CVE-2026-76389 (GCVE-0-2026-76389)
Vulnerability from cvelistv5 – Published: 2026-08-19 21:35 – Updated: 2026-08-20 13:25
VLAI
EPSS
VEX
Title
Server-Side Request Forgery (SSRF) through the REST API in Cisco Talos Intelligence for Enterprise Security Cloud
Summary
In Cisco Talos Intelligence for Enterprise Security Cloud versions below 1.0.3, a user that holds a role with the get_talos_enrichment capability could send a crafted request to the Talos intelligence enrichment Representational State Transfer (REST) API endpoint and cause the instance to make an outbound request to an attacker-controlled server. The request could expose tokens that compromise all relevant data and system integrity in the Splunk instance. The vulnerability is possible because the Talos intelligence enrichment REST endpoint accepts the destination for authenticated Splunk management requests from request data. For more information see Deploy Cisco Talos Intelligence for Splunk Enterprise Security (https://help.splunk.com/en/splunk-enterprise-security-8/user-guide/8.0/introduction/deploy-cisco-talos-intelligence-for-splunk-enterprise-security-cloud-only) in the Splunk documentation.
Severity
8.8 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-20 13:25 UTC
CWE
- CWE-918 - The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination.
Assigner
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Splunk | Cisco Talos Intelligence for Enterprise Security Cloud |
Affected:
1.0 , < 1.0.3
(custom)
|
guessed |
Date Public
2026-08-19 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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