mal-2026-17339
Vulnerability from ossf_malicious_packages
Published
2026-09-30 09:30
Modified
2026-09-30 14:48
Summary
Malicious code in reactjs-risk (npm)
Details
-= Per source details. Do not edit below this line.=-
Source: amazon-inspector (0e58c82916c5199ef9e73a5d70f91d120312151eb5c28090d8bbf6dbf4117543)
The package's preinstall lifecycle script collects host identity metadata from the installer machine — os.hostname(), the output of whoami/os.userInfo().username, and os.platform() — hex-encodes the values, and issues a DNS A-record lookup for <hex>.768hgkqn53abdemu8ikzkel4g.canarytokens.com, causing the installer's hostname, username, and platform to be transmitted to the canarytoken operator on every npm install. The dns module is loaded via string concatenation ('d'+'n'+'s') and the whoami command is similarly split, indicating deliberate obfuscation of the module and command names. The package's declared main entry is an empty stub with no library functionality, so the preinstall beacon is the package's only behavior. Installing this package auto-executes an unauthenticated exfiltration of installer identity metadata to a third-party DNS endpoint the installer did not opt into.
Source: ossf-package-analysis (a32a318956967c92b753750e0b607e48db7eef07d05f25c2b687f3b9612f806e)
The OpenSSF Package Analysis project identified 'reactjs-risk' @ 99.17.1 (npm) as malicious.
It is considered malicious because:
-
The package communicates with a domain associated with malicious activity.
-
The package executes one or more commands associated with malicious behavior.
CWE
- CWE-506 - The product contains code that appears to be malicious in nature.
- CWE-506 - The product contains code that appears to be malicious in nature.
- CWE-506 - The product contains code that appears to be malicious in nature.
- CWE-506 - The product contains code that appears to be malicious in nature.
- CWE-506 - The product contains code that appears to be malicious in nature.
- CWE-506 - The product contains code that appears to be malicious in nature.
{
"affected": [
{
"database_specific": {
"cwes": [
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
},
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
},
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
},
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
},
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
},
{
"cweId": "CWE-506",
"description": "The product contains code that appears to be malicious in nature.",
"name": "Embedded Malicious Code"
}
],
"indicators": {
"evidence_files": [
{
"path": "poc.js",
"sha256": "5292bd901e13ce268893b18ff670d10b3dcc305ca08d0ce95a6dfe14ea5da4a6",
"tlsh": "c201d31317b162a4416119c1db9b84245053f3533512d1e87a9ec3465fd75904a733f5"
}
],
"package_integrity": [
{
"filename": "reactjs-risk-99.17.2.tgz",
"hashes": {
"sha1": "8c24f8798f3a55696d4bed5bbe5e540b6381a4fb",
"sha512_sri": "sha512-K40VN3M1DDdwO8Wtc3zfVTIPqK4RZPf+QE/q33ExGcl2PCybyv4xuInj1EIPyl43SDDpDhYU7I881ZK+Mmh7/Q=="
}
}
]
}
},
"package": {
"ecosystem": "npm",
"name": "reactjs-risk"
},
"versions": [
"99.17.1",
"99.17.2",
"99.9.9",
"99.17.4",
"99.12.0",
"99.17.0"
]
}
],
"credits": [
{
"contact": [
"inspector-research@amazon.com"
],
"name": "Amazon Inspector",
"type": "FINDER"
},
{
"contact": [
"https://github.com/ossf/package-analysis",
"https://openssf.slack.com/channels/package_analysis"
],
"name": "OpenSSF: Package Analysis",
"type": "FINDER"
}
],
"database_specific": {
"malicious-packages-origins": [
{
"import_time": "2026-09-30T09:46:26.826943396Z",
"modified_time": "2026-09-30T09:30:37Z",
"sha256": "a32a318956967c92b753750e0b607e48db7eef07d05f25c2b687f3b9612f806e",
"source": "ossf-package-analysis",
"versions": [
"99.17.1"
]
},
{
"import_time": "2026-09-30T10:20:20.592074968Z",
"modified_time": "2026-09-30T09:55:47Z",
"sha256": "7bb6a3319bd95ae759acafaee820c331f78291170c6895d06f5c0e78c761afd2",
"source": "ossf-package-analysis",
"versions": [
"99.17.2"
]
},
{
"id": "IN-MAL-2026-020824",
"import_time": "2026-09-30T14:21:25.406710779Z",
"modified_time": "2026-09-30T14:05:35Z",
"sha256": "0e58c82916c5199ef9e73a5d70f91d120312151eb5c28090d8bbf6dbf4117543",
"source": "amazon-inspector",
"versions": [
"99.17.2"
]
},
{
"id": "IN-MAL-2026-020823",
"import_time": "2026-09-30T14:21:25.321757098Z",
"modified_time": "2026-09-30T14:05:24Z",
"sha256": "3a5dc3ce9adff40ece4797ddd3349d25cc9e587737bde995ce0038740f72c56b",
"source": "amazon-inspector",
"versions": [
"99.17.1"
]
},
{
"id": "IN-MAL-2026-020828",
"import_time": "2026-09-30T14:46:12.515689658Z",
"modified_time": "2026-09-30T14:30:31Z",
"sha256": "54ea883450b7f65285f08f4610b55333d89153938d2618de98f2857b3b9053ca",
"source": "amazon-inspector",
"versions": [
"99.9.9"
]
},
{
"id": "IN-MAL-2026-020827",
"import_time": "2026-09-30T14:46:12.429965559Z",
"modified_time": "2026-09-30T14:30:23Z",
"sha256": "834b02617e1065531a64b675b64d6d003f8c79f6c2fc9fd9779f259c5bf05ef4",
"source": "amazon-inspector",
"versions": [
"99.17.4"
]
},
{
"id": "IN-MAL-2026-020825",
"import_time": "2026-09-30T14:46:12.193137634Z",
"modified_time": "2026-09-30T14:30:01Z",
"sha256": "a808d3c4997253da115154c5466b69ef5f4138bdb07398a475a20d54bfcba303",
"source": "amazon-inspector",
"versions": [
"99.12.0"
]
},
{
"id": "IN-MAL-2026-020826",
"import_time": "2026-09-30T14:46:12.316348692Z",
"modified_time": "2026-09-30T14:30:14Z",
"sha256": "cf0f2c8b571beb70f6c3a64b36b88bad2c3566e4889e7545eb781589921761a7",
"source": "amazon-inspector",
"versions": [
"99.17.0"
]
}
]
},
"details": "\n---\n_-= Per source details. Do not edit below this line.=-_\n\n## Source: amazon-inspector (0e58c82916c5199ef9e73a5d70f91d120312151eb5c28090d8bbf6dbf4117543)\nThe package\u0027s preinstall lifecycle script collects host identity metadata from the installer machine \u2014 os.hostname(), the output of `whoami`/os.userInfo().username, and os.platform() \u2014 hex-encodes the values, and issues a DNS A-record lookup for `\u003chex\u003e.768hgkqn53abdemu8ikzkel4g.canarytokens.com`, causing the installer\u0027s hostname, username, and platform to be transmitted to the canarytoken operator on every `npm install`. The dns module is loaded via string concatenation (`\u0027d\u0027+\u0027n\u0027+\u0027s\u0027`) and the `whoami` command is similarly split, indicating deliberate obfuscation of the module and command names. The package\u0027s declared main entry is an empty stub with no library functionality, so the preinstall beacon is the package\u0027s only behavior. Installing this package auto-executes an unauthenticated exfiltration of installer identity metadata to a third-party DNS endpoint the installer did not opt into.\n\n## Source: ossf-package-analysis (a32a318956967c92b753750e0b607e48db7eef07d05f25c2b687f3b9612f806e)\nThe OpenSSF Package Analysis project identified \u0027reactjs-risk\u0027 @ 99.17.1 (npm) as malicious.\n\nIt is considered malicious because:\n\n- The package communicates with a domain associated with malicious activity.\n\n- The package executes one or more commands associated with malicious behavior.\n",
"id": "MAL-2026-17339",
"modified": "2026-09-30T14:48:15.013405781Z",
"published": "2026-09-30T09:30:37Z",
"references": [
{
"type": "PACKAGE",
"url": "https://www.npmjs.com/package/reactjs-risk/v/99.17.2"
},
{
"type": "PACKAGE",
"url": "https://www.npmjs.com/package/reactjs-risk/v/99.17.1"
},
{
"type": "PACKAGE",
"url": "https://www.npmjs.com/package/reactjs-risk/v/99.9.9"
},
{
"type": "PACKAGE",
"url": "https://www.npmjs.com/package/reactjs-risk/v/99.17.4"
},
{
"type": "PACKAGE",
"url": "https://www.npmjs.com/package/reactjs-risk/v/99.12.0"
},
{
"type": "PACKAGE",
"url": "https://www.npmjs.com/package/reactjs-risk/v/99.17.0"
}
],
"schema_version": "1.7.4",
"summary": "Malicious code in reactjs-risk (npm)"
}
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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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