CVE-2026-86237 (GCVE-0-2026-86237)
Vulnerability from cvelistv5 – Published: 2026-09-07 00:15 – Updated: 2026-09-08 18:10
VLAI
EPSS
VEX
Title
openagents-org openagents http.py test_default_model server-side request forgery
Summary
A vulnerability was found in openagents-org openagents up to 0.8.19/0.9.3.post20. Impacted is the function test_default_model of the file sdk/src/openagents/sdk/transports/http.py. Performing a manipulation of the argument base_url results in server-side request forgery. The attack may be initiated remotely. The exploit has been made public and could be used. Endpoint and both sinks unchanged since filing; only the file moved (e277dd1a). Maintainer closed as inapplicable yet the identical unguarded code still ships in 0.9.3.post20. Sibling admin endpoints do call the shipped-but-unused-by-this-handler _require_admin().
Severity
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-08 18:10 UTC
CWE
- CWE-918 - Server-Side Request Forgery
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/399394 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/399394/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-86237 | third-party-advisory |
| https://vuldb.com/submit/898788 | third-party-advisory |
| https://vuldb.com/submit/901667 | third-party-advisory |
| https://github.com/openagents-org/openagents/issues/566 | exploitissue-tracking |
| https://github.com/openagents-org/openagents/ | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| openagents-org | openagents |
Affected:
0.8.0
Affected: 0.8.1 Affected: 0.8.2 Affected: 0.8.3 Affected: 0.8.4 Affected: 0.8.5 Affected: 0.8.6 Affected: 0.8.7 Affected: 0.8.8 Affected: 0.8.9 Affected: 0.8.10 Affected: 0.8.11 Affected: 0.8.12 Affected: 0.8.13 Affected: 0.8.14 Affected: 0.8.15 Affected: 0.8.16 Affected: 0.8.17 Affected: 0.8.18 Affected: 0.8.19 Affected: 0.9.3.post20 cpe:2.3:a:openagents-org:openagents:*:*:*:*:*:*:*:* |
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}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-918",
"description": "Server-Side Request Forgery",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-09-07T00:15:08.485Z",
"orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"shortName": "VulDB"
},
"references": [
{
"name": "VDB-399394 | openagents-org openagents http.py test_default_model server-side request forgery",
"tags": [
"vdb-entry",
"technical-description"
],
"url": "https://vuldb.com/vuln/399394"
},
{
"name": "VDB-399394 | CTI Indicators (IOB, IOC, IOA)",
"tags": [
"signature",
"permissions-required"
],
"url": "https://vuldb.com/vuln/399394/cti"
},
{
"name": "CVE-2026-86237 | CVE Analysis and Report",
"tags": [
"third-party-advisory"
],
"url": "https://vuldb.com/cve/CVE-2026-86237"
},
{
"name": "Submit #898788 | openagents-org OpenAgents v0.8.19 SSRF",
"tags": [
"third-party-advisory"
],
"url": "https://vuldb.com/submit/898788"
},
{
"name": "Submit #901667 | openagents-org OpenAgents v0.8.19 SSRF (Duplicate)",
"tags": [
"third-party-advisory"
],
"url": "https://vuldb.com/submit/901667"
},
{
"tags": [
"exploit",
"issue-tracking"
],
"url": "https://github.com/openagents-org/openagents/issues/566"
},
{
"tags": [
"product"
],
"url": "https://github.com/openagents-org/openagents/"
}
],
"timeline": [
{
"lang": "en",
"time": "2026-09-06T00:00:00.000Z",
"value": "Advisory disclosed"
},
{
"lang": "en",
"time": "2026-09-06T02:00:00.000Z",
"value": "VulDB entry created"
},
{
"lang": "en",
"time": "2026-09-06T10:48:32.000Z",
"value": "VulDB entry last update"
}
],
"title": "openagents-org openagents http.py test_default_model server-side request forgery",
"x_generator": [
"VulDB PVTS v202609"
]
}
},
"cveMetadata": {
"assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"assignerShortName": "VulDB",
"cveId": "CVE-2026-86237",
"datePublished": "2026-09-07T00:15:08.485Z",
"dateReserved": "2026-09-06T08:43:22.565Z",
"dateUpdated": "2026-09-08T18:10:28.355Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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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