CVE-2026-72818 (GCVE-0-2026-72818)
Vulnerability from cvelistv5 – Published: 2026-08-20 21:57 – Updated: 2026-08-21 11:20
VLAI
EPSS
VEX
Title
NLTK TweetTokenizer URL Pattern Backtracks Catastrophically on Naked-Domain-Like Input
Summary
The URLS regular expression in nltk/tokenize/casual.py, compiled into TweetTokenizer.WORD_RE and applied by TweetTokenizer.tokenize, contains a naked-domain branch whose domain-label prefix [a-z0-9]+(?:[.\-][a-z0-9]+)* is unbounded. Input consisting of many alternating label separators can be partitioned in exponentially many ways, and because the branch also requires a trailing top-level domain that such input never supplies, the engine explores those partitions before failing at each offset. A few kilobytes of input therefore consumes seconds to minutes of single-threaded CPU, and the HANG_RE substitution performed before matching does not collapse the pattern. TweetTokenizer is intended for tokenizing untrusted social-media text, so any service that applies it, or the module-level casual_tokenize, to submitted text can be stalled per request without authentication. Version 3.10.1 bounds the label repetition.
Severity
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-21 11:05 UTC
CWE
- CWE-1333 - Inefficient Regular Expression Complexity
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/nltk/nltk/issues/3704 | issue-tracking |
| https://github.com/nltk/nltk/blob/3.9.4/nltk/toke… | technical-description |
| https://github.com/nltk/nltk/releases/tag/v3.10.1 | release-notes |
| https://github.com/nltk/nltk | product |
| https://www.vulncheck.com/advisories/nltk-tweetto… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| nltk | nltk |
Affected:
0 , < 3.10.1
(semver)
Unaffected: 3.10.1 (semver) cpe:2.3:a:nltk:nltk:3.9.3:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.9.2:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.9.1:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.9:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.9:beta1:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.8.1:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.8:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.7:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.6.5:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.6.6:*:*:*:*:*:*:* cpe:2.3:a:nltk:nltk:3.6.7:*:*:*:*:*:*:* |
Date Public
2026-07-12 00:00
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"cweId": "CWE-1333",
"description": "Inefficient Regular Expression Complexity",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-08-21T11:20:57.674Z",
"orgId": "83251b91-4cc7-4094-a5c7-464a1b83ea10",
"shortName": "VulnCheck"
},
"references": [
{
"name": "GitHub Issue #3704",
"tags": [
"issue-tracking"
],
"url": "https://github.com/nltk/nltk/issues/3704"
},
{
"name": "Unbounded naked-domain branch in the URLS pattern at 3.9.4",
"tags": [
"technical-description"
],
"url": "https://github.com/nltk/nltk/blob/3.9.4/nltk/tokenize/casual.py"
},
{
"name": "NLTK v3.10.1 Release Notes",
"tags": [
"release-notes"
],
"url": "https://github.com/nltk/nltk/releases/tag/v3.10.1"
},
{
"tags": [
"product"
],
"url": "https://github.com/nltk/nltk"
},
{
"name": "VulnCheck Advisory: NLTK TweetTokenizer URL Pattern Backtracks Catastrophically on Naked-Domain-Like Input",
"tags": [
"third-party-advisory"
],
"url": "https://www.vulncheck.com/advisories/nltk-tweettokenizer-url-pattern-backtracks-catastrophically-on-naked-domain-like-input"
}
],
"title": "NLTK TweetTokenizer URL Pattern Backtracks Catastrophically on Naked-Domain-Like Input",
"x_generator": {
"engine": "vulncheck-endgame"
}
}
},
"cveMetadata": {
"assignerOrgId": "83251b91-4cc7-4094-a5c7-464a1b83ea10",
"assignerShortName": "VulnCheck",
"cveId": "CVE-2026-72818",
"datePublished": "2026-08-20T21:57:34.230Z",
"dateReserved": "2026-08-10T15:12:16.754Z",
"dateUpdated": "2026-08-21T11:20:57.674Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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