Would this actually stop scrapers?
This is a discussion about a font-based anti-scraping technique that scrambles text characters by remapping font glyphs to hide email addresses and other sensitive text from web scrapers. The method encodes real text into gibberish in the HTML, which browsers render correctly using a custom font with a randomized character map. While this approach can stop naive and regex-based scrapers, it does not prevent targeted scrapers that can download and analyze the font to decode the text. The technique is intended to reduce spam harvesting but has trade-offs such as impacting copy-paste and screen reader accessibility.
AI Analysis
Technical Summary
The technique generates a per-user randomized font that remaps printable ASCII characters to different glyphs, effectively scrambling text such as email addresses in the HTML source. The browser renders the scrambled text as the intended readable text by applying the custom font's character map. This prevents scrapers that rely on reading the page source or DOM from easily extracting the real text. However, because the font itself contains the key to decode the text, a determined scraper can download the font file, read its cmap table, and invert the mapping to recover the original text. The method increases the cost of bulk scraping by using unique mappings per user but does not stop targeted attacks. It is a mitigation against naive scrapers rather than a full security control.
Potential Impact
The impact is primarily a reduction in the effectiveness of common web scrapers that harvest email addresses or other sensitive text by reading page source or DOM content. It can reduce spam and automated data collection from websites using this technique. However, it does not prevent determined attackers who can analyze the font files from decoding the text. Accessibility and usability are affected since copy-paste and screen readers receive the scrambled text, requiring additional accessibility attributes to mitigate.
Mitigation Recommendations
This technique itself is a mitigation against scraping but is not a security vulnerability. No patch or fix is applicable. Website operators considering this approach should understand its limitations and use it only for spam-sensitive text. They should add appropriate accessibility attributes (e.g., aria-label) to maintain usability. No urgent action is required as this is a defensive technique rather than a vulnerability. Users should evaluate if this approach fits their threat model and combine it with other anti-scraping measures if needed.
Would this actually stop scrapers?
Description
This is a discussion about a font-based anti-scraping technique that scrambles text characters by remapping font glyphs to hide email addresses and other sensitive text from web scrapers. The method encodes real text into gibberish in the HTML, which browsers render correctly using a custom font with a randomized character map. While this approach can stop naive and regex-based scrapers, it does not prevent targeted scrapers that can download and analyze the font to decode the text. The technique is intended to reduce spam harvesting but has trade-offs such as impacting copy-paste and screen reader accessibility.
Reddit Discussion
I've been watching how web-scrapers work to collect your emails and I have found a curious little project to stop them. In theory I understand how it works, e.g. it just remaps characters in a font file to be other characters, but in practice, would this stop the 95th percentile of scrapers?
I am tired of replacing my email addresses listed on my site every time a spamming scraper picks them up.
Links cited in this discussion
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The technique generates a per-user randomized font that remaps printable ASCII characters to different glyphs, effectively scrambling text such as email addresses in the HTML source. The browser renders the scrambled text as the intended readable text by applying the custom font's character map. This prevents scrapers that rely on reading the page source or DOM from easily extracting the real text. However, because the font itself contains the key to decode the text, a determined scraper can download the font file, read its cmap table, and invert the mapping to recover the original text. The method increases the cost of bulk scraping by using unique mappings per user but does not stop targeted attacks. It is a mitigation against naive scrapers rather than a full security control.
Potential Impact
The impact is primarily a reduction in the effectiveness of common web scrapers that harvest email addresses or other sensitive text by reading page source or DOM content. It can reduce spam and automated data collection from websites using this technique. However, it does not prevent determined attackers who can analyze the font files from decoding the text. Accessibility and usability are affected since copy-paste and screen readers receive the scrambled text, requiring additional accessibility attributes to mitigate.
Mitigation Recommendations
This technique itself is a mitigation against scraping but is not a security vulnerability. No patch or fix is applicable. Website operators considering this approach should understand its limitations and use it only for spam-sensitive text. They should add appropriate accessibility attributes (e.g., aria-label) to maintain usability. No urgent action is required as this is a defensive technique rather than a vulnerability. Users should evaluate if this approach fits their threat model and combine it with other anti-scraping measures if needed.
Technical Details
- Source Type
- Subreddit
- cybersecurity
- Reddit Score
- 0
- Discussion Level
- minimal
- Content Source
- reddit_link_post
- Post Type
- link
- Domain
- null
- Newsworthiness Assessment
- {"score":27,"reasons":["external_link","established_author","very_recent"],"isNewsworthy":true,"foundNewsworthy":[],"foundNonNewsworthy":[]}
- Has External Source
- true
- Trusted Domain
- false
Threat ID: 6a6099c69c2644c7f8d657c1
Added to database: 07/22/2026, 10:21:58 UTC
Last enriched: 07/22/2026, 10:22:08 UTC
Last updated: 07/22/2026, 13:51:55 UTC
Views: 10
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