FKIE_CVE-2025-53884

Vulnerability from fkie_nvd - Published: 2025-09-17 13:15 - Updated: 2026-06-17 09:39
Severity
5.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
Summary
NeuVector stores user passwords and API keys using a simple, unsalted hash. This method is vulnerable to rainbow table attack (offline attack where hashes of known passwords are precomputed).
References
meissner@suse.dehttps://bugzilla.suse.com/show_bug.cgi?id=CVE-2025-53884
meissner@suse.dehttps://github.com/neuvector/neuvector/security/advisories/GHSA-8ff6-pc43-jwv3
Impacted products
Vendor Product Version
To clipboard 

{
  "affected": [
    {
      "affectedData": [
        {
          "defaultStatus": "unaffected",
          "packageName": "github.com/neuvector/neuvector",
          "product": "neuvector",
          "vendor": "SUSE",
          "versions": [
            {
              "lessThan": "5.4.6",
              "status": "affected",
              "version": "5.0.0",
              "versionType": "semver"
            }
          ]
        }
      ],
      "source": "meissner@suse.de"
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "NeuVector stores user passwords and API keys using a simple, unsalted hash. This method is vulnerable to rainbow table attack (offline attack where hashes of known passwords are precomputed)."
    },
    {
      "lang": "es",
      "value": "NeuVector almacena las contrase\u00f1as de usuario y las claves de API utilizando un hash simple y sin hash. Este m\u00e9todo es vulnerable a ataques de tabla arco\u00edris (un ataque fuera de l\u00ednea donde los hashes de contrase\u00f1as conocidas se precalculan)."
    }
  ],
  "id": "CVE-2025-53884",
  "lastModified": "2026-06-17T09:39:04.293",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 5.3,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "LOW",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 1.4,
        "source": "meissner@suse.de",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2025-53884",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "yes"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2025-09-17T13:23:56.456330Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2025-09-17T13:15:33.830",
  "references": [
    {
      "source": "meissner@suse.de",
      "url": "https://bugzilla.suse.com/show_bug.cgi?id=CVE-2025-53884"
    },
    {
      "source": "meissner@suse.de",
      "url": "https://github.com/neuvector/neuvector/security/advisories/GHSA-8ff6-pc43-jwv3"
    }
  ],
  "sourceIdentifier": "meissner@suse.de",
  "vulnStatus": "Deferred",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-759"
        }
      ],
      "source": "meissner@suse.de",
      "type": "Secondary"
    }
  ]
}



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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

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Nomenclature

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  • 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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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.