GHSA-2CHV-87WJ-PJV2

Vulnerability from github – Published: 2022-05-24 16:54 – Updated: 2022-11-22 18:45
VLAI
Summary
OHDSI WebAPI vulnerable to SQL Injection
Details

Observational Health Data Sciences and Informatics (OHDSI) WebAPI before 2.7.2 allows SQL injection in FeatureExtractionService.java.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Maven",
        "name": "org.ohdsi:WebAPI"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2019-15563"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-11-22T18:45:23Z",
    "nvd_published_at": "2019-08-26T15:15:00Z",
    "severity": "CRITICAL"
  },
  "details": "Observational Health Data Sciences and Informatics (OHDSI) WebAPI before 2.7.2 allows SQL injection in `FeatureExtractionService.java`.",
  "id": "GHSA-2chv-87wj-pjv2",
  "modified": "2022-11-22T18:45:23Z",
  "published": "2022-05-24T16:54:46Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-15563"
    },
    {
      "type": "WEB",
      "url": "https://github.com/OHDSI/WebAPI/pull/1101"
    },
    {
      "type": "WEB",
      "url": "https://github.com/OHDSI/WebAPI/commit/d7b12b2f5234e425e5bc76545e75de0d6eb3f8fd"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/OHDSI/WebAPI"
    },
    {
      "type": "WEB",
      "url": "https://github.com/OHDSI/WebAPI/milestone/28?closed=1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/OHDSI/WebAPI/releases/tag/v2.7.2"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "OHDSI WebAPI vulnerable to SQL Injection"
}



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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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