Vulnerability-Lookup

GSD-2022-30350

Vulnerability from gsd - Updated: 2023-12-13 01:19

Details

Avanquest Software RAD PDF (PDFEscape Online) 3.19.2.2 is vulnerable to Information Leak / Disclosure. The PDFEscape Online tool provides users with a "white out" functionality for redacting images, text, and other graphics from a PDF document. However, this mechanism does not remove underlying text or PDF object specification information from the PDF. As a result, for example, redacted text may be copy-pasted by a PDF reader.

Aliases

CVE-2022-30350

Aliases

CVE-2022-30350

JSON

To clipboard

{
  "GSD": {
    "alias": "CVE-2022-30350",
    "id": "GSD-2022-30350"
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
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      "id": "GSD-2022-30350",
      "modified": "2023-12-13T01:19:36.988025Z",
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}

CVE-2022-30350 (GCVE-0-2022-30350)

Vulnerability from cvelistv5 – Published: 2023-03-30 00:00 – Updated: 2025-02-18 16:22

Summary

Severity

7.5 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N

SSVC

Exploitation: poc Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-02-18 16:21 UTC

CWE

n/a
CWE-213 - Exposure of Sensitive Information Due to Incompatible Policies

Assigner

mitre mitre root

References

2 references

URL	Tags
https://www.pdfescape.com/open/
https://arxiv.org/pdf/2206.02285.pdf

Show details on NVD website

JSON

To clipboard

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  "containers": {
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        "providerMetadata": {
          "dateUpdated": "2024-08-03T06:48:35.774Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
              "x_transferred"
            ],
            "url": "https://www.pdfescape.com/open/"
          },
          {
            "tags": [
              "x_transferred"
            ],
            "url": "https://arxiv.org/pdf/2206.02285.pdf"
          }
        ],
        "title": "CVE Program Container"
      },
      {
        "metrics": [
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              "attackVector": "NETWORK",
              "availabilityImpact": "NONE",
              "baseScore": 7.5,
              "baseSeverity": "HIGH",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "NONE",
              "privilegesRequired": "NONE",
              "scope": "UNCHANGED",
              "userInteraction": "NONE",
              "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
              "version": "3.1"
            }
          },
          {
            "other": {
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                "id": "CVE-2022-30350",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-02-18T16:21:47.740431Z",
                "version": "2.0.3"
              },
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}

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.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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.