FKIE_CVE-2025-32422
Vulnerability from fkie_nvd - Published: 2026-06-18 17:16 - Updated: 2026-09-29 20:10
Severity
Summary
AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, `StepThroughItemsBlock` can iterate all the contents in a list and send them to `FileStoreBlock` for downloading one by one. Although `FileStoreBlock` has access time limits for downloading files, `StepThroughItemsBlock` can be used to slowly iterate and download relatively small files (e.g., 100M) multiple times. `StepThroughItemsBlock` does not limit the number of loops. In addition, `FileStoreBlock` does not limit the amount of disk space consumed in the current working directory. When a malicious user chooses to download too many videos, the disk space will eventually run out, causing a DoS. Version 0.6.63 patches the issue.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "AutoGPT",
"vendor": "Significant-Gravitas",
"versions": [
{
"status": "affected",
"version": "\u003c 0.6.63"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, `StepThroughItemsBlock` can iterate all the contents in a list and send them to `FileStoreBlock` for downloading one by one. Although `FileStoreBlock` has access time limits for downloading files, `StepThroughItemsBlock` can be used to slowly iterate and download relatively small files (e.g., 100M) multiple times. `StepThroughItemsBlock` does not limit the number of loops. In addition, `FileStoreBlock` does not limit the amount of disk space consumed in the current working directory. When a malicious user chooses to download too many videos, the disk space will eventually run out, causing a DoS. Version 0.6.63 patches the issue."
},
{
"lang": "es",
"value": "AutoGPT es una plataforma de automatizaci\u00f3n de flujos de trabajo para crear, desplegar y gestionar agentes de inteligencia artificial continuos. Antes de la versi\u00f3n 0.6.63, \u0027StepThroughItemsBlock\u0027 puede iterar todos los contenidos de una lista y enviarlos a \u0027FileStoreBlock\u0027 para su descarga uno por uno. Aunque \u0027FileStoreBlock\u0027 tiene l\u00edmites de tiempo de acceso para la descarga de archivos, \u0027StepThroughItemsBlock\u0027 puede utilizarse para iterar lentamente y descargar archivos relativamente peque\u00f1os (por ejemplo, 100M) varias veces. \u0027StepThroughItemsBlock\u0027 no limita el n\u00famero de bucles. Adem\u00e1s, \u0027FileStoreBlock\u0027 no limita la cantidad de espacio en disco consumido en el directorio de trabajo actual. Cuando un usuario malintencionado elige descargar demasiados v\u00eddeos, el espacio en disco se agotar\u00e1 finalmente, causando un DoS. La versi\u00f3n 0.6.63 corrige el problema."
}
],
"id": "CVE-2025-32422",
"lastModified": "2026-09-29T20:10:00.200",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 8.7,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "HIGH",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2025-32422",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-06-18T18:52:44.951623Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-06-18T17:16:26.547",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/Significant-Gravitas/AutoGPT/security/advisories/GHSA-9fr4-9jj9-mhh6"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"url": "https://github.com/Significant-Gravitas/AutoGPT/security/advisories/GHSA-9fr4-9jj9-mhh6"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-400"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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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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