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CVE-2016-15005 (GCVE-0-2016-15005)

Vulnerability from cvelistv5 – Published: 2022-12-27 21:13 – Updated: 2025-04-11 16:39
VLAI
Title
Cryptographically weak random number generation in github.com/dinever/golf
Summary
CSRF tokens are generated using math/rand, which is not a cryptographically secure random number generator, allowing an attacker to predict values and bypass CSRF protections with relatively few requests.
Severity
8.8 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-11 16:38 UTC
CWE
  • CWE 338: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)
Assigner
References
Impacted products
Vendor Product Version CPE status
github.com/dinever/golf github.com/dinever/golf Affected: 0 , < 0.3.0 (semver)
guessed Create a notification for this product.
Credits
@elithrar
Show details on NVD website
To clipboard 

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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

  • 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.


Detection rules are retrieved from Rulezet.


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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.