CVE-2022-43769 (GCVE-0-2022-43769)
Vulnerability from cvelistv5 – Published: 2023-04-03 17:47 – Updated: 2025-10-21 23:15Title
Hitachi Vantara Pentaho Business Analytics Server - Failure to Sanitize Special Elements into a Different Plane (Special Element Injection)
Summary
Hitachi Vantara Pentaho Business Analytics Server prior to versions 9.4.0.1 and 9.3.0.2, including 8.3.x allow certain web services to set property values which contain Spring templates that are interpreted downstream.
Severity
8.8 (High)
SSVC
Exploitation: active
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-03-03 20:12 UTC
CWE
- CWE-74 - Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')
References
3 references
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Hitachi Vantara | Pentaho Business Analytics Server |
Affected:
1.0 , < 9.3.0.2
(maven)
Affected: 9.4.0.0 , < 9.4.0.1 (maven) |
CISA
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 68e73e8a-6065-4765-a949-0bfde97ab0a5
Exploited: Yes
Timestamps
First Seen: 2025-03-03
Asserted: 2025-03-03
Scope
Notes: Hitachi Vantara Pentaho BA Server Special Element Injection Vulnerability | Affected: Hitachi Vantara / Pentaho Business Analytics (BA) Server | Description: Hitachi Vantara Pentaho BA Server contains a special element injection vulnerability that allows an attacker to inject Spring templates into properties files, allowing for arbitrary command execution. | Required action: Apply mitigations per vendor instructions, follow applicable BOD 22-01 guidance for cloud services, or discontinue use of the product if mitigations are unavailable. | Due date: 2025-03-24 | Known ransomware campaign use (KEV): Unknown | Notes (KEV): https://support.pentaho.com/hc/en-us/articles/14455561548301--Resolved-Pentaho-BA-Server-Failure-to-Sanitize-Special-Elements-into-a-Different-Plane-Special-Element-Injection-Versions-before-9-4-0-1-and-9-3-0-2-including-8-3-x-Impacted-CVE-2022-43769 ; https://nvd.nist.gov/vuln/detail/CVE-2022-43769
Evidence
Type: Vendor Report
Signal: Successful Exploitation
Confidence: 80%
Source: cisa-kev
Details
| Cwes | CWE-74 |
|---|---|
| Feed | CISA Known Exploited Vulnerabilities Catalog |
| Product | Pentaho Business Analytics (BA) Server |
| Due Date | 2025-03-24 |
| Date Added | 2025-03-03 |
| Vendorproject | Hitachi Vantara |
| Vulnerabilityname | Hitachi Vantara Pentaho BA Server Special Element Injection Vulnerability |
| Knownransomwarecampaignuse | Unknown |
References
Created: 2026-10-02 08:09 CEST
| Updated: 2026-10-02 08:09 CEST
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 581b7f4c-e4f8-4636-8c1b-bc2a29297fba
Exploited: Yes
Timestamps
First Seen: 2025-03-03
Asserted: 2025-03-03
Scope
Notes: Hitachi Vantara Pentaho Business Analytics Server - Failure to Sanitize Special Elements into a Different Plane (Special Element Injection) | Affected: Hitachi Vantara / Pentaho Business Analytics Server | CVSS: 8.8 (HIGH) | EPSS: 0.9767 | Used in malware: unknown | Not yet in CISA KEV: False
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: previdian
Details
| Feed | Previdian (previdian.com) |
|---|---|
| Title | Hitachi Vantara Pentaho Business Analytics Server - Failure to Sanitize Special Elements into a Different Plane (Special Element Injection) |
| Cve Id | CVE-2022-43769 |
| Vendor | Hitachi Vantara |
| Ghsa Id | None |
| Product | Pentaho Business Analytics Server |
| Added Date | 2025-03-03T00:00:00.000Z |
| Cvss Score | 8.8 |
| Epss Score | 0.9767 |
| Previous Ids | |
| Cvss Severity | HIGH |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.99903 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2022-43769 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | False |
References
Created: 2026-10-02 09:11 CEST
| Updated: 2026-10-02 09:11 CEST
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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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