Vulnerability-Lookup

GHSA-FQ96-JX7G-9639

Vulnerability from github – Published: 2026-10-26 09:31 – Updated: 2026-10-26 09:31

Details

SOEM version 2.0.0 and earlier contains multiple vulnerabilities in frame processing where a malicious device can cause the master to read data outside allocated buffers. The software uses length and offset values from device messages without validating them against buffer sizes. This can cause the master to access invalid memory locations, potentially disclosing sensitive information or causing crashes.

Severity

7.1 (High)


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

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JSON

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{
  "affected": [],
  "aliases": [
    "CVE-2026-82947"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-10-26T09:16:36Z",
    "severity": "HIGH"
  },
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  "id": "GHSA-fq96-jx7g-9639",
  "modified": "2026-10-26T09:31:11Z",
  "published": "2026-10-26T09:31:11Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-82947"
    },
    {
      "type": "WEB",
      "url": "https://rt-labs.com/wp-content/uploads/2026/10/RRTL-260921-01.pdf"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:L",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2026-82947 (GCVE-0-2026-82947)

Vulnerability from cvelistv5 – Published: 2026-10-26 08:59 – Updated: 2026-10-26 08:59

Title

Multiple Out-of-Bounds Reads in Frame Processing

Summary

Severity

7.1 (High)


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

CWE

CWE-125 - Out-of-bounds read
CWE-787 - Out-of-bounds write
CWE-191 - Integer underflow (wrap or wraparound)
CWE-129 - Improper validation of array index

Assigner

ENISA CNA under the ENISA root

CNA scorecard B 80/100 over 54 records in the last 180 days details

References

1 reference

URL	Tags
https://rt-labs.com/wp-content/uploads/2026/10/RR…	vendor-advisory

Impacted products

1 product

Vendor	Product	Version
RT-Labs AB	SOEM	Affected: 0 , < 2.0.1 (semver)

Credits

f0rw4rd / quellsec.dev, alosafuzz, Brian Willows / graith.co.uk, Mayur Agnihotri

Show details on NVD website

JSON

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              "version": "0",
              "versionType": "semver"
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        }
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          "lang": "en",
          "type": "finder",
          "value": "f0rw4rd / quellsec.dev, alosafuzz, Brian Willows / graith.co.uk, Mayur Agnihotri"
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            "confidentialityImpact": "HIGH",
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          "url": "https://rt-labs.com/wp-content/uploads/2026/10/RRTL-260921-01.pdf"
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    "dateReserved": "2026-08-31T12:26:22.054Z",
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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.

Vulnerability timeline

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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.

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