| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 5.4 | $0-$5k | 0.00 |
Summary
A vulnerability was found in PySpark 1.x/2.0.x/2.1.x/2.2.0 to 2.2.2/2.3.0 to 2.3.1. It has been classified as critical. Impacted is an unknown function. Performing a manipulation results in access control (Impersonation). This vulnerability was named CVE-2018-11760. The attack needs to be approached locally. There is no available exploit.
Details
A vulnerability was found in PySpark 1.x/2.0.x/2.1.x/2.2.0 to 2.2.2/2.3.0 to 2.3.1. It has been classified as critical. This affects an unknown code block. The manipulation with an unknown input leads to a access control vulnerability (Impersonation). CWE is classifying the issue as CWE-284. The product does not restrict or incorrectly restricts access to a resource from an unauthorized actor. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:
When using PySpark , it's possible for a different local user to connect to the Spark application and impersonate the user running the Spark application. This affects versions 1.x, 2.0.x, 2.1.x, 2.2.0 to 2.2.2, and 2.3.0 to 2.3.1.
The bug was discovered 01/28/2019. The weakness was presented 02/04/2019 (Website). It is possible to read the advisory at lists.apache.org. This vulnerability is uniquely identified as CVE-2018-11760 since 06/05/2018. Attacking locally is a requirement. No form of authentication is needed for exploitation. The technical details are unknown and an exploit is not publicly available. The attack technique deployed by this issue is T1068 according to MITRE ATT&CK.
The vulnerability was handled as a non-public zero-day exploit for at least 7 days. During that time the estimated underground price was around $0-$5k.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 5.4VulDB Meta Temp Score: 5.4
VulDB Base Score: 5.3
VulDB Temp Score: 5.3
VulDB Vector: 🔍
VulDB Reliability: 🔍
NVD Base Score: 5.5
NVD Vector: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
|---|---|---|---|---|---|
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
|---|---|---|---|---|---|
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
NVD Base Score: 🔍
Exploiting
Name: ImpersonationClass: Access control / Impersonation
CWE: CWE-284 / CWE-266
CAPEC: 🔍
ATT&CK: 🔍
Physical: Partially
Local: Yes
Remote: No
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
| 0-Day | Unlock | Unlock | Unlock | Unlock |
|---|---|---|---|---|
| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
06/05/2018 🔍01/28/2019 🔍
02/04/2019 🔍
02/05/2019 🔍
07/04/2023 🔍
Sources
Advisory: lists.apache.orgStatus: Not defined
CVE: CVE-2018-11760 (🔍)
GCVE (CVE): GCVE-0-2018-11760
GCVE (VulDB): GCVE-100-130443
SecurityFocus: 106786
Entry
Created: 02/05/2019 08:50Updated: 07/04/2023 14:46
Changes: 02/05/2019 08:50 (55), 05/07/2020 16:54 (1), 07/04/2023 14:46 (3)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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