FKIE_CVE-2026-61599
Vulnerability from fkie_nvd - Published: 2026-09-16 23:16 - Updated: 2026-09-17 14:17
Severity
Summary
djust provides Phoenix LiveView-style reactive server-side rendering for Django with Rust-powered performance. Prior to version 1.0.7, the djust live transport resolves the LiveView to mount from a client-supplied dotted path by calling `__import__(module_path, ...)`. The module is imported — running its top-level code (import side effects) — before the framework checks that the resolved object is a `LiveView` subclass and before any per-view authentication. The `LIVEVIEW_ALLOWED_MODULES` allowlist that should contain this is fail-open (`if allowed_modules:` — skipped when the setting is unset, the framework default) and uses loose `startswith` matching. An unauthenticated WebSocket client (the WS handshake does not require auth; per-view auth runs only after import + instantiate) can therefore send a `mount` / `live_redirect_mount` / `url_change` frame (or an SSE mount) with `view = "<any.importable.module>.AnyName"` and cause the server to import — and execute the top-level code of — any importable Python module by name. Version 1.0.7 fixes the issue with a fail-closed resolution gate (`djust._view_resolution.is_view_import_allowed`): a client view path resolves only if (a) its module is already loaded (`sys.modules` — so resolving runs no new code; URL-routed views loaded by URLconf at startup keep working with zero config) or (b) it matches `LIVEVIEW_ALLOWED_MODULES` on a module-segment boundary (explicit opt-in for lazily-imported views). The gate runs before `__import__` at all three sinks (+ defense-in-depth inside `_instantiate_view`). As a workaround, set `LIVEVIEW_ALLOWED_MODULES` to the narrow list of modules that contain your mountable LiveView classes. (Note: pre-patch the allowlist is `startswith`-matched and the import still precedes the subclass check, so this is mitigation, not a complete fix.)
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "djust",
"vendor": "djust-org",
"versions": [
{
"status": "affected",
"version": "\u003c 1.0.7"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "djust provides Phoenix LiveView-style reactive server-side rendering for Django with Rust-powered performance. Prior to version 1.0.7, the djust live transport resolves the LiveView to mount from a client-supplied dotted path by calling `__import__(module_path, ...)`. The module is imported \u2014 running its top-level code (import side effects) \u2014 before the framework checks that the resolved object is a `LiveView` subclass and before any per-view authentication. The `LIVEVIEW_ALLOWED_MODULES` allowlist that should contain this is fail-open (`if allowed_modules:` \u2014 skipped when the setting is unset, the framework default) and uses loose `startswith` matching. An unauthenticated WebSocket client (the WS handshake does not require auth; per-view auth runs only after import + instantiate) can therefore send a `mount` / `live_redirect_mount` / `url_change` frame (or an SSE mount) with `view = \"\u003cany.importable.module\u003e.AnyName\"` and cause the server to import \u2014 and execute the top-level code of \u2014 any importable Python module by name. Version 1.0.7 fixes the issue with a fail-closed resolution gate (`djust._view_resolution.is_view_import_allowed`): a client view path resolves only if (a) its module is already loaded (`sys.modules` \u2014 so resolving runs no new code; URL-routed views loaded by URLconf at startup keep working with zero config) or (b) it matches `LIVEVIEW_ALLOWED_MODULES` on a module-segment boundary (explicit opt-in for lazily-imported views). The gate runs before `__import__` at all three sinks (+ defense-in-depth inside `_instantiate_view`). As a workaround, set `LIVEVIEW_ALLOWED_MODULES` to the narrow list of modules that contain your mountable LiveView classes. (Note: pre-patch the allowlist is `startswith`-matched and the import still precedes the subclass check, so this is mitigation, not a complete fix.)"
}
],
"id": "CVE-2026-61599",
"lastModified": "2026-09-17T14:17:14.853",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:H/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "LOW",
"vulnConfidentialityImpact": "LOW",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-61599",
"options": [
{
"exploitation": "none"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-17T13:21:13.251135Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-16T23:16:54.010",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/djust-org/djust/releases/tag/v1.0.7"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/djust-org/djust/security/advisories/GHSA-7prp-2623-8g45"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-470"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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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.
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- 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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