VAR-202005-0398

Vulnerability from variot - Updated: 2025-01-30 21:22

TRENDnet ProView Wireless camera TV-IP512WN 1.0R 1.0.4 is vulnerable to an unauthenticated stack-based buffer overflow in handling RTSP packets. This may result in remote code execution or denial of service. The issue is in the binary rtspd (in /sbin) when parsing a long "Authorization: Basic" RTSP header. TRENDnet ProView Wireless camera TV-IP512WN Is vulnerable to out-of-bounds writes.Information is obtained, information is tampered with, and service operation is interrupted. (DoS) It may be put into a state. TRENDnet ProView Wireless camera TV-IP512WN is a wireless network camera produced by TRENDnet

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    },
    "data": "buffer error",
    "sources": [
      {
        "db": "CNNVD",
        "id": "CNNVD-202005-717"
      }
    ],
    "trust": 0.6
  }
}



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Tags
Taxonomy of the tags.


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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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