CVE-2023-0435 (GCVE-0-2023-0435)
Vulnerability from cvelistv5 – Published: 2023-01-22 00:00 – Updated: 2025-04-02 15:50
VLAI
EPSS
VEX
Title
Excessive Attack Surface in pyload/pyload
Summary
Excessive Attack Surface in GitHub repository pyload/pyload prior to 0.5.0b3.dev41.
Severity
4 (Medium)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-02 15:49 UTC
CWE
- CWE-1125 - Excessive Attack Surface
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| pyload | pyload/pyload |
Affected:
unspecified , < 0.5.0b3.dev41
(custom)
|
guessed |
{
"containers": {
"adp": [
{
"providerMetadata": {
"dateUpdated": "2024-08-02T05:10:56.243Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"tags": [
"x_transferred"
],
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
},
{
"tags": [
"x_transferred"
],
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
}
],
"title": "CVE Program Container"
},
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2023-0435",
"options": [
{
"Exploitation": "poc"
},
{
"Automatable": "yes"
},
{
"Technical Impact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-02T15:49:55.092645Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2025-04-02T15:50:20.297Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"product": "pyload/pyload",
"vendor": "pyload",
"versions": [
{
"lessThan": "0.5.0b3.dev41",
"status": "affected",
"version": "unspecified",
"versionType": "custom"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Excessive Attack Surface in GitHub repository pyload/pyload prior to 0.5.0b3.dev41."
}
],
"metrics": [
{
"cvssV3_0": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 4,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.0"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-1125",
"description": "CWE-1125 Excessive Attack Surface",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2023-01-22T00:00:00.000Z",
"orgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
"shortName": "@huntrdev"
},
"references": [
{
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
},
{
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
}
],
"source": {
"advisory": "a3e32ad5-caee-4f43-b10a-4a876d4e3f1d",
"discovery": "EXTERNAL"
},
"title": "Excessive Attack Surface in pyload/pyload"
}
},
"cveMetadata": {
"assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
"assignerShortName": "@huntrdev",
"cveId": "CVE-2023-0435",
"datePublished": "2023-01-22T00:00:00.000Z",
"dateReserved": "2023-01-22T00:00:00.000Z",
"dateUpdated": "2025-04-02T15:50:20.297Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1",
"vulnerability-lookup:meta": {
"epss": {
"cve": "CVE-2023-0435",
"date": "2026-09-24",
"epss": "0.00726",
"percentile": "0.52084"
},
"fkie_nvd": {
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:pyload:pyload:*:*:*:*:*:*:*:*",
"matchCriteriaId": "DACFA9B5-22AD-4BC6-87D5-8272FF49BD56",
"versionEndIncluding": "0.4.20",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Excessive Attack Surface in GitHub repository pyload/pyload prior to 0.5.0b3.dev41."
},
{
"lang": "es",
"value": "Superficie de ataque excesiva en pyload/pyload del repositorio de GitHub anterior a 0.5.0b3.dev41."
}
],
"id": "CVE-2023-0435",
"lastModified": "2024-11-21T07:37:10.510",
"metrics": {
"cvssMetricV30": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 4.0,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.0"
},
"exploitabilityScore": 2.5,
"impactScore": 1.4,
"source": "security@huntr.dev",
"type": "Secondary"
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2023-01-22T22:15:10.177",
"references": [
{
"source": "security@huntr.dev",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
},
{
"source": "security@huntr.dev",
"tags": [
"Exploit",
"Patch",
"Third Party Advisory"
],
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Exploit",
"Patch",
"Third Party Advisory"
],
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
}
],
"sourceIdentifier": "security@huntr.dev",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-1125"
}
],
"source": "security@huntr.dev",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "NVD-CWE-Other"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"nvd": {
"cve": {
"affected": [
{
"affectedData": [
{
"product": "pyload/pyload",
"vendor": "pyload",
"versions": [
{
"lessThan": "0.5.0b3.dev41",
"status": "affected",
"version": "unspecified",
"versionType": "custom"
}
]
}
],
"source": "security@huntr.dev"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:pyload:pyload:*:*:*:*:*:*:*:*",
"matchCriteriaId": "DACFA9B5-22AD-4BC6-87D5-8272FF49BD56",
"versionEndIncluding": "0.4.20",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Excessive Attack Surface in GitHub repository pyload/pyload prior to 0.5.0b3.dev41."
},
{
"lang": "es",
"value": "Superficie de ataque excesiva en pyload/pyload del repositorio de GitHub anterior a 0.5.0b3.dev41."
}
],
"id": "CVE-2023-0435",
"lastModified": "2026-06-17T05:25:32.800",
"metrics": {
"cvssMetricV30": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 4.0,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.0"
},
"exploitabilityScore": 2.5,
"impactScore": 1.4,
"source": "security@huntr.dev",
"type": "Secondary"
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2023-0435",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-02T15:49:55.092645Z",
"version": "2.0.3"
}
}
]
},
"published": "2023-01-22T22:15:10.177",
"references": [
{
"source": "security@huntr.dev",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
},
{
"source": "security@huntr.dev",
"tags": [
"Exploit",
"Patch",
"Third Party Advisory"
],
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Exploit",
"Patch",
"Third Party Advisory"
],
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
}
],
"sourceIdentifier": "security@huntr.dev",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-1125"
}
],
"source": "security@huntr.dev",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "NVD-CWE-Other"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
},
"redhat_vex": {
"current_release_date": "2025-05-28T23:43:12+00:00",
"cve": "CVE-2023-0435",
"id": "CVE-2023-0435",
"initial_release_date": "2023-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "Excessive Attack Surface in pyload/pyload",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2023/cve-2023-0435.json",
"version": "3"
},
"vulnrichment": {
"containers": {
"adp": [
{
"providerMetadata": {
"dateUpdated": "2024-08-02T05:10:56.243Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"tags": [
"x_transferred"
],
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
},
{
"tags": [
"x_transferred"
],
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
}
],
"title": "CVE Program Container"
},
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2023-0435",
"options": [
{
"Exploitation": "poc"
},
{
"Automatable": "yes"
},
{
"Technical Impact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-02T15:49:55.092645Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2025-04-02T15:50:13.533Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"product": "pyload/pyload",
"vendor": "pyload",
"versions": [
{
"lessThan": "0.5.0b3.dev41",
"status": "affected",
"version": "unspecified",
"versionType": "custom"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Excessive Attack Surface in GitHub repository pyload/pyload prior to 0.5.0b3.dev41."
}
],
"metrics": [
{
"cvssV3_0": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 4,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.0"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-1125",
"description": "CWE-1125 Excessive Attack Surface",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2023-01-22T00:00:00.000Z",
"orgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
"shortName": "@huntrdev"
},
"references": [
{
"url": "https://huntr.dev/bounties/a3e32ad5-caee-4f43-b10a-4a876d4e3f1d"
},
{
"url": "https://github.com/pyload/pyload/commit/431ea6f0371d748df66b344a05ca1a8e0310cff3"
}
],
"source": {
"advisory": "a3e32ad5-caee-4f43-b10a-4a876d4e3f1d",
"discovery": "EXTERNAL"
},
"title": "Excessive Attack Surface in pyload/pyload"
}
},
"cveMetadata": {
"assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
"assignerShortName": "@huntrdev",
"cveId": "CVE-2023-0435",
"datePublished": "2023-01-22T00:00:00.000Z",
"dateReserved": "2023-01-22T00:00:00.000Z",
"dateUpdated": "2025-04-02T15:50:20.297Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
Loading…
Loading…
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.
Loading…
Loading…
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.
Loading…
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.
Loading…