Vulnerability-Lookup

GHSA-GW6G-FVJM-97C4

Vulnerability from github – Published: 2022-05-24 19:10 – Updated: 2022-05-24 19:10

Details

JBL Go 2 devices through 2021-08-09 allow remote attackers to recover speech signals from an LED on the device, via a telescope and an electro-optical sensor, aka a "Glowworm" attack. The power indicator LED of the speakers is connected directly to the power line, as a result, the intensity of a device's power indicator LED is correlative to the power consumption. The sound played by the speakers affects their power consumption and as a result is also correlative to the light intensity of the LEDs. By analyzing measurements obtained from an electro-optical sensor directed at the power indicator LEDs of the speakers, we can recover the sound played by them.

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{
  "affected": [],
  "aliases": [
    "CVE-2021-38548"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-08-11T16:15:00Z",
    "severity": "MODERATE"
  },
  "details": "JBL Go 2 devices through 2021-08-09 allow remote attackers to recover speech signals from an LED on the device, via a telescope and an electro-optical sensor, aka a \"Glowworm\" attack. The power indicator LED of the speakers is connected directly to the power line, as a result, the intensity of a device\u0027s power indicator LED is correlative to the power consumption. The sound played by the speakers affects their power consumption and as a result is also correlative to the light intensity of the LEDs. By analyzing measurements obtained from an electro-optical sensor directed at the power indicator LEDs of the speakers, we can recover the sound played by them.",
  "id": "GHSA-gw6g-fvjm-97c4",
  "modified": "2022-05-24T19:10:41Z",
  "published": "2022-05-24T19:10:41Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-38548"
    },
    {
      "type": "WEB",
      "url": "https://www.nassiben.com/glowworm-attack"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

CVE-2021-38548 (GCVE-0-2021-38548)

Vulnerability from cvelistv5 – Published: 2021-08-11 15:24 – Updated: 2024-08-04 01:44

Summary

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

1 reference

URL	Tags
https://www.nassiben.com/glowworm-attack	x_refsource_MISC

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          "dateUpdated": "2024-08-04T01:44:23.502Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
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        },
        "references": [
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://www.nassiben.com/glowworm-attack"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
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          "vendor": "n/a",
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        }
      ],
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      ],
      "providerMetadata": {
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        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
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      },
      "references": [
        {
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      "x_legacyV4Record": {
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        },
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          "vendor": {
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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.