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CVE-2025-68705 (GCVE-0-2025-68705)

Vulnerability from cvelistv5 – Published: 2026-01-07 20:31 – Updated: 2026-01-07 21:28
VLAI
Title
RustFS Path Traversal Vulnerability
Summary
RustFS is a distributed object storage system built in Rust. In versions 1.0.0-alpha.13 to 1.0.0-alpha.78, RustFS contains a path traversal vulnerability in the /rustfs/rpc/read_file_stream endpoint. This issue has been patched in version 1.0.0-alpha.79.
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-07 21:28 UTC
CWE
  • CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
References
Impacted products
Vendor Product Version CPE status
rustfs rustfs Affected: >= 1.0.0-alpha.13, < 1.0.0-alpha.79
guessed Create a notification for this product.
Show details on NVD website

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  }
}



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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

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.

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Detection rules are retrieved from Rulezet.

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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.


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