CVE-2024-47554 (GCVE-0-2024-47554)
Vulnerability from cvelistv5 – Published: 2024-10-03 11:32 – Updated: 2025-01-31 15:02
VLAI
EPSS
VEX
Title
Apache Commons IO: Possible denial of service attack on untrusted input to XmlStreamReader
Summary
Uncontrolled Resource Consumption vulnerability in Apache Commons IO.
The org.apache.commons.io.input.XmlStreamReader class may excessively consume CPU resources when processing maliciously crafted input.
This issue affects Apache Commons IO: from 2.0 before 2.14.0.
Users are recommended to upgrade to version 2.14.0 or later, which fixes the issue.
Severity
4.3 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-10-03 13:00 UTC
CWE
- CWE-400 - Uncontrolled Resource Consumption
Assigner
References
3 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Apache Software Foundation | Apache Commons IO |
Affected:
2.0 , < 2.14.0
(semver)
|
guessed |
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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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