CVE-2025-6518 (GCVE-0-2025-6518)
Vulnerability from cvelistv5 – Published: 2025-06-23 19:00 – Updated: 2025-06-23 19:25
VLAI
EPSS
VEX
Title
PySpur-Dev pyspur Jinja2 Template single_llm_call.py SingleLLMCallNode special elements used in a template engine
Summary
A vulnerability was found in PySpur-Dev pyspur up to 0.1.18. It has been classified as critical. Affected is the function SingleLLMCallNode of the file backend/pyspur/nodes/llm/single_llm_call.py of the component Jinja2 Template Handler. The manipulation of the argument user_message leads to improper neutralization of special elements used in a template engine. It is possible to launch the attack remotely. The exploit has been disclosed to the public and may be used.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-06-23 19:25 UTC
CWE
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.313638 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.313638 | signaturepermissions-required |
| https://vuldb.com/?submit.593612 | third-party-advisory |
| https://github.com/PySpur-Dev/pyspur/issues/289 | exploitissue-tracking |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| PySpur-Dev | pyspur |
Affected:
0.1.0
Affected: 0.1.1 Affected: 0.1.2 Affected: 0.1.3 Affected: 0.1.4 Affected: 0.1.5 Affected: 0.1.6 Affected: 0.1.7 Affected: 0.1.8 Affected: 0.1.9 Affected: 0.1.10 Affected: 0.1.11 Affected: 0.1.12 Affected: 0.1.13 Affected: 0.1.14 Affected: 0.1.15 Affected: 0.1.16 Affected: 0.1.17 Affected: 0.1.18 |
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"time": "2025-06-23T02:00:00.000Z",
"value": "VulDB entry created"
},
{
"lang": "en",
"time": "2025-06-23T14:31:45.000Z",
"value": "VulDB entry last update"
}
],
"title": "PySpur-Dev pyspur Jinja2 Template single_llm_call.py SingleLLMCallNode special elements used in a template engine"
}
},
"cveMetadata": {
"assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"assignerShortName": "VulDB",
"cveId": "CVE-2025-6518",
"datePublished": "2025-06-23T19:00:11.222Z",
"dateReserved": "2025-06-23T12:26:37.952Z",
"dateUpdated": "2025-06-23T19:25:40.707Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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