pytest up to 9.0.2 on UNIX /tmp/pytest-of-{user} temp file

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 (≈)
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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.
6.0$0-$5k0.00

Summaryinfo

A vulnerability classified as problematic has been found in pytest up to 9.0.2 on UNIX. Affected by this issue is some unknown functionality of the file /tmp/pytest-of-{user}. The manipulation leads to temp file. This vulnerability is traded as CVE-2025-71176. An attack has to be approached locally. There is no exploit available.

Detailsinfo

A vulnerability, which was classified as problematic, has been found in pytest up to 9.0.2 on UNIX. This issue affects some unknown processing of the file /tmp/pytest-of-{user}. The manipulation with an unknown input leads to a temp file vulnerability. Using CWE to declare the problem leads to CWE-379. The product creates a temporary file in a directory whose permissions allow unintended actors to determine the file's existence or otherwise access that file. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

pytest through 9.0.2 on UNIX relies on directories with the /tmp/pytest-of-{user} name pattern, which allows local users to cause a denial of service or possibly gain privileges.

It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2025-71176 since 01/22/2026. The exploitation is known to be easy. Attacking locally is a requirement. Technical details of the vulnerability are known, but there is no available exploit.

The vulnerability scanner Nessus provides a plugin with the ID 297678 (Linux Distros Unpatched Vulnerability : CVE-2025-71176), which helps to determine the existence of the flaw in a target environment.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

The vulnerability is also documented in the vulnerability database at Tenable (297678). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.0
VulDB Meta Temp Score: 6.0

VulDB Base Score: 5.3
VulDB Temp Score: 5.3
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 6.8
CNA Vector (MITRE): 🔒

CVSSv2info

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

Exploitinginfo

Class: Temp file
CWE: CWE-379 / CWE-377
CAPEC: 🔒
ATT&CK: 🔒

Physical: Partially
Local: Yes
Remote: No

Availability: 🔒
Status: Not defined

EPSS Score: 🔒
EPSS Percentile: 🔒

Price Prediction: 🔍
Current Price Estimation: 🔒

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Nessus ID: 297678
Nessus Name: Linux Distros Unpatched Vulnerability : CVE-2025-71176

Threat Intelligenceinfo

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

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

01/22/2026 Advisory disclosed
01/22/2026 +0 days CVE reserved
01/22/2026 +0 days VulDB entry created
02/04/2026 +13 days VulDB entry last update

Sourcesinfo

Advisory: 13669
Status: Confirmed

CVE: CVE-2025-71176 (🔒)
GCVE (CVE): GCVE-0-2025-71176
GCVE (VulDB): GCVE-100-342299

Entryinfo

Created: 01/22/2026 08:14
Updated: 02/04/2026 02:38
Changes: 01/22/2026 08:14 (62), 02/04/2026 02:38 (2)
Complete: 🔍
Cache ID: 216::103

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

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