CVE-2026-12203 (GCVE-0-2026-12203)
Vulnerability from cvelistv5 – Published: 2026-06-15 01:00 – Updated: 2026-06-15 14:47 X_Open Source
VLAI
EPSS
VEX
Title
HKUDS AI-Trader Research Export agents.csv information disclosure
Summary
A vulnerability was found in HKUDS AI-Trader up to 74caf996f78dcc0c657df8365c8544678a16e215. This affects an unknown part of the file /api/research/agents.csv of the component Research Export. Performing a manipulation results in information disclosure. Remote exploitation of the attack is possible. The exploit has been made public and could be used. This product follows a rolling release approach for continuous delivery, so version details for affected or updated releases are not provided. The patch is named 91a31aac1b0f4dbc6b8bef9f6eff0b7912e0bc65. Applying a patch is the recommended action to fix this issue. The vendor confirms: "Research export endpoints now require an authenticated agent with the research_exports capability".
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-15 14:47 UTC
Assigner
References
9 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/370846 | vdb-entry |
| https://vuldb.com/vuln/370846/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-12203 | third-party-advisory |
| https://vuldb.com/submit/830273 | third-party-advisory |
| https://github.com/HKUDS/AI-Trader/issues/242 | issue-tracking |
| https://github.com/HKUDS/AI-Trader/pull/227 | issue-trackingpatch |
| https://github.com/Dave-gilmore-aus/security-advi… | broken-linkexploit |
| https://github.com/HKUDS/AI-Trader/commit/91a31aa… | patch |
| https://github.com/HKUDS/AI-Trader/ | product |
Impacted products
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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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