CVE-2026-19953 (GCVE-0-2026-19953)
Vulnerability from cvelistv5 – Published: 2026-08-31 17:29 – Updated: 2026-08-31 20:07
VLAI
EPSS
VEX
Title
URI versions before 5.36 for Perl encode non-NFC host names to non-standard punycode labels via missing normalization in nameprep
Summary
URI versions before 5.36 for Perl encode non-NFC host names to non-standard punycode labels via missing normalization in nameprep.
nameprep lowercases each host label but performs no Unicode normalization. IDNA requires a label to be normalized to Form C before it is encoded (RFC 5891), so a label that is not already in NFC is encoded to a different A-label than its normalized form. A label built from the precomposed Devanagari sequence U+0958 U+093E encodes to xn--72b5c without normalization but to xn--11b2fg after NFC normalization, and xn--72b5c does not round-trip back to the original label.
Any caller that reads host() from a URI built from untrusted input and uses it for a security decision (an allow or deny list, an SSRF filter, deduplication, a cache key) sees the non-standard label, while a client that fetches the same URL resolves the NFC form, so the check and the fetch can disagree about the host.
Severity
No CVSS data available.
CWE
- CWE-1289 - Improper Validation of Unsafe Equivalence in Input
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/libwww-perl/URI/commit/956619a… | patch |
| https://github.com/libwww-perl/URI/pull/191 | issue-tracking |
| https://metacpan.org/release/OALDERS/URI-5.36/changes | release-notes |
| https://www.rfc-editor.org/rfc/rfc5891#section-5.2 | technical-description |
| http://www.openwall.com/lists/oss-security/2026/0… |
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"dateReserved": "2026-08-15T21:13:08.480Z",
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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- Confirmed: The vulnerability has been validated from an analyst's perspective.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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