CVE-2023-38831 (GCVE-0-2023-38831)
Vulnerability from cvelistv5 – Published: 2023-08-23 00:00 – Updated: 2026-08-05 03:55Summary
RARLAB WinRAR before 6.23 allows attackers to execute arbitrary code when a user attempts to view a benign file within a ZIP archive. The issue occurs because a ZIP archive may include a benign file (such as an ordinary .JPG file) and also a folder that has the same name as the benign file, and the contents of the folder (which may include executable content) are processed during an attempt to access only the benign file. This was exploited in the wild in April through October 2023.
Severity
7.8 (High)
SSVC
Exploitation: active
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2023-08-23 00:00 UTC
CWE
- n/a
- CWE-351 - Insufficient Type Distinction
Assigner
References
6 references
Impacted products
CISA
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 87218d7c-7733-4366-8322-ffcfacc7a1b4
Exploited: Yes
Timestamps
First Seen: 2023-08-24
Asserted: 2023-08-24
Scope
Notes: KEV entry: RARLAB WinRAR Code Execution Vulnerability | Affected: RARLAB / WinRAR | Description: RARLAB WinRAR contains an unspecified vulnerability that allows an attacker to execute code when a user attempts to view a benign file within a ZIP archive. | Required action: Apply mitigations per vendor instructions or discontinue use of the product if mitigations are unavailable. | Due date: 2023-09-14 | Known ransomware campaign use (KEV): Known | Notes (KEV): http://www.win-rar.com/singlenewsview.html?&L=0&tx_ttnews%5Btt_news%5D=232&cHash=c5bf79590657e32554c6683296a8e8aa; https://nvd.nist.gov/vuln/detail/CVE-2023-38831
Evidence
Type: Vendor Report
Signal: Successful Exploitation
Confidence: 80%
Source: cisa-kev
Details
| Cwes | CWE-351 |
|---|---|
| Feed | CISA Known Exploited Vulnerabilities Catalog |
| Product | WinRAR |
| Due Date | 2023-09-14 |
| Date Added | 2023-08-24 |
| Vendorproject | RARLAB |
| Vulnerabilityname | RARLAB WinRAR Code Execution Vulnerability |
| Knownransomwarecampaignuse | Known |
References
Created: 2026-02-02 13:24 UTC
| Updated: 2026-02-06 07:53 UTC
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: f599bfd7-e0a6-433f-8f80-c49b19c561d5
Exploited: Yes
Timestamps
First Seen: 2023-08-24
Asserted: 2023-08-24
Scope
Notes: KEVIntel entry: RARLAB WinRAR before 6.23 allows attackers to execute arbitrary code when a user attempts to view a benign file within a ZIP archive. The issue... | Affected: RARLAB / WinRAR | CVSS: 7.8 (HIGH) | Used in malware: yes | Not yet in CISA KEV: False
Evidence
Type: Public Report
Signal: Confirmed Compromise
Confidence: 70%
Source: kevintel
Details
| Feed | KEVIntel (kevintel.com) |
|---|---|
| Title | RARLAB WinRAR before 6.23 allows attackers to execute arbitrary code when a user attempts to view a benign file within a ZIP archive. The issue... |
| Vendor | RARLAB |
| Product | WinRAR |
| Added Date | 2023-08-24T00:00:00.000Z |
| Cvss Score | 7.8 |
| Epss Score | None |
| Cvss Severity | HIGH |
| Epss Percentile | None |
| Used In Malware | yes |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | False |
References
Created: 2026-06-23 11:14 UTC
| Updated: 2026-06-23 11:14 UTC
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"orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
"shortName": "mitre"
},
"references": [
{
"url": "https://www.group-ib.com/blog/cve-2023-38831-winrar-zero-day/"
},
{
"url": "https://www.bleepingcomputer.com/news/security/winrar-zero-day-exploited-since-april-to-hack-trading-accounts/"
},
{
"url": "https://news.ycombinator.com/item?id=37236100"
},
{
"url": "http://packetstormsecurity.com/files/174573/WinRAR-Remote-Code-Execution.html"
},
{
"url": "https://blog.google/threat-analysis-group/government-backed-actors-exploiting-winrar-vulnerability/"
}
]
}
},
"cveMetadata": {
"assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
"assignerShortName": "mitre",
"cveId": "CVE-2023-38831",
"datePublished": "2023-08-23T00:00:00.000Z",
"dateReserved": "2023-07-25T00:00:00.000Z",
"dateUpdated": "2026-08-05T03:55:55.112Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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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