CVE-2026-90583 (GCVE-0-2026-90583)
Vulnerability from cvelistv5 – Published: 2026-09-13 20:00 – Updated: 2026-09-15 17:58 X_Open Source
VLAI
EPSS
VEX
Title
kagisearch smallweb Query String Rendering sw.py index cross site scripting
Summary
A security flaw has been discovered in kagisearch smallweb up to 0ecb9c48edbf98dc7e934b54fbac43869e64b4cf. The affected element is the function index of the file app/sw.py of the component Query String Rendering. Performing a manipulation of the argument qs results in cross site scripting. The attack is possible to be carried out remotely. This product adopts a rolling release strategy to maintain continuous delivery. Therefore, version details for affected or updated releases cannot be specified. The patch is named 00b68144e583f20a6b67e29cf01bc07f57979ffb. It is recommended to apply a patch to fix this issue. Exploitability requires a raw HTTP request carrying unencoded double-quote characters in the query string - Werkzeug's request.query_string returns the raw request-target, and ordinary browsers percent-encode " as %22, so the payload only lands via netcat/curl-style raw sockets.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-15 17:58 UTC
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/403168 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/403168/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-90583 | third-party-advisory |
| https://vuldb.com/submit/913779 | third-party-advisory |
| https://github.com/kagisearch/smallweb/issues/854 | issue-tracking |
| https://github.com/kagisearch/smallweb/commit/00b… | patch |
| https://github.com/kagisearch/smallweb/ | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| kagisearch | smallweb |
Affected:
0ecb9c48edbf98dc7e934b54fbac43869e64b4cf
cpe:2.3:a:kagisearch:smallweb:*:*:*:*:*:*:*:* |
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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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