CVE-2026-93581 (GCVE-0-2026-93581)
Vulnerability from cvelistv5 – Published: 2026-10-12 06:49 – Updated: 2026-10-12 06:49
VLAI
EPSS
VEX
Title
Insufficient Neutralization of Formula Elements in CSV Exports
Summary
User-controlled values are not sufficiently neutralized when included in CSV exports. Values originating from user input, including data submitted by authenticated users or received through external communication channels such as email, may be stored in fields that are later included in CSV exports. An attacker can therefore inject values beginning with spreadsheet formula characters such as =, +, -, or @. An attacker does not necessarily require an authenticated account if the affected field can be populated through an external input channel such as incoming email.
When an affected CSV file is opened in spreadsheet software, the application may interpret these values as formulas instead of plain text. Depending on the spreadsheet application and its security configuration, a malicious formula may cause unintended actions, disclose information, or invoke external functionality. Exploitation may require the user opening the exported CSV file to confirm one or more security warning dialogs. The vulnerability does not execute code on the OTRS server; any additional impact occurs in the spreadsheet application used to process the exported file.
This issue affects OTRS:
* 7.0.X
* 8.0.X
* 2023.X
* 2024.X
* 2025.X
* 2026.X before 2026.7.X
Please note that ((OTRS)) Community Edition 6.x and before are vulnerable. Products based on the ((OTRS)) Community Edition also very likely to be affected
Severity
6.1 (Medium)
CWE
- CWE-1236 - Improper Neutralization of Formula Elements in a CSV File.
Assigner
References
1 reference
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| OTRS GmbH (former OTRS AG) | OTRS |
Affected:
7.0.x
Affected: 8.0.x Affected: 2023.x Affected: 2024.x Affected: 2025.x Affected: 2026.x , ≤ 2026.6.x (patch) |
guessed | |
| OTRS GmbH (former OTRS AG) | ((OTRS)) Community Edition |
Affected:
6.x
|
guessed |
Date Public
2026-10-12 07:00
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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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