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CVE-2026-7511 (GCVE-0-2026-7511)

Vulnerability from cvelistv5 – Published: 2026-06-25 21:32 – Updated: 2026-06-26 10:37
VLAI
Title
PKCS7_verify signer confusion allows forged signatures to be accepted
Summary
PKCS7_verify signer confusion allows forged signatures, where the signer associated with a signature is not correctly bound, permitting a forged signature to be accepted.
Severity
5.9 (Medium)
CVSS:4.0/AV:A/AC:H/AT:P/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-26 10:36 UTC
CWE
  • CWE-347 - Improper Verification of Cryptographic Signature
Assigner
References
Impacted products
Vendor Product Version CPE status
wolfSSL wolfSSL Affected: 3.15.5 , ≤ 5.9.1 (semver)
guessed Create a notification for this product.
Credits
Nicholas Carlini from Anthropic
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.