CVE-2026-31965

March 19, 2026, 2:47 p.m.

6.9
Medium

Description

HTSlib is a library for reading and writing bioinformatics file formats. CRAM is a compressed format which stores DNA sequence alignment data. In the `cram_decode_slice()` function called while reading CRAM records, validation of the reference id field occurred too late, allowing two out of bounds reads to occur before the invalid data was detected. The bug does allow two values to be leaked to the caller, however as the function reports an error it may be difficult to exploit them. It is also possible that the program will crash due to trying to access invalid memory. Versions 1.23.1, 1.22.2 and 1.21.1 include fixes for this issue. There is no workaround for this issue.

Product(s) Impacted

Vendor Product Versions
Htslib
  • Htslib
  • *, 1.23

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-125
Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a htslib htslib / / / / / / / /
a htslib htslib / / / / / / / /
a htslib htslib 1.23 / / / / / / /

CVSS Score

6.9 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: NONE
  • Availability Impact: LOW
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: March 18, 2026, 7:16 p.m.
Last Modified: March 19, 2026, 2:47 p.m.

Status : Analyzed

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.