GSD-2022-24196
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
iText v7.1.17, up to (exluding)": 7.1.18 and 7.2.2 was discovered to contain an out-of-memory error via the component readStreamBytesRaw, which allows attackers to cause a Denial of Service (DoS) via a crafted PDF file.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-24196",
"description": "iText v7.1.17 was discovered to contain an out-of-memory error via the component readStreamBytesRaw, which allows attackers to cause a Denial of Service (DoS) via a crafted PDF file.",
"id": "GSD-2022-24196",
"references": [
"https://www.suse.com/security/cve/CVE-2022-24196.html"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-24196"
],
"details": "iText v7.1.17, up to (exluding)\": 7.1.18 and 7.2.2 was discovered to contain an out-of-memory error via the component readStreamBytesRaw, which allows attackers to cause a Denial of Service (DoS) via a crafted PDF file.",
"id": "GSD-2022-24196",
"modified": "2023-12-13T01:19:43.269423Z",
"schema_version": "1.4.0"
}
},
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"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
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"version": {
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"name": "https://github.com/itext/itext7/pull/78",
"refsource": "MISC",
"url": "https://github.com/itext/itext7/pull/78"
},
{
"name": "https://github.com/itext/itext7/pull/78#issuecomment-1089279222",
"refsource": "MISC",
"url": "https://github.com/itext/itext7/pull/78#issuecomment-1089279222"
},
{
"name": "https://github.com/itext/itext7/releases/tag/7.1.18",
"refsource": "MISC",
"url": "https://github.com/itext/itext7/releases/tag/7.1.18"
}
]
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "(,7.1.17]",
"affected_versions": "All versions up to 7.1.17",
"cvss_v2": "AV:N/AC:M/Au:N/C:N/I:N/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-770",
"CWE-937"
],
"date": "2022-02-10",
"description": "iText v7.1.17 was discovered to contain an out-of-memory error via the component readStreamBytesRaw, which allows attackers to cause a Denial of Service (DoS) via a crafted PDF file.",
"fixed_versions": [
"7.2.0"
],
"identifier": "CVE-2022-24196",
"identifiers": [
"GHSA-hhh6-cm2m-3fhc",
"CVE-2022-24196"
],
"not_impacted": "All versions after 7.1.17",
"package_slug": "maven/com.itextpdf/itext7-core",
"pubdate": "2022-02-02",
"solution": "Upgrade to version 7.2.0 or above.",
"title": "Allocation of Resources Without Limits or Throttling",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2022-24196",
"https://github.com/itext/itext7/pull/78",
"https://github.com/advisories/GHSA-hhh6-cm2m-3fhc"
],
"uuid": "8b5b2fb1-132f-4b8f-ba29-101e6ce97fb5"
}
]
},
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"cpe23Uri": "cpe:2.3:a:itextpdf:itext:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "7.2.2",
"vulnerable": true
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}
]
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"references": {
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"refsource": "MISC",
"tags": [
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{
"name": "https://github.com/itext/itext7/pull/78#issuecomment-1089279222",
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{
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"refsource": "MISC",
"tags": [],
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}
]
}
},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 4.3,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": true
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 6.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 3.6
}
},
"lastModifiedDate": "2023-03-24T22:15Z",
"publishedDate": "2022-02-01T20:15Z"
}
}
}
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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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