CVE-2026-68749 rrrene CVE debrief

Who should care

Users of html_sanitize_ex versions from 0.3.1 before 1.5.3 should be aware of this vulnerability and take steps to mitigate it. This includes developers and administrators who use or manage applications that rely on html_sanitize_ex for sanitizing HTML input.

Technical summary

The CVE-2026-68749 vulnerability is caused by an inefficient regular expression in the CSS scrubber of html_sanitize_ex. The declaration regex in HtmlSanitizeEx.Scrubber.CSS.scrub/1 matches property names with an unbounded greedy [-w]+ followed by a mandatory :, allowing an attacker to exhaust server CPU via a long CSS declaration in sanitized HTML. The vulnerability affects html_sanitize_ex versions from 0.3.1 before 1.5.3. An 80 KB <style> body costs roughly 2.4 seconds of scheduler time, and concurrent requests can saturate the BEAM scheduler pool, making the application unresponsive.

Defensive priority

CVE-2026-68749 has a CVSS score of 8.2 and is classified as HIGH severity. The vulnerability is caused by inefficient regular expression complexity in the CSS scrubber of html_sanitize_ex, which can be exploited by an unauthenticated remote attacker to exhaust server CPU via a long CSS declaration in sanitized HTML.

Recommended defensive actions

• Inventory and verify the version of html_sanitize_ex in use
• Apply the vendor-provided patch or upgrade to version 1.5.3 or later
• Implement compensating controls such as rate limiting or monitoring for suspicious traffic
• Monitor system performance and scheduler pool utilization
• Consider implementing additional security measures to prevent similar attacks

Evidence notes

The CVE-2026-68749 issue affects html_sanitize_ex versions from 0.3.1 before 1.5.3. The vulnerability is caused by an unbounded greedy regular expression in the CSS scrubber, which can lead to CPU exhaustion when processing long CSS declarations. An 80 KB <style> body costs roughly 2.4 seconds of scheduler time, and concurrent requests can saturate the BEAM scheduler pool, making the application unresponsive.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.