CVE-2026-46858 (GCVE-0-2026-46858)
Vulnerability from cvelistv5 – Published: 2026-06-16 19:27 – Updated: 2026-06-17 14:40
VLAI
EPSS
VEX
Summary
Vulnerability in the APM - Application Performance Management product of Oracle Enterprise Manager (component: JADM, JVM Diagnostics). Supported versions that are affected are 13.5 and 24.1. Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP to compromise APM - Application Performance Management. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all APM - Application Performance Management accessible data and unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of APM - Application Performance Management. CVSS 3.1 Base Score 9.1 (Integrity and Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H).
Severity
9.1 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-17 14:38 UTC
CWE
- Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP to compromise APM - Application Performance Management. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all APM - Application Performance Management accessible data and unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of APM - Application Performance Management.
- CWE-284 - Improper Access Control
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://www.oracle.com/security-alerts/cspujun2026.html | vendor-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Oracle Corporation | APM - Application Performance Management |
Affected:
13.5
(semver)
Affected: 24.1 (semver) cpe:2.3:a:oracle:apm_-_application_performance_management:13.5:*:*:*:*:*:*:* cpe:2.3:a:oracle:apm_-_application_performance_management:24.1:*:*:*:*:*:*:* |
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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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