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CVE-2024-49361

Estado: AplazadaAlta (8.1)—

ACON is a widely-used library of tools for machine learning that focuses on adaptive correlation optimization. A potential vulnerability has been identified in the input validation process, which could lead to arbitrary code execution if exploited. This issue could allow an attacker to submit malicious input data, bypassing input validation, resulting in remote code execution in certain machine learning applications using the ACON library. All users utilizing ACON’s input-handling functions are potentially at risk.

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Specifically, machine learning models or applications that ingest user-generated data without proper sanitization are the most vulnerable. Users running ACON on production servers are at heightened risk, as the vulnerability could be exploited remotely. As of time of publication, it is unclear whether a fix is available.

CVSS

Probabilidad de explotación (EPSS)

EPSS (Exploit Prediction Scoring System, de FIRST) estima la probabilidad de que una vulnerabilidad sea explotada en 30 días. Complementa a CVSS (impacto) y a CISA KEV (explotación confirmada).

🎯 Técnicas ATT&CK

Cómo se explota esta vulnerabilidad y qué consigue el atacante, en el lenguaje de MITRE ATT&CK.

AV:N, PR:N, UI:N indica exposición de aplicación remota sin autenticación (T1190). RCE en aplicaciones ML que procesan datos de usuario (T1059); acceso a datos de entrenamiento potencial (T1005).

Inferido por nuestro agente de análisis a partir de la descripción oficial, el vector CVSS y la CWE, y comprobado por un supervisor. Puede contener errores.

🛡️ Mitigaciones ATT&CK que cubren estas técnicas

Privileged Account ManagementVulnerability ScanningRestrict Web-Based ContentNetwork SegmentationLimit Software InstallationLimit Access to Resource Over Network

Tecnologías afectadas (1)

⚠ Inferidas por IA a partir de la descripción — NVD aún no ha analizado esta CVE; no son CPE verificados.

Ahmed Abdel-hamid Mohamed — AconAI

CWE

Referencias

JSON original (NVD)

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{
  "id": "CVE-2024-49361",
  "cveTags": [],
  "metrics": {
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2024-49361",
          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "yes"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2024-10-18T19:57:13.221660Z"
        }
      }
    ],
    "cvssMetricV40": [
      {
        "type": "Secondary",
        "source": "security-advisories@github.com",
        "cvssData": {
          "Safety": "NOT_DEFINED",
          "version": "4.0",
          "Recovery": "NOT_DEFINED",
          "baseScore": 8.1,
          "Automatable": "NOT_DEFINED",
          "attackVector": "NETWORK",
          "baseSeverity": "HIGH",
          "valueDensity": "NOT_DEFINED",
          "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
          "exploitMaturity": "UNREPORTED",
          "providerUrgency": "NOT_DEFINED",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "attackRequirements": "NONE",
          "privilegesRequired": "NONE",
          "subIntegrityImpact": "NONE",
          "vulnIntegrityImpact": "HIGH",
          "integrityRequirement": "NOT_DEFINED",
          "modifiedAttackVector": "NOT_DEFINED",
          "subAvailabilityImpact": "NONE",
          "vulnAvailabilityImpact": "HIGH",
          "availabilityRequirement": "NOT_DEFINED",
          "modifiedUserInteraction": "NOT_DEFINED",
          "modifiedAttackComplexity": "NOT_DEFINED",
          "subConfidentialityImpact": "NONE",
          "vulnConfidentialityImpact": "HIGH",
          "confidentialityRequirement": "NOT_DEFINED",
          "modifiedAttackRequirements": "NOT_DEFINED",
          "modifiedPrivilegesRequired": "NOT_DEFINED",
          "modifiedSubIntegrityImpact": "NOT_DEFINED",
          "modifiedVulnIntegrityImpact": "NOT_DEFINED",
          "vulnerabilityResponseEffort": "NOT_DEFINED",
          "modifiedSubAvailabilityImpact": "NOT_DEFINED",
          "modifiedVulnAvailabilityImpact": "NOT_DEFINED",
          "modifiedSubConfidentialityImpact": "NOT_DEFINED",
          "modifiedVulnConfidentialityImpact": "NOT_DEFINED"
        }
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    ]
  },
  "affected": [
    {
      "source": "security-advisories@github.com",
      "affectedData": [
        {
          "vendor": "torinriley",
          "product": "ACON",
          "versions": [
            {
              "status": "affected",
              "version": "<= 1.1.0"
            }
          ]
        }
      ]
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "affectedData": [
        {
          "cpes": [
            "cpe:2.3:a:acon:acon:*:*:*:*:*:*:*:*"
          ],
          "vendor": "acon",
          "product": "acon",
          "versions": [
            {
              "status": "affected",
              "version": "0",
              "versionType": "custom",
              "lessThanOrEqual": "1.1.0"
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          ],
          "defaultStatus": "unknown"
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      ]
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  ],
  "published": "2024-10-18T19:15:14.393",
  "references": [
    {
      "url": "https://github.com/torinriley/ACON/security/advisories/GHSA-345g-6rmp-3cv9",
      "source": "security-advisories@github.com"
    }
  ],
  "vulnStatus": "Deferred",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-20"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "ACON is a widely-used library of tools for machine learning that focuses on adaptive correlation optimization. A potential vulnerability has been identified in the input validation process, which could lead to arbitrary code execution if exploited. This issue could allow an attacker to submit malicious input data, bypassing input validation, resulting in remote code execution in certain machine learning applications using the ACON library. All users utilizing ACON’s input-handling functions are potentially at risk. Specifically, machine learning models or applications that ingest user-generated data without proper sanitization are the most vulnerable. Users running ACON on production servers are at heightened risk, as the vulnerability could be exploited remotely. As of time of publication, it is unclear whether a fix is available."
    },
    {
      "lang": "es",
      "value": "ACON es una librería de herramientas de aprendizaje automático ampliamente utilizada que se centra en la optimización de la correlación adaptativa. Se ha identificado una vulnerabilidad potencial en el proceso de validación de entrada, que podría provocar la ejecución de código arbitrario si se explota. Este problema podría permitir que un atacante envíe datos de entrada maliciosos, evitando la validación de entrada, lo que da como resultado la ejecución remota de código en ciertas aplicaciones de aprendizaje automático que utilizan la librería ACON. Todos los usuarios que utilizan las funciones de manejo de entrada de ACON corren un riesgo potencial. En concreto, los modelos o aplicaciones de aprendizaje automático que ingieren datos generados por el usuario sin una desinfección adecuada son los más vulnerables. Los usuarios que ejecutan ACON en servidores de producción corren un mayor riesgo, ya que la vulnerabilidad podría explotarse de forma remota. Al momento de la publicación, no está claro si hay una solución disponible."
    }
  ],
  "lastModified": "2026-06-17T07:59:45.973",
  "sourceIdentifier": "security-advisories@github.com"
}