CVE-2023-38831
Rarlab Winrar ≤ 6.23
Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-38831 is a high-severity Insufficient Verification of Data Authenticity (CWE-345) vulnerability in Rarlab Winrar. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Junk Data (T1001.001); ranked in the top 0.0% of CVEs by exploit likelihood; CISA has added it to the Known Exploited Vulnerabilities catalog; a public proof-of-concept is referenced.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
RARLAB WinRAR versions prior to 6.23 contain a path-handling flaw that permits arbitrary code execution. When a user opens or previews a seemingly benign file such as a .JPG inside a ZIP archive, the application also processes a folder that shares the same name as the file; any executable content placed inside that folder is executed with the privileges of the user. The vulnerability is tracked as CWE-345 and CWE-351 and carries a CVSS 3.1 score of 7.8.
An attacker can deliver a crafted ZIP archive via email, download, or removable media. Once the recipient attempts to view the innocuous file, the hidden folder contents run automatically, granting the attacker remote code execution on the local system without further user interaction beyond opening the archive.
WinRAR 6.23 and subsequent releases correct the folder-name collision logic. Security advisories and vendor guidance therefore recommend immediate upgrade; organizations should also verify that older builds are removed from endpoints and build pipelines.
The issue was exploited in the wild from April through October 2023, including campaigns attributed to government-backed actors that targeted cryptocurrency trading accounts. The current EPSS of 0.9386, near its recorded peak of 0.9395, reflects sustained attacker interest after public disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-42604
Vulnerability Data
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…
more
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.
- CWE(s)
- KEV Date Added
- 24 August 2023
Related Threats
Threat-Actor AttributionAI
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.5.3
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Directly requires independent verification of matching output before adverse decisions, mitigating insufficient authenticity checks on data from external sources.
Use of approved PKI certificates provides verifiable data authenticity and origin for communications and artifacts.
Mandates provision of authenticity and integrity artifacts that enable verification of name/address resolution data.
Requires explicit verification of data authenticity from authoritative sources, preventing acceptance of unauthenticated resolution responses.
Control requires verification of data authenticity/integrity (e.g., checksums) after aggregation/packing, directly reducing exploitation of insufficient verification before transmission.
Time synchronization supports reliable freshness verification when checking data authenticity across systems or components.
Mandates verification of data authenticity for software, firmware, and information.
Provenance documentation and monitoring directly enables verification of authenticity for components and data throughout their history.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly prevent type-distinction flaws during development while the control addresses the full lifecycle.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
A.8.24's guidance on identifying protection levels, selecting algorithms/strength for authenticity/integrity (items b,f), using cryptography for transmitted/stored data (c), and key management directly stops many CWE-345 exploits by ensuring verifiable authenticity; however, it leaves a bounded remainder where verification logic itself is flawed or absent (e.g. accepting unverified signatures or weak schemes), as the control depends on correct implementation in other mechanisms.
Secure SDLC incorporates authenticity verification requirements throughout development.
Application security requirements can mandate data authenticity verification mechanisms.
A.8.27 establishes and applies secure-by-design principles (defense-in-depth, least privilege, distrust external input, fail securely, etc.) and requires design reviews against known attack patterns, but does not itself stop exploitation of a type-distinction error that has been introduced into the code.
Secure coding practices include implementing proper data authenticity checks.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.