FKIE_CVE-2022-3188
Vulnerability from fkie_nvd - Published: 2022-12-21 23:15 - Updated: 2026-06-17 04:59
Severity
5.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
5.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
5.3 (Medium) - CVSS:3.1/
Summary
Dataprobe iBoot-PDU FW versions prior to 1.42.06162022 contain a vulnerability where unauthenticated users could open PHP index pages without authentication and download the history file from the device; the history file includes the latest actions completed by specific users.
References
| URL | Tags | ||
|---|---|---|---|
| ics-cert@hq.dhs.gov | https://www.cisa.gov/uscert/ics/advisories/icsa-22-263-03 | Patch, Third Party Advisory, US Government Resource | |
| af854a3a-2127-422b-91ae-364da2661108 | https://www.cisa.gov/uscert/ics/advisories/icsa-22-263-03 | Patch, Third Party Advisory, US Government Resource |
Impacted products
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"lastModified": "2026-06-17T04:59:01.900",
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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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