CVE-2023-26364 (GCVE-0-2023-26364)
Vulnerability from cvelistv5 – Published: 2023-11-17 13:38 – Updated: 2024-08-29 14:12
VLAI
EPSS
VEX
Title
Denial of Service of regular expression in package @adobe/css-tools
Summary
@adobe/css-tools version 4.3.0 and earlier are affected by an Improper Input Validation vulnerability that could result in a minor denial of service while attempting to parse CSS. Exploitation of this issue does not require user interaction or privileges.
Severity
5.3 (Medium)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-08-29 14:10 UTC
CWE
- CWE-20 - Improper Input Validation (CWE-20)
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/adobe/css-tools/security/advis… | vendor-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Adobe | Not a product |
Affected:
0 , ≤ 4.3.0
(semver)
|
guessed |
Date Public
2023-08-29 17:00
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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.
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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