What is the CVSS score of CVE-2023-25399?

CVE-2023-25399 has a CVSS 3.1 base score of 5.5 (Medium). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H. EPSS exploitation probability: 0.4%.

Is there a public PoC exploit available for CVE-2023-25399?

Yes, a public proof-of-concept exploit is available for CVE-2023-25399. Prioritise patching immediately. EPSS: 0.4%.

Is there a patch available for CVE-2023-25399?

Yes, a patch is available for CVE-2023-25399. Update the affected software to the latest version immediately.

Scipy CVE-2023-25399

MEDIUM

Memory Leak (CWE-401)

2023-07-05 cve@mitre.org

Information Disclosure Scipy

5.5

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

5.5 MEDIUM

AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

None

Integrity

None

Availability

High

Lifecycle Timeline

CVE Published

Jul 05, 2023 - 17:15 nvd

MEDIUM 5.5

Blast Radius

ecosystem impact

† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth

143 pypi packages depend on scipy (126 direct, 17 indirect)

Ecosystem-wide dependent count for version 1.10.0.

DescriptionNVD

A refcounting issue which leads to potential memory leak was discovered in scipy commit 8627df31ab in Py_FindObjects() function. Note: This is disputed as a bug and not a vulnerability. SciPy is not designed to be exposed to untrusted users or data directly.

AnalysisAI

A refcounting issue which leads to potential memory leak was discovered in scipy commit 8627df31ab in Py_FindObjects() function. Rated medium severity (CVSS 5.5), this vulnerability is low attack complexity. Public exploit code available.

Technical ContextAI

This vulnerability is classified as Memory Leak (CWE-401), which allows attackers to exhaust available memory leading to denial of service. A refcounting issue which leads to potential memory leak was discovered in scipy commit 8627df31ab in Py_FindObjects() function. Note: This is disputed as a bug and not a vulnerability. SciPy is not designed to be exposed to untrusted users or data directly. Affected products include: Scipy.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Ensure all allocated memory is properly freed. Use RAII patterns or garbage-collected languages.