GHSA-38MG-WM59-G64X
Vulnerability from github – Published: 2025-03-20 12:32 – Updated: 2025-03-21 03:24
VLAI
Summary
composio allows Server-Side Request Forgery (SSRF) in BROWSERTOOL
Details
A Server-Side Request Forgery (SSRF) vulnerability exists in composiohq/composio version v0.4.4. This vulnerability allows an attacker to read the contents of any file in the system by exploiting the BROWSERTOOL_GOTO_PAGE and BROWSERTOOL_GET_PAGE_DETAILS actions.
Severity
6.8 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "composio-core"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "0.4.4"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2024-8955"
],
"database_specific": {
"cwe_ids": [
"CWE-643",
"CWE-918"
],
"github_reviewed": true,
"github_reviewed_at": "2025-03-21T03:24:41Z",
"nvd_published_at": "2025-03-20T10:15:45Z",
"severity": "MODERATE"
},
"details": "A Server-Side Request Forgery (SSRF) vulnerability exists in composiohq/composio version v0.4.4. This vulnerability allows an attacker to read the contents of any file in the system by exploiting the BROWSERTOOL_GOTO_PAGE and BROWSERTOOL_GET_PAGE_DETAILS actions.",
"id": "GHSA-38mg-wm59-g64x",
"modified": "2025-03-21T03:24:41Z",
"published": "2025-03-20T12:32:49Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-8955"
},
{
"type": "PACKAGE",
"url": "https://github.com/ComposioHQ/composio"
},
{
"type": "WEB",
"url": "https://github.com/ComposioHQ/composio/blob/master/python/composio/tools/local/browsertool/actions/goto_page.py#L1"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/13bc0399-2d9b-449e-95f2-6e9a7e39383d"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:C/C:H/I:N/A:N",
"type": "CVSS_V3"
}
],
"summary": "composio allows Server-Side Request Forgery (SSRF) in BROWSERTOOL"
}
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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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