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EUVD-2026-7943
European Vulnerability Database identifier assigned by ENISAReserved
2026-10-02 05:56
Assigner
ENISA
Alias of
a CVE record, shown under related vulnerabilities.
This identifier carries no description, severity or references of its own:
they belong to that CVE.
{
"assigner": "ENISA",
"date_reserved": "2026-10-02T05:56:40.222829+00:00",
"id": "EUVD-2026-7943"
}
CVE-2023-20190 (GCVE-0-2023-20190)
Vulnerability from cvelistv5 – Published: 2023-09-13 16:43 – Updated: 2024-08-02 09:05
VLAI
EPSS
VEX
Summary
A vulnerability in the classic access control list (ACL) compression feature of Cisco IOS XR Software could allow an unauthenticated, remote attacker to bypass the protection that is offered by a configured ACL on an affected device.
This vulnerability is due to incorrect destination address range encoding in the compression module of an ACL that is applied to an interface of an affected device. An attacker could exploit this vulnerability by sending traffic through the affected device that should be denied by the configured ACL. A successful exploit could allow the attacker to bypass configured ACL protections on the affected device, allowing the attacker to access trusted networks that the device might be protecting.
There are workarounds that address this vulnerability.
This advisory is part of the September 2023 release of the Cisco IOS XR Software Security Advisory Bundled Publication. For a complete list of the advisories and links to them, see Cisco Event Response: September 2023 Semiannual Cisco IOS XR Software Security Advisory Bundled Publication .
Severity
5.8 (Medium)
CWE
- CWE-264 - Permissions, Privileges, and Access Control
Assigner
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Cisco | Cisco IOS XR Software |
Affected:
5.2.0
Affected: 5.2.1 Affected: 5.2.2 Affected: 5.2.4 Affected: 5.2.3 Affected: 5.2.5 Affected: 5.2.47 Affected: 5.3.0 Affected: 5.3.1 Affected: 5.3.2 Affected: 5.3.3 Affected: 5.3.4 Affected: 6.0.0 Affected: 6.0.1 Affected: 6.0.2 Affected: 6.1.1 Affected: 6.1.2 Affected: 6.1.3 Affected: 6.1.4 Affected: 6.1.12 Affected: 6.1.22 Affected: 6.1.32 Affected: 6.1.36 Affected: 6.1.42 Affected: 6.2.1 Affected: 6.2.2 Affected: 6.2.3 Affected: 6.2.25 Affected: 6.2.11 Affected: 6.3.2 Affected: 6.3.3 Affected: 6.3.15 Affected: 6.4.1 Affected: 6.4.2 Affected: 6.4.3 Affected: 6.5.1 Affected: 6.5.2 Affected: 6.5.3 Affected: 6.5.25 Affected: 6.5.26 Affected: 6.5.28 Affected: 6.5.29 Affected: 6.5.32 Affected: 6.5.33 Affected: 6.6.2 Affected: 6.6.3 Affected: 6.6.25 Affected: 6.6.4 Affected: 7.0.1 Affected: 7.0.2 Affected: 7.0.12 Affected: 7.0.14 Affected: 7.1.1 Affected: 7.1.15 Affected: 7.1.2 Affected: 7.1.3 Affected: 6.7.1 Affected: 6.7.2 Affected: 6.7.3 Affected: 6.7.4 Affected: 7.2.0 Affected: 7.2.1 Affected: 7.2.2 Affected: 7.3.1 Affected: 7.3.15 Affected: 7.3.2 Affected: 7.3.3 Affected: 7.4.1 Affected: 7.4.2 Affected: 6.8.1 Affected: 6.8.2 Affected: 7.5.1 Affected: 7.5.3 Affected: 7.5.2 Affected: 7.6.1 Affected: 7.6.2 Affected: 7.7.1 Affected: 7.7.2 Affected: 6.9.1 Affected: 6.9.2 Affected: 7.8.1 |
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{
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{
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"status": "affected",
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{
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{
"status": "affected",
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{
"status": "affected",
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{
"status": "affected",
"version": "6.6.25"
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{
"status": "affected",
"version": "6.6.4"
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{
"status": "affected",
"version": "7.0.1"
},
{
"status": "affected",
"version": "7.0.2"
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{
"status": "affected",
"version": "7.0.12"
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{
"status": "affected",
"version": "7.0.14"
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{
"status": "affected",
"version": "7.1.1"
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{
"status": "affected",
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"status": "affected",
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{
"status": "affected",
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{
"status": "affected",
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"status": "affected",
"version": "7.2.2"
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"status": "affected",
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"status": "affected",
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"status": "affected",
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"status": "affected",
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"status": "affected",
"version": "7.4.1"
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"version": "7.4.2"
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"status": "affected",
"version": "6.8.1"
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"status": "affected",
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"status": "affected",
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"status": "affected",
"version": "6.9.1"
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{
"status": "affected",
"version": "6.9.2"
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}
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"exploits": [
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"state": "PUBLISHED"
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"dataType": "CVE_RECORD",
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}
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Trend slope:
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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.
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- 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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