CVE-2023-51456 (GCVE-0-2023-51456)
Vulnerability from cvelistv5 – Published: 2024-04-02 10:31 – Updated: 2024-09-30 10:03
VLAI
EPSS
VEX
Summary
A Improper Input Validation issue affecting the v2_sdk_service running on a set of DJI drone devices on the port 10000 could allow an attacker to trigger an out-of-bound read/write into the process memory through a crafted payload due to a missing input sanity check in the v2_pack_array_to_msg function implemented in the libv2_sdk.so library imported by the v2_sdk_service binary implementing the service, potentially leading to a memory information leak or an arbitrary code execution. Affected models are Mavic 3 Pro until v01.01.0300, Mavic 3 until v01.00.1200, Mavic 3 Classic until v01.00.0500, Mavic 3 Enterprise until v07.01.10.03, Matrice 300 until v57.00.01.00, Matrice M30 until v07.01.0022 and Mini 3 Pro until v01.00.0620.
Severity
6.8 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-16 01:24 UTC
Assigner
References
1 reference
Impacted products
12 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| DJI | Mavic 3 Pro |
Affected:
0 , < 01.01.0300
(custom)
|
guessed | |
| DJI | Mavic 3 |
Affected:
0 , < 01.00.1200
(custom)
|
guessed | |
| DJI | Mavic 3 Classic |
Affected:
0 , < 01.00.0500
(custom)
|
guessed | |
| DJI | Mavic 3 Enterprise |
Affected:
0 , < 7.01.10.03
(custom)
|
guessed | |
| DJI | Matrice 300 |
Affected:
0 , < 57.00.01.00
(custom)
|
guessed | |
| DJI | Matrice M30 |
Affected:
0 , < 07.01.0022
(custom)
|
guessed | |
| DJI | Mini 3 Pro |
Affected:
0 , < 01.00.0620
(custom)
|
guessed | |
| dji | mavic_3_pro_firmware |
Affected:
0 , < 01.01.0300
(custom)
cpe:2.3:o:dji:mavic_3_pro_firmware:*:*:*:*:*:*:*:* |
||
| dji | matrice_m30_firmware |
Affected:
0 , < 07.01.0022
(custom)
cpe:2.3:o:dji:matrice_m30_firmware:*:*:*:*:*:*:*:* |
||
| dji | matrice_300_firmware |
Affected:
0 , < 57.00.01.00
(custom)
cpe:2.3:o:dji:matrice_300_firmware:*:*:*:*:*:*:*:* |
||
| dji | mavic_3_firmware |
Affected:
0 , < 01.00.1200
(custom)
cpe:2.3:o:dji:mavic_3_firmware:*:*:*:*:*:*:*:* |
||
| dji | mini_3_pro_firmware |
Affected:
0 , < 01.00.0620
(custom)
cpe:2.3:o:dji:mini_3_pro_firmware:*:*:*:*:*:*:*:* |
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"url": "https://www.nozominetworks.com/labs/vulnerability-advisories-cve-2023-51456/"
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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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