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CVE-2025-45466VulnerabilityPublished

CVE-2025-45466: n/a

Source CVE Database V5

0

Not known to be exploited · CVSS 8.8 High.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score
8.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.6% chance of exploitation in 30 days – higher than 50% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 25 Jul 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.

What to do

AI-suggested

European organizations should immediately conduct an inventory to identify all Unitree Go1 robots in use and verify their firmware versions. Until an official patch is released, organizations should restrict network access to these devices by implementing strict network segmentation and firewall rules, limiting communication to trusted management stations only. Employing VPNs or secure tunnels for remote access can reduce exposure. Monitoring network traffic for unusual access attempts or anomalies related to these devices is critical. Organizations should also consider disabling any unnecessary remote management interfaces and changing default or hardcoded credentials if possible through configuration options or firmware updates. Engaging with Unitree Robotics for official patches or firmware updates is essential. Additionally, organizations should prepare incident response plans specific to robotic systems and train personnel on the risks associated with hardcoded credentials. For long-term security, adopting hardware or software solutions that support dynamic credential management and multi-factor authentication for robotic platforms is recommended.

Description

Unitree Go1 <= Go1_2022_05_11 is vulnerale to Incorrect Access Control due to authentication credentials being hardcoded in plaintext.

References

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