CVE-2026-33545

medium

MobSF is a mobile application security testing tool used. Prior to version 4.4.6, MobSF's `read_sqlite()` function in `mobsf/MobSF/utils.py` (lines 542-566) uses Python string formatting (`%`) to construct SQL queries with table names read from a SQLite database's `sqlite_master` table. When a security analyst uses MobSF to analyze a malicious mobile application containing a crafted SQLite database, attacker-controlled table names are interpolated directly into SQL queries without parameterization or escaping. This allows an attacker to cause denial of service and achieve SQL injection. Version 4.4.6 patches the issue.

5.3

cvss medium

common vulnerability scoring system v3.1. measures intrinsic severity on a 0-10 scale.

epss 0.0004

exploitation prediction scoring system. probability this vulnerability will be exploited in the wild in the next 30 days.

kev no

cisa known exploited vulnerabilities catalog. confirmed active exploitation.

CVSS 3.1 Common Vulnerability Scoring System v3.1

5.3 / 10

MEDIUM

exploitability

Attack Vector

Network

Attack Vector (AV:N): exploitable remotely over the network — most dangerous. no physical or adjacent access needed.

Attack Complexity

High

Attack Complexity (AC:H): exploitation requires specific conditions outside the attacker's control (race condition, non-default config, etc).

Privileges Required

None

Privileges Required (PR:N): no authentication needed. any anonymous attacker can exploit this.

User Interaction

Required

User Interaction (UI:R): victim must perform some action (e.g. clicking a link, opening a file).

impact

Scope

Unchanged

Scope (S:U): impact limited to the vulnerable component.

Confidentiality

None

Confidentiality (C:N): no confidentiality impact.

Integrity

None

Integrity (I:N): no integrity impact.

Availability

High

Availability (A:H): total denial of service. attacker can fully shut down the resource.

CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:N/I:N/A:H

exploitation detection attribution advisories media timeline

activity density

rdintel assessment

composite score from 15+ signals including exploitation status, epss probability, detection coverage, and community attention. 0-100 scale.

exploitation

actively exploited

Vendor - Product Name

Apply vendor-provided patches

poc repositories (3)

researcher/exploit-poc - 42 stars - Python

security-lab/cve-checker - 18 stars - Go

detection

nuclei-template-id - critical - by projectdiscovery

sigma-rule-title - high - windows

timeline

2024-01-15 - published - CVE record created

2024-01-18 - poc - First exploit code published

2024-01-20 - kev - Added to known exploited

pocs, detection rules, timeline, advisories, and more