CVE-2026-105315 (GCVE-0-2026-105315)
Vulnerability from cvelistv5 – Published: 2026-10-05 12:45 – Updated: 2026-10-05 13:27 X_Open Source
VLAI
EPSS
VEX
Title
django-haystack more_like_this Template Tag elasticsearch_backend.py _to_python eval injection
Summary
A vulnerability has been found in django-haystack up to 3.3.0. Affected is the function _to_python of the file haystack/backends/elasticsearch_backend.py of the component more_like_this Template Tag Handler. Such manipulation of the argument result_class leads to improper neutralization of directives in dynamically evaluated code. The attack can be launched remotely. The exploit has been disclosed to the public and may be used. Upgrading to version 3.4.0 is able to address this issue. The name of the patch is eb05f193c9771a68dcc8cfac6674a0d48a52ee9d. It is suggested to upgrade the affected component.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-05 13:27 UTC
CWE
Assigner
References
8 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/413523 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/413523/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-105315 | third-party-advisory |
| https://vuldb.com/submit/978642 | third-party-advisory |
| https://github.com/django-haystack/django-haystac… | exploit |
| https://github.com/django-haystack/django-haystac… | patch |
| https://github.com/django-haystack/django-haystac… | patch |
| https://github.com/django-haystack/django-haystack/ | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| n/a | django-haystack |
Affected:
3.0
Affected: 3.1 Affected: 3.2 Affected: 3.3.0 Unaffected: 3.4.0 cpe:2.3:a:django-haystack:django-haystack:*:*:*:*:*:*:*:* |
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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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