 80% | 7% | Tier 2 |
| Wine & Spirits | 95% | 24% | 28% | 47% | 32% | 15% | 84% | 14% | Tier 1 |
Tobacco's 3% AI-blocking rate is the lowest in the Retail & E-commerce cohort. WAF (98%) and JavaScript (38%) are at or above cohort peers on technical barriers.