GHSA-7G89-3W9X-XW88

Vulnerability from github – Published: 2026-10-07 18:32 – Updated: 2026-10-07 18:32
VLAI
Details

Gophish through 0.12.1 contains a timing discrepancy vulnerability in AdminServer.Login that allows unauthenticated attackers to enumerate valid usernames by measuring login response times. Attackers can submit candidate usernames to POST /login and detect bcrypt comparison delays for existing accounts, narrowing targets for password guessing or credential stuffing.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-107269"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-208"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-10-07T16:17:46Z",
    "severity": "MODERATE"
  },
  "details": "Gophish through 0.12.1 contains a timing discrepancy vulnerability in AdminServer.Login that allows unauthenticated attackers to enumerate valid usernames by measuring login response times. Attackers can submit candidate usernames to POST /login and detect bcrypt comparison delays for existing accounts, narrowing targets for password guessing or credential stuffing.",
  "id": "GHSA-7g89-3w9x-xw88",
  "modified": "2026-10-07T18:32:09Z",
  "published": "2026-10-07T18:32:08Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-107269"
    },
    {
      "type": "WEB",
      "url": "https://blog.ostorlab.co/gophish-0121-manual-review-agentic-deep-scan.html"
    },
    {
      "type": "WEB",
      "url": "https://github.com/gophish/gophish"
    },
    {
      "type": "WEB",
      "url": "https://github.com/gophish/gophish/blob/b1648f0759c6d57ac989157c55d8b47c40254fe6/controllers/route.go#L375-L390"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/gophish-through-0.12.1-username-enumeration-via-post-login-timing-discrepancy"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/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",
      "type": "CVSS_V4"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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

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.

Loading…

Loading…

Loading…

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.


Loading…