Cyber Resilience

CVE-2026-48110

High

Published: 10 June 2026

Published
10 June 2026
Modified
11 June 2026
KEV Added
Patch
CVSS Score v3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0027 18.2th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2026-48110 is a high-severity Improper Input Validation (CWE-20) vulnerability. Its CVSS base score is 7.5 (High).

Operationally, ranked at the 18.2th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

EU & UK References

Vulnerability details

Russh is a Rust SSH client & server library. From version 0.34.0 to before version 0.61.0, several russh client and server message handlers decoded attacker-controlled SSH strings, name-lists, and byte fields into owned allocations before applying field-specific bounds. A remote…

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SSH peer could send oversized, high-fanout, or malformed length-prefixed fields and make the library allocate, attempt to allocate, or split data before rejecting input that should have been rejected earlier. This issue has been patched in version 0.61.0.

CWE(s)

Related Threats

No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.

Affected Assets

From
inferred from references and description; NVD did not file a CPE for this CVE

Mitigating Controls

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.

addresses: CWE-20

Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.

addresses: CWE-20

Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.

addresses: CWE-20

Directly implements checks on information inputs to reject invalid data before processing.

addresses: CWE-20

Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.

References