CVE-2022-29945 (GCVE-0-2022-29945)
Vulnerability from cvelistv5 – Published: 2022-04-29 19:39 – Updated: 2024-08-03 06:33
VLAI
EPSS
VEX
Summary
DJI drone devices sold in 2017 through 2022 broadcast unencrypted information about the drone operator's physical location via the AeroScope protocol.
Severity
4 (Medium)
CWE
- n/a
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://www.theverge.com/2022/4/28/23046916/dji-a… | x_refsource_MISC |
| https://twitter.com/d0tslash/status/1519774807776284672 | x_refsource_MISC |
| https://twitter.com/StarFire2258/status/151976709… | x_refsource_MISC |
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Party Advisory\"]},{\"url\":\"https://twitter.com/d0tslash/status/1519774807776284672\",\"source\":\"cve@mitre.org\",\"tags\":[\"Third Party Advisory\"]},{\"url\":\"https://www.theverge.com/2022/4/28/23046916/dji-aeroscope-signals-not-encrypted-drone-tracking\",\"source\":\"cve@mitre.org\",\"tags\":[\"Press/Media Coverage\",\"Third Party Advisory\"]},{\"url\":\"https://twitter.com/StarFire2258/status/1519767091829637120\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Third Party Advisory\"]},{\"url\":\"https://twitter.com/d0tslash/status/1519774807776284672\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Third Party Advisory\"]},{\"url\":\"https://www.theverge.com/2022/4/28/23046916/dji-aeroscope-signals-not-encrypted-drone-tracking\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Press/Media Coverage\",\"Third Party Advisory\"]}],\"evaluatorComment\":\"The vulnerable configuration displayed has \\\"-\\\" in the version component of each match string. This is because the precise mapping of the year that the relevant products were sold to a known numerical version is unknown at this time.\"}}",
"redhat_vex": {
"current_release_date": "2026-03-27T12:28:19+00:00",
"cve": "CVE-2022-29945",
"id": "CVE-2022-29945",
"initial_release_date": "2022-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "CVE-2022-29945",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2022/cve-2022-29945.json",
"version": "3"
}
}
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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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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.
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.
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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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