FKIE_CVE-2026-32611
Vulnerability from fkie_nvd - Published: 2026-03-18 18:16 - Updated: 2026-06-17 10:36
Severity
7.0 (High) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:L
9.1 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
9.1 (Critical) - CVSS:3.1/
Summary
Glances is an open-source system cross-platform monitoring tool. The GHSA-x46r fix (commit 39161f0) addressed SQL injection in the TimescaleDB export module by converting all SQL operations to use parameterized queries and `psycopg.sql` composable objects. However, the DuckDB export module (`glances/exports/glances_duckdb/__init__.py`) was not included in this fix and contains the same class of vulnerability: table names and column names derived from monitoring statistics are directly interpolated into SQL statements via f-strings. While DuckDB INSERT values already use parameterized queries (`?` placeholders), the DDL construction and table name references do not escape or parameterize identifier names. Version 4.5.3 provides a more complete fix.
References
{
"affected": [
{
"affectedData": [
{
"product": "glances",
"vendor": "nicolargo",
"versions": [
{
"status": "affected",
"version": "\u003c 4.5.2"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:nicolargo:glances:*:*:*:*:*:*:*:*",
"matchCriteriaId": "3FC19E01-80F1-43BB-912C-39FE99143A59",
"versionEndExcluding": "4.5.2",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Glances is an open-source system cross-platform monitoring tool. The GHSA-x46r fix (commit 39161f0) addressed SQL injection in the TimescaleDB export module by converting all SQL operations to use parameterized queries and `psycopg.sql` composable objects. However, the DuckDB export module (`glances/exports/glances_duckdb/__init__.py`) was not included in this fix and contains the same class of vulnerability: table names and column names derived from monitoring statistics are directly interpolated into SQL statements via f-strings. While DuckDB INSERT values already use parameterized queries (`?` placeholders), the DDL construction and table name references do not escape or parameterize identifier names. Version 4.5.3 provides a more complete fix."
},
{
"lang": "es",
"value": "Glances es una herramienta de monitoreo de sistema multiplataforma de c\u00f3digo abierto. La correcci\u00f3n GHSA-x46r (commit 39161f0) abord\u00f3 la inyecci\u00f3n SQL en el m\u00f3dulo de exportaci\u00f3n de TimescaleDB al convertir todas las operaciones SQL para usar consultas parametrizadas y objetos componibles psycopg.sql. Sin embargo, el m\u00f3dulo de exportaci\u00f3n de DuckDB (glances/exports/glances_duckdb/__init__.py) no fue incluido en esta correcci\u00f3n y contiene la misma clase de vulnerabilidad: los nombres de tabla y los nombres de columna derivados de las estad\u00edsticas de monitoreo se interpolan directamente en las sentencias SQL a trav\u00e9s de f-strings. Si bien los valores INSERT de DuckDB ya usan consultas parametrizadas (marcadores de posici\u00f3n ?), la construcci\u00f3n DDL y las referencias a nombres de tabla no escapan ni parametrizan los nombres de identificador. La versi\u00f3n 4.5.3 proporciona una correcci\u00f3n m\u00e1s completa."
}
],
"id": "CVE-2026-32611",
"lastModified": "2026-06-17T10:36:05.850",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 7.0,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:L/A:L",
"version": "3.1"
},
"exploitabilityScore": 2.2,
"impactScore": 4.7,
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 9.1,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.2,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-32611",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-03-18T18:50:55.560409Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-03-18T18:16:28.593",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch"
],
"url": "https://github.com/nicolargo/glances/commit/63b7da28895249d775202d639e5531ba63491a5c"
},
{
"source": "security-advisories@github.com",
"tags": [
"Release Notes"
],
"url": "https://github.com/nicolargo/glances/releases/tag/v4.5.2"
},
{
"source": "security-advisories@github.com",
"tags": [
"Exploit",
"Vendor Advisory"
],
"url": "https://github.com/nicolargo/glances/security/advisories/GHSA-49g7-2ww7-3vf5"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"tags": [
"Exploit",
"Vendor Advisory"
],
"url": "https://github.com/nicolargo/glances/security/advisories/GHSA-49g7-2ww7-3vf5"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-89"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
Loading…
Loading…
Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
Loading timeline…
Loading…
Loading…
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.
Loading…
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.