9.8
CVE-2019-18956
- EPSS 15.68%
- Veröffentlicht 17.12.2019 16:15:14
- Zuletzt bearbeitet 21.11.2024 04:33:54
- Quelle cve@mitre.org
- CVE-Watchlists
- Unerledigt
Divisa Proxia Suite 9 < 9.12.16, 9.11.19, 9.10.26, 9.9.8, 9.8.43 and 9.7.10, 10.0 < 10.0.32, and 10.1 < 10.1.5, SparkSpace 1.0 < 1.0.30, 1.1 < 1.1.2, and 1.2 < 1.2.4, and Proxia PHR 1.0 < 1.0.30 and 1.1 < 1.1.2 allows remote code execution via untrusted Java deserialization. The proxia-error cookie is insecurely deserialized in every request (GET or POST). Thus, an unauthenticated attacker can easily craft a seria1.0lized payload in order to execute arbitrary code via the prepareError function in the com.divisait.dv2ee.controller.MVCControllerServlet class of the dv2eemvc.jar component. allows remote code execution via untrusted Java deserialization. The proxia-error cookie is insecurely deserialized in every request (GET or POST). Thus, an unauthenticated attacker can easily craft a serialized payload in order to execute arbitrary code via the prepareError function in the com.divisait.dv2ee.controller.MVCControllerServlet class of the dv2eemvc.jar component. Affected products include Proxia Premium Edition 2017 and Sparkspace.
Daten sind bereitgestellt durch National Vulnerability Database (NVD)
Divisait ≫ Proxia Phr Version >= 1.0 < 1.0.30
Divisait ≫ Proxia Phr Version >= 1.1 < 1.1.2
Divisait ≫ Proxia Suite Version >= 9.0 < 9.12.16
Divisait ≫ Proxia Suite Version >= 10.0 < 10.0.32
Divisait ≫ Proxia Suite Version >= 10.1 < 10.1.5
Divisait ≫ Sparkspace Version >= 1.0 < 1.0.30
Divisait ≫ Sparkspace Version >= 1.1 < 1.1.2
Divisait ≫ Sparkspace Version >= 1.2 < 1.2.4
| Typ | Quelle | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 15.68% | 0.944 |
| Quelle | Base Score | Exploit Score | Impact Score | Vector String |
|---|---|---|---|---|
| nvd@nist.gov | 9.8 | 3.9 | 5.9 |
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
|
| nvd@nist.gov | 7.5 | 10 | 6.4 |
AV:N/AC:L/Au:N/C:P/I:P/A:P
|
CWE-502 Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.