CVE-2026-28221 (GCVE-0-2026-28221)
Vulnerability from cvelistv5 – Published: 2026-04-29 17:53 – Updated: 2026-04-29 18:34
VLAI
EPSS
VEX
Title
Wazuh: Pre-auth stack-based buffer overflow in wazuh-remoted print_hex_string() due to signed char promotion on x86_64
Summary
Wazuh is a free and open source platform used for threat prevention, detection, and response. From version 4.8.0 to before version 4.14.4, a stack-based buffer overflow exists in print_hex_string() in wazuh-remoted. The bug is triggered when formatting attacker-controlled bytes using sprintf(dst_buf + 2*i, "%.2x", src_buf[i]) on platforms where char is treated as signed and the compiled code sign-extends bytes before the variadic call. For input bytes such as 0xFF, the formatting can emit "ffffffff" (8 chars) instead of "ff" (2 chars), causing an out-of-bounds write past a fixed 2049-byte stack buffer. The vulnerable path is reachable remotely prior to any agent authentication/registration logic via TCP/1514 when an oversized length prefix causes the “unexpected message (hex)” diagnostic path to run. Additionally, the same unauthenticated oversized-message diagnostic path logs an attacker-controlled hex dump to /var/ossec/logs/ossec.log for each trigger, allowing remote log amplification that can degrade monitoring fidelity and consume disk/I/O. This log amplification is reachable even without triggering the sign-extension overflow (e.g., using bytes < 0x80). This issue has been patched in version 4.14.4.
Severity
6.5 (Medium)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-29 18:34 UTC
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/wazuh/wazuh/security/advisorie… | x_refsource_CONFIRM |
| https://github.com/wazuh/wazuh/releases/tag/v4.14.4 | x_refsource_MISC |
Impacted products
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"title": "Wazuh: Pre-auth stack-based buffer overflow in wazuh-remoted print_hex_string() due to signed char promotion on x86_64",
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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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