CVE-2026-20251 (GCVE-0-2026-20251)
Vulnerability from cvelistv5 – Published: 2026-06-10 17:16 – Updated: 2026-06-11 03:55
VLAI
EPSS
VEX
Title
Remote Code Execution through Deserialization of Untrusted Data in Splunk Secure Gateway
Summary
In Splunk Enterprise versions below 10.2.4, 10.0.7, 9.4.12, and 9.3.13, Splunk Cloud Platform versions below 10.3.2512.12, 10.2.2510.14, 10.1.2507.22, and 9.3.2411.132, and Splunk Secure Gateway versions below 3.10.6, 3.9.20, and 3.8.67, a low-privileged user that does not hold the 'admin' or 'power' Splunk roles could perform a Remote Code Execution (RCE) through the Splunk Secure Gateway app.<br><br>The Remote Code Execution is possible because of unsafe deserialization of App Key Value Store (KV Store) data through the ‘jsonpickle’ Python library, which reconstructs arbitrary Python objects from specially crafted JavaScript Object Notation (JSON) without adequate validation.
Severity
8.8 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-10 00:00 UTC
CWE
- CWE-502 - The application deserializes untrusted data without sufficiently verifying that the resulting data will be valid.
Assigner
References
1 reference
Impacted products
3 products
| Vendor | Product | Version | |
|---|---|---|---|
| Splunk | Splunk Enterprise |
Affected:
10.2 , < 10.2.4
(custom)
Affected: 10.0 , < 10.0.7 (custom) Affected: 9.4 , < 9.4.12 (custom) Affected: 9.3 , < 9.3.13 (custom) |
|
| Splunk | Splunk Cloud Platform |
Affected:
10.3.2512 , < 10.3.2512.12
(custom)
Affected: 10.2.2510 , < 10.2.2510.14 (custom) Affected: 10.1.2507 , < 10.1.2507.22 (custom) Affected: 9.3.2411 , < 9.3.2411.132 (custom) |
|
| Splunk | Splunk Secure Gateway |
Affected:
3.10 , < 3.10.6
(custom)
Affected: 3.9 , < 3.9.20 (custom) Affected: 3.8 , < 3.8.67 (custom) |
Date Public
2026-06-10 00:00
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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.
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.
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