Qualcomm Snapdragon Compute/Snapdragon Industrial IOT up to X2 Elite memory corruption

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
8.1$0-$5k0.85+

Summaryinfo

A vulnerability identified as very critical has been detected in Qualcomm Snapdragon Compute and Snapdragon Industrial IOT. The impacted element is an unknown function. This manipulation causes memory corruption. This vulnerability appears as CVE-2026-25280. The attack requires local access. There is no available exploit. You should upgrade the affected component.

Detailsinfo

A vulnerability was found in Qualcomm Snapdragon Compute and Snapdragon Industrial IOT. It has been declared as very critical. Affected by this vulnerability is some unknown functionality. The manipulation with an unknown input leads to a memory corruption vulnerability. The CWE definition for the vulnerability is CWE-119. The product performs operations on a memory buffer, but it can read from or write to a memory location that is outside of the intended boundary of the buffer. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

Memory corruption when processing escape handling flow with insufficient user buffer sizes.

It is possible to read the advisory at docs.qualcomm.com. This vulnerability is known as CVE-2026-25280 since 02/02/2026. The exploitation appears to be easy. Attacking locally is a requirement. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 09/17/2026).

Upgrading eliminates this vulnerability.

The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2026-81327). Be aware that VulDB is the high quality source for vulnerability data.

Productinfo

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Vendor

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 8.3
VulDB Meta Temp Score: 8.1

VulDB Base Score: 8.8
VulDB Temp Score: 8.4
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 7.8
CNA Vector (qualcomm): 🔒

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Memory corruption
CWE: CWE-119
CAPEC: 🔒
ATT&CK: 🔒

Physical: Partially
Local: Yes
Remote: No

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔒

Timelineinfo

02/02/2026 CVE reserved
09/17/2026 +226 days Advisory disclosed
09/17/2026 +0 days VulDB entry created
09/17/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: qualcomm.com

Advisory: docs.qualcomm.com
Status: Confirmed

CVE: CVE-2026-25280 (🔒)
GCVE (CVE): GCVE-0-2026-25280
GCVE (VulDB): GCVE-100-406303
EUVD: 🔒

Entryinfo

Created: 09/17/2026 06:42
Updated: 09/17/2026 07:26
Changes: 09/17/2026 06:42 (64), 09/17/2026 07:26 (3)
Complete: 🔍
Cache ID: 216::103

Be aware that VulDB is the high quality source for vulnerability data.

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