CVE-2026-11822

June 10, 2026, 7:43 p.m.

8.5
High

Description

SQLite before 3.53.2 contains memory corruption vulnerabilities in the FTS5 full-text search extension that allow attackers to cause process crashes, memory exhaustion, or arbitrary code execution by supplying a crafted database with malformed FTS5 page data. Attackers can trigger an out-of-bounds read in fts5LeafSeek() via an attacker-controlled loop bound and a heap buffer overflow write in fts5ChunkIterate() through a crafted continuation page causing an integer underflow, exploitable when an FTS5 MATCH query is executed against the malicious database.

Product(s) Impacted

Vendor Product Versions
Sqlite
  • Sqlite
  • <3.53.2

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-122
Heap-based Buffer Overflow
A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc().

*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 sqlite sqlite <3.53.2 / / / / / / /

CVSS Score

8.5 / 10

CVSS Data - 4.0

  • Attack Vector: LOCAL
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/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: June 9, 2026, 8:16 p.m.
Last Modified: June 10, 2026, 7:43 p.m.

Status : Awaiting Analysis

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.