CVE-2026-61588 (GCVE-0-2026-61588)
Vulnerability from cvelistv5 – Published: 2026-09-16 22:04 – Updated: 2026-09-19 02:06
VLAI
EPSS
VEX
Title
djust's Django model serialization has no sensitive-field denylist: password hashes, privilege flags, and PII on a public view attribute are sent to the client
Summary
djust provides Phoenix LiveView-style reactive server-side rendering for Django with Rust-powered performance. Prior to version 1.0.7, when a Django `Model` instance is assigned to a public view attribute, djust serialized it to the client with no sensitive-field denylist — sending fields such as `password` (the hash), privilege flags (e.g. `is_staff` / `is_superuser`), tokens, and other PII to the browser. Because exposing model objects to templates is a normal djust pattern, this could leak credentials/PII without the developer realizing the full object crossed the wire. This is fixed in djust 1.0.7. Model serialization applies a secure-by-default sensitive-field denylist (password/hash/token/secret-style fields and known privilege flags are withheld) with an identity-subset fallback. As a workaround, keep `Model` instances on `_private` attributes and expose only the specific fields needed, until patched.
Severity
6.5 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-19 02:06 UTC
CWE
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/djust-org/djust/security/advis… | x_refsource_CONFIRM |
| https://github.com/djust-org/djust/releases/tag/v1.0.7 | x_refsource_MISC |
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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