GSD-2022-38817
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Dapr Dashboard v0.1.0 through v0.10.0 is vulnerable to Incorrect Access Control that allows attackers to obtain sensitive data.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-38817",
"description": "Dapr Dashboard v0.1.0 through v0.10.0 is vulnerable to Incorrect Access Control that allows attackers to obtain sensitive data.",
"id": "GSD-2022-38817"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
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],
"details": "Dapr Dashboard v0.1.0 through v0.10.0 is vulnerable to Incorrect Access Control that allows attackers to obtain sensitive data.",
"id": "GSD-2022-38817",
"modified": "2023-12-13T01:19:22.053848Z",
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}
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"affects": {
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{
"product": {
"product_data": [
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"name": "https://github.com/dapr/dashboard",
"refsource": "MISC",
"url": "https://github.com/dapr/dashboard"
},
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"name": "https://github.com/dapr/dashboard/issues/222",
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"url": "https://github.com/dapr/dashboard/issues/222"
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},
"gitlab.com": {
"advisories": [
{
"affected_range": "\u003e=v0.1.0 \u003c=v0.10.0",
"affected_versions": "All versions starting from 0.1.0 up to 0.10.0",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"cwe_ids": [
"CWE-1035",
"CWE-306",
"CWE-937"
],
"date": "2023-08-08",
"description": "Dapr Dashboard v0.1.0 through v0.10.0 is vulnerable to Incorrect Access Control that allows attackers to obtain sensitive data.",
"fixed_versions": [],
"identifier": "CVE-2022-38817",
"identifiers": [
"CVE-2022-38817"
],
"not_impacted": "",
"package_slug": "go/github.com/dapr/dashboard",
"pubdate": "2022-10-03",
"solution": "Unfortunately, there is no solution available yet.",
"title": "Improper Access Control",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2022-38817",
"https://github.com/dapr/dashboard/issues/222",
"https://github.com/dapr/dashboard"
],
"uuid": "1e7c6ae2-6332-406a-b848-38e681964d26",
"versions": [
{
"commit": {
"sha": "3fe41948b7657a92ab871c21b68a3444635ee17b",
"tags": [
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"timestamp": "20200706170457"
},
"number": "v0.1.0"
},
{
"commit": {
"sha": "febc4a7bca4cb992bc3fdd9799a0a87b5922f8f6",
"tags": [
"v0.10.0",
"v0.10.0-rc.1"
],
"timestamp": "20220328200551"
},
"number": "v0.10.0"
}
]
}
]
},
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"nodes": [
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{
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"versionEndIncluding": "0.10.0",
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]
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"references": {
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"tags": [
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},
{
"name": "https://github.com/dapr/dashboard",
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"tags": [
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}
},
"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2022-10-05T14:10Z",
"publishedDate": "2022-10-03T13:15Z"
}
}
}
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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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