CVE-2023-32676 (GCVE-0-2023-32676)
Vulnerability from cvelistv5 – Published: 2023-05-26 22:44 – Updated: 2024-10-15 16:29
VLAI
EPSS
VEX
Title
Autolab tar slip in Install Assessment functionality (`GHSL-2023-081`)
Summary
Autolab is a course management service that enables auto-graded programming assignments. A Tar slip vulnerability was found in the Install assessment functionality of Autolab. To exploit this vulnerability an authenticated attacker with instructor permissions needs to upload a specially crafted Tar file. Using the install assessment functionality an attacker can feed a Tar file that contain files with paths pointing outside of the target directory (e.g., `../../../../tmp/tarslipped1.sh`). When the Install assessment form is submitted the files inside of the archives are expanded to the attacker-chosen locations. This issue has been addressed in version 2.11.0. Users are advised to upgrade.
Severity
6.7 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-01-24 17:20 UTC
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/autolab/Autolab/security/advis… | x_refsource_CONFIRM |
| https://github.com/autolab/Autolab/commit/14f5084… | x_refsource_MISC |
| https://securitylab.github.com/advisories/GHSL-20… | x_refsource_MISC |
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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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