CVE-2026-27510 (GCVE-0-2026-27510)
Vulnerability from cvelistv5 – Published: 2026-02-26 18:56 – Updated: 2026-05-25 23:41
VLAI
EPSS
VEX
Title
Unitree Go2 Mobile Program Tampering Enables Root RCE
Summary
Unitree Go2 firmware versions 1.1.7 through 1.1.11, when used with the Unitree Go2 Android application (com.unitree.doggo2), are vulnerable to remote code execution due to missing integrity protection and validation of user-created programmes. The Android application stores programs in a local SQLite database (unitree_go2.db, table dog_programme) and transmits the programme_text content, including the pyCode field, to the robot. The robot's actuator_manager.py executes the supplied Python as root without integrity verification or content validation. An attacker with local access to the Android device can tamper with the stored programme record to inject arbitrary Python that executes when the user triggers the program via a controller keybinding, and the malicious binding persists across reboots. Additionally, a malicious program shared through the application's community marketplace can result in arbitrary code execution on any robot that imports and runs it.
Severity
9.6 (Critical)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-02-26 21:09 UTC
CWE
- CWE-345 - Insufficient Verification of Data Authenticity
Assigner
VulnCheck
CNA
References
3 references
| URL | Tags |
|---|---|
| https://boschko.ca/unitree-go2-rce/ | technical-descriptionexploit |
| https://shop.unitree.com/products/unitree-go2 | product |
| https://www.vulncheck.com/advisories/unitree-go2-… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| UnitreeRobotics | Unitree Go2 |
Affected:
1.1.7 , ≤ 1.1.11
(semver)
|
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Nomenclature
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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.
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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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