CVE-2026-69704 (GCVE-0-2026-69704)
Vulnerability from cvelistv5 – Published: 2026-08-04 18:47 – Updated: 2026-09-24 14:18
VLAI
EPSS
VEX
Title
Atals-Livre SQL Injection via Unsanitized GET Parameter in supp()
Summary
Atals-Livre contains a SQL injection vulnerability that allows attackers to manipulate database queries by passing unsanitized input through a GET parameter to the supp() deletion helper function. Attackers can inject malicious SQL syntax via the vulnerable GET parameter to perform unauthorized database operations including data deletion and extraction.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-05 14:53 UTC
CWE
- CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/maximeAmini/Atals-Livre | product |
| https://gist.github.com/arjunjaincs/8cd878b6628d5… | technical-description |
| https://www.vulncheck.com/advisories/atals-livre-… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| maximeAmini | Atals-Livre |
Affected:
0 , ≤ de0893f
(git)
|
guessed |
Date Public
2026-08-04 00:00
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Sightings
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|---|
Nomenclature
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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.
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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.