Microsoft Windows up to Server 2025 integer underflow

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.
9.6$25k-$100k1.05-

Summaryinfo

A vulnerability has been found in Microsoft Windows and classified as very critical. The affected element is an unknown function. The manipulation leads to integer underflow. This vulnerability is documented as CVE-2026-83869. The attack can be initiated remotely. There is not any exploit available. To fix this issue, it is recommended to deploy a patch.

Detailsinfo

A vulnerability, which was classified as very critical, has been found in Microsoft Windows. This issue affects an unknown part. The manipulation with an unknown input leads to a integer underflow vulnerability. Using CWE to declare the problem leads to CWE-191. The product subtracts one value from another, such that the result is less than the minimum allowable integer value, which produces a value that is not equal to the correct result. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

Integer underflow (wrap or wraparound) in DNS Server allows an unauthorized attacker to execute code over a network.

It is possible to read the advisory at msrc.microsoft.com. The identification of this vulnerability is CVE-2026-83869 since 09/01/2026. The exploitation is known to be easy. The attack may be initiated remotely. No form of authentication is needed for a successful exploitation. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $25k-$100k at the moment (estimation calculated on 10/14/2026).

Applying a patch is able to eliminate this problem.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Type

Vendor

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 9.9
VulDB Meta Temp Score: 9.6

VulDB Base Score: 10.0
VulDB Temp Score: 9.5
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 9.8
CNA Vector (microsoft): 🔒

CVSSv2info

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

Exploitinginfo

Class: Integer underflow
CWE: CWE-191 / CWE-189
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

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

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Threat Intelligenceinfo

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

Countermeasuresinfo

Recommended: Patch
Status: 🔍

0-Day Time: 🔒

Timelineinfo

09/01/2026 CVE reserved
10/14/2026 +43 days Advisory disclosed
10/14/2026 +0 days VulDB entry created
10/14/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: microsoft.com
Product: microsoft.com

Advisory: msrc.microsoft.com
Status: Confirmed

CVE: CVE-2026-83869 (🔒)
GCVE (CVE): GCVE-0-2026-83869
GCVE (VulDB): GCVE-100-419051
scip Labs: https://www.scip.ch/en/?labs.20161215

Entryinfo

Created: 10/14/2026 07:01
Changes: 10/14/2026 07:01 (62)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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