GHSA-G56C-H972-7RHP

Vulnerability from github – Published: 2022-05-13 01:08 – Updated: 2022-05-13 01:08
VLAI
Details

Symantec SSL Visibility (SSLV) 3.8.4FC, 3.10 prior to 3.10.4.1, 3.11, and 3.12 prior to 3.12.2.1 are vulnerable to the Return of the Bleichenbacher Oracle Threat (ROBOT) attack. All affected SSLV versions act as weak oracles according the oracle classification used in the ROBOT research paper. A remote attacker, who has captured a pre-recorded SSL session inspected by SSLV, can establish multiple millions of crafted SSL connections to the target and obtain the session keys required to decrypt the pre-recorded SSL session.

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{
  "affected": [],
  "aliases": [
    "CVE-2017-15533"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-203"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-05-17T13:29:00Z",
    "severity": "MODERATE"
  },
  "details": "Symantec SSL Visibility (SSLV) 3.8.4FC, 3.10 prior to 3.10.4.1, 3.11, and 3.12 prior to 3.12.2.1 are vulnerable to the Return of the Bleichenbacher Oracle Threat (ROBOT) attack. All affected SSLV versions act as weak oracles according the oracle classification used in the ROBOT research paper. A remote attacker, who has captured a pre-recorded SSL session inspected by SSLV, can establish multiple millions of crafted SSL connections to the target and obtain the session keys required to decrypt the pre-recorded SSL session.",
  "id": "GHSA-g56c-h972-7rhp",
  "modified": "2022-05-13T01:08:58Z",
  "published": "2022-05-13T01:08:58Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-15533"
    },
    {
      "type": "WEB",
      "url": "https://www.symantec.com/security-center/network-protection-security-advisories/SA160"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/104163"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}


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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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