FKIE_CVE-2008-1786
Vulnerability from fkie_nvd - Published: 2008-04-16 17:05 - Updated: 2026-06-16 22:52
Severity
Summary
The DSM gui_cm_ctrls ActiveX control (gui_cm_ctrls.ocx), as used in multiple CA products including BrightStor ARCServe Backup for Laptops and Desktops r11.5, Desktop Management Suite r11.1 through r11.2 C2; Unicenter r11.1 through r11.2 C2; and Desktop and Server Management r11.1 through r11.2 C2 allows remote attackers to execute arbitrary code via crafted function arguments.
References
Impacted products
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"descriptions": [
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"lang": "en",
"value": "The DSM gui_cm_ctrls ActiveX control (gui_cm_ctrls.ocx), as used in multiple CA products including BrightStor ARCServe Backup for Laptops and Desktops r11.5, Desktop Management Suite r11.1 through r11.2 C2; Unicenter r11.1 through r11.2 C2; and Desktop and Server Management r11.1 through r11.2 C2 allows remote attackers to execute arbitrary code via crafted function arguments."
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"value": "El control ActiveX DSM gui_cm_ctrls (archivo gui_cm_ctrls.ocx), tal y como es usado en distintos productos de CA, incluyendo a BrightStor ARCServe Backup for Laptops and Desktops versi\u00f3n r11.5, Desktop Management Suite versiones r11.1 hasta r11.2 C2; Unicenter versiones r11.1 hasta r11.2 C2; y Desktop and Server Management versiones r11.1 hasta r11.2 C2, permite a los atacantes remotos ejecutar c\u00f3digo arbitrario por medio de argumentos de funci\u00f3n dise\u00f1ados."
}
],
"id": "CVE-2008-1786",
"lastModified": "2026-06-16T22:52:29.100",
"metrics": {
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"acInsufInfo": false,
"baseSeverity": "HIGH",
"cvssData": {
"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 9.3,
"confidentialityImpact": "COMPLETE",
"integrityImpact": "COMPLETE",
"vectorString": "AV:N/AC:M/Au:N/C:C/I:C/A:C",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 10.0,
"obtainAllPrivilege": true,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
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"published": "2008-04-16T17:05:00.000",
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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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