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CVE-2026-82648 (GCVE-0-2026-82648)

Vulnerability from cvelistv5 – Published: 2026-08-30 14:33 – Updated: 2026-09-02 16:00
VLAI
Title
WWBN AVideo SSRF Filter Bypass via NAT64 Hex Address
Summary
WWBN AVideo contains a server-side request forgery filter bypass vulnerability in the isSSRFSafeURL function that fails to normalize NAT64 addresses written in hexadecimal form. Attackers can bypass SSRF protections by supplying hex-encoded NAT64 addresses like 64:ff9b::a9fe:a9fe to reach cloud metadata services and loopback interfaces.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-02 16:00 UTC
CWE
  • CWE-20 - Improper Input Validation
References
Impacted products
Vendor Product Version CPE status
WWBN AVideo     cpe:2.3:a:wwbn:avideo:*:*:*:*:*:*:*:*
Create a notification for this product.
Date Public
2026-08-14 00:00
Credits
Show details on NVD website

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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.

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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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