CVE-2026-20307 (GCVE-0-2026-20307)
Vulnerability from cvelistv5 – Published: 2026-09-16 16:55 – Updated: 2026-09-17 11:39
VLAI
EPSS
VEX
Title
Cisco Identity Services Engine Remote Code Execution Vulnerability
Summary
A vulnerability in the web-based management interface of Cisco ISE could allow an authenticated, remote attacker to execute arbitrary commands on the underlying operating system of an affected device. To exploit this vulnerability, the attacker must have at least low-privileged administrative credentials.
This vulnerability is due to insecure deserialization of a user-supplied Java byte stream. An attacker could exploit this vulnerability by sending a crafted serialized Java object to the web-based management interface of an affected device. A successful exploit could allow the attacker to execute arbitrary code on the device and elevate privileges to root. In single-node deployments, successful exploitation of this vulnerability could cause the affected ISE node to become unavailable, resulting in a denial of service (DoS) condition. In that condition, endpoints that have not already authenticated would be unable to access the network until the node is restored.
Severity
9.9 (Critical)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-17 03:57 UTC
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Cisco | Cisco Identity Services Engine Software |
Affected:
3.1.0
Affected: 3.1.0 p1 Affected: 3.1.0 p3 Affected: 3.1.0 p2 Affected: 3.2.0 Affected: 3.1.0 p4 Affected: 3.1.0 p5 Affected: 3.2.0 p1 Affected: 3.1.0 p6 Affected: 3.2.0 p2 Affected: 3.1.0 p7 Affected: 3.3.0 Affected: 3.2.0 p3 Affected: 3.2.0 p4 Affected: 3.1.0 p8 Affected: 3.2.0 p5 Affected: 3.2.0 p6 Affected: 3.1.0 p9 Affected: 3.3 Patch 2 Affected: 3.3 Patch 1 Affected: 3.3 Patch 3 Affected: 3.4.0 Affected: 3.2.0 p7 Affected: 3.3 Patch 4 Affected: 3.4 Patch 1 Affected: 3.1.0 p10 Affected: 3.3 Patch 5 Affected: 3.3 Patch 6 Affected: 3.4 Patch 2 Affected: 3.3 Patch 7 Affected: 3.4 Patch 3 Affected: 3.5.0 Affected: 3.4 Patch 4 Affected: 3.3 Patch 8 Affected: 3.2 Patch 8 Affected: 3.5 Patch 1 Affected: 3.3 Patch 9 Affected: 3.2 Patch 9 Affected: 3.4 Patch 5 Affected: 3.5 Patch 3 Affected: 3.5 Patch 2 Affected: 3.3 Patch 10 Affected: 3.3 Patch 11 Affected: 3.4 Patch 6 Affected: 3.2 Patch 10 Affected: 3.1.0 p72 Affected: 3.1.0 p11 |
guessed |
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}
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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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