CVE-2025-62376 (GCVE-0-2025-62376)
Vulnerability from cvelistv5 – Published: 2025-10-14 21:58 – Updated: 2025-12-03 15:25
VLAI
EPSS
VEX
Title
pwn.college DOJO vulnerable to improper authentication in workspace endpoint allowing unauthorized Windows VM access
Summary
pwn.college DOJO is an education platform for learning cybersecurity. Prior to commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef, the /workspace endpoint contains an improper authentication vulnerability that allows an attacker to access any active Windows VM without proper authorization. The vulnerability occurs in the view_desktop function where the user is retrieved via a URL parameter without verifying that the requester has administrative privileges. An attacker can supply any user ID and arbitrary password in the request parameters to impersonate another user. When requesting a Windows desktop service, the function does not validate the supplied password before generating access credentials, allowing the attacker to obtain an iframe source URL that grants full access to the target user's Windows VM. This impacts all users with active Windows VMs, as an attacker can access and modify data on the Windows machine and in the home directory of the associated Linux machine via the Z: drive. This issue has been patched in commit 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef. No known workarounds exist.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-10-15 20:11 UTC
CWE
- CWE-287 - Improper Authentication
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/pwncollege/dojo/security/advis… | x_refsource_CONFIRM |
| https://github.com/pwncollege/dojo/commit/467db0b… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| pwncollege | dojo |
Affected:
< 467db0b9ea0d9a929dc89b41f6eb59f7cfc68bef
|
guessed |
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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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