CVE-2022-38932: n/a in n/a
readelf in ToaruOS 2.0.1 has a global overflow allowing RCE when parsing a crafted ELF file.
AI Analysis
Technical Summary
CVE-2022-38932 is a high-severity vulnerability identified in the readelf utility of ToaruOS version 2.0.1. The vulnerability is classified as a global buffer overflow (CWE-787) that occurs when readelf parses a specially crafted ELF (Executable and Linkable Format) file. This overflow allows an attacker to execute arbitrary code remotely (Remote Code Execution - RCE) without requiring any privileges or user interaction. The vulnerability arises due to improper bounds checking during the parsing process, which leads to memory corruption. Exploiting this flaw could allow an attacker to compromise the system by executing malicious payloads, potentially leading to full system takeover. The CVSS v3.1 base score is 8.4, indicating a high severity with the following vector: Attack Vector: Local (AV:L), Attack Complexity: Low (AC:L), Privileges Required: None (PR:N), User Interaction: None (UI:N), Scope: Unchanged (S:U), and impacts on Confidentiality, Integrity, and Availability are all High (C:H/I:H/A:H). No patches or known exploits in the wild have been reported as of the publication date (September 27, 2022).
Potential Impact
For European organizations, the impact of this vulnerability depends largely on the adoption of ToaruOS within their infrastructure. ToaruOS is a niche operating system primarily used for educational or experimental purposes rather than mainstream enterprise deployment. However, any specialized environments or research institutions using ToaruOS could face significant risks if they process untrusted ELF files using readelf. Successful exploitation could lead to complete system compromise, data breaches, and disruption of services. Given the high impact on confidentiality, integrity, and availability, organizations relying on ToaruOS must consider this vulnerability critical. Additionally, if attackers leverage this vulnerability as a foothold, it could be used to pivot into broader network attacks. Although the attack vector is local, the lack of required privileges and user interaction lowers the barrier for exploitation by local users or malicious insiders.
Mitigation Recommendations
Since no official patches are currently available, organizations should implement strict controls to mitigate risk. These include: 1) Restricting access to systems running ToaruOS to trusted personnel only, minimizing exposure to untrusted ELF files. 2) Implementing file integrity monitoring and scanning of ELF files before processing with readelf to detect malformed or suspicious files. 3) Employing sandboxing or containerization techniques to isolate the execution of readelf, limiting potential damage from exploitation. 4) Monitoring system logs for abnormal behavior indicative of exploitation attempts. 5) Considering disabling or replacing readelf usage in workflows where possible until a patch is released. 6) Engaging with the ToaruOS community or maintainers to obtain updates or patches addressing this vulnerability. 7) Applying general hardening measures such as least privilege principles and network segmentation to reduce attack surface.
Affected Countries
Germany, France, United Kingdom, Netherlands, Sweden
CVE-2022-38932: n/a in n/a
Description
readelf in ToaruOS 2.0.1 has a global overflow allowing RCE when parsing a crafted ELF file.
AI-Powered Analysis
Technical Analysis
CVE-2022-38932 is a high-severity vulnerability identified in the readelf utility of ToaruOS version 2.0.1. The vulnerability is classified as a global buffer overflow (CWE-787) that occurs when readelf parses a specially crafted ELF (Executable and Linkable Format) file. This overflow allows an attacker to execute arbitrary code remotely (Remote Code Execution - RCE) without requiring any privileges or user interaction. The vulnerability arises due to improper bounds checking during the parsing process, which leads to memory corruption. Exploiting this flaw could allow an attacker to compromise the system by executing malicious payloads, potentially leading to full system takeover. The CVSS v3.1 base score is 8.4, indicating a high severity with the following vector: Attack Vector: Local (AV:L), Attack Complexity: Low (AC:L), Privileges Required: None (PR:N), User Interaction: None (UI:N), Scope: Unchanged (S:U), and impacts on Confidentiality, Integrity, and Availability are all High (C:H/I:H/A:H). No patches or known exploits in the wild have been reported as of the publication date (September 27, 2022).
Potential Impact
For European organizations, the impact of this vulnerability depends largely on the adoption of ToaruOS within their infrastructure. ToaruOS is a niche operating system primarily used for educational or experimental purposes rather than mainstream enterprise deployment. However, any specialized environments or research institutions using ToaruOS could face significant risks if they process untrusted ELF files using readelf. Successful exploitation could lead to complete system compromise, data breaches, and disruption of services. Given the high impact on confidentiality, integrity, and availability, organizations relying on ToaruOS must consider this vulnerability critical. Additionally, if attackers leverage this vulnerability as a foothold, it could be used to pivot into broader network attacks. Although the attack vector is local, the lack of required privileges and user interaction lowers the barrier for exploitation by local users or malicious insiders.
Mitigation Recommendations
Since no official patches are currently available, organizations should implement strict controls to mitigate risk. These include: 1) Restricting access to systems running ToaruOS to trusted personnel only, minimizing exposure to untrusted ELF files. 2) Implementing file integrity monitoring and scanning of ELF files before processing with readelf to detect malformed or suspicious files. 3) Employing sandboxing or containerization techniques to isolate the execution of readelf, limiting potential damage from exploitation. 4) Monitoring system logs for abnormal behavior indicative of exploitation attempts. 5) Considering disabling or replacing readelf usage in workflows where possible until a patch is released. 6) Engaging with the ToaruOS community or maintainers to obtain updates or patches addressing this vulnerability. 7) Applying general hardening measures such as least privilege principles and network segmentation to reduce attack surface.
Affected Countries
For access to advanced analysis and higher rate limits, contact root@offseq.com
Technical Details
- Data Version
- 5.1
- Assigner Short Name
- mitre
- Date Reserved
- 2022-08-29T00:00:00.000Z
- Cisa Enriched
- true
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 682defd5c4522896dcc016a8
Added to database: 5/21/2025, 3:23:01 PM
Last enriched: 7/7/2025, 2:41:03 PM
Last updated: 8/18/2025, 10:44:28 AM
Views: 13
Related Threats
CVE-2025-33100: CWE-798 Use of Hard-coded Credentials in IBM Concert Software
MediumCVE-2025-33090: CWE-1333 Inefficient Regular Expression Complexity in IBM Concert Software
HighCVE-2025-27909: CWE-942 Permissive Cross-domain Policy with Untrusted Domains in IBM Concert Software
MediumCVE-2025-1759: CWE-244 Improper Clearing of Heap Memory Before Release ('Heap Inspection') in IBM Concert Software
MediumCVE-2025-4962: CWE-284 Improper Access Control in lunary-ai lunary-ai/lunary
HighActions
Updates to AI analysis are available only with a Pro account. Contact root@offseq.com for access.
External Links
Need enhanced features?
Contact root@offseq.com for Pro access with improved analysis and higher rate limits.