Vulnerability-Lookup

GHSA-4G73-3MXF-J47W

Vulnerability from github – Published: 2022-01-14 00:02 – Updated: 2025-10-22 00:32

Details

In the case of instances where the SAML SSO authentication is enabled (non-default), session data can be modified by a malicious actor, because a user login stored in the session was not verified. Malicious unauthenticated actor may exploit this issue to escalate privileges and gain admin access to Zabbix Frontend. To perform the attack, SAML authentication is required to be enabled and the actor has to know the username of Zabbix user (or use the guest account, which is disabled by default).

Severity

9.8 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

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{
  "affected": [],
  "aliases": [
    "CVE-2022-23131"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-290"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-01-13T16:15:00Z",
    "severity": "CRITICAL"
  },
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  "id": "GHSA-4g73-3mxf-j47w",
  "modified": "2025-10-22T00:32:28Z",
  "published": "2022-01-14T00:02:17Z",
  "references": [
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      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23131"
    },
    {
      "type": "WEB",
      "url": "https://support.zabbix.com/browse/ZBX-20350"
    },
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      "url": "https://www.cisa.gov/known-exploited-vulnerabilities-catalog?field_cve=CVE-2022-23131"
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  "schema_version": "1.4.0",
  "severity": [
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      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2022-23131 (GCVE-0-2022-23131)

Vulnerability from cvelistv5 – Published: 2022-01-13 15:50 – Updated: 2025-10-21 23:15

Title

Unsafe client-side session storage leading to authentication bypass/instance takeover via Zabbix Frontend with configured SAML

Summary

Severity

9.1 (Critical)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N

SSVC

Exploitation: active Automatable: yes Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-01-29 17:20 UTC

CWE

CWE-290 - Authentication Bypass by Spoofing

Assigner

Zabbix mitre root

References

2 references

URL	Tags
https://support.zabbix.com/browse/ZBX-20350	x_refsource_MISC
https://www.cisa.gov/known-exploited-vulnerabilit…	government-resource

Impacted products

1 product

Vendor	Product	Version
Zabbix	Frontend	Affected: 5.4.0 - 5.4.8 Unaffected: 5.4.9 , < 5.4.9* (custom)

Date Public

2021-11-22 00:00

Credits

Zabbix wants to thank Thomas Chauchefoin from SonarSource for reporting this issue to us

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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.

Detection rules are retrieved from Rulezet.

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.

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.