6.9
MEDIUM CVSS 3.1
CVE-2025-63675
Cryptidy Deserialization Vulnerability (Code Execution)
Description

cryptidy through 1.2.4 allows code execution via untrusted data because pickle.loads is used. This occurs in aes_decrypt_message in symmetric_encryption.py.

INFO

Published Date :

Oct. 31, 2025, 7:15 a.m.

Last Modified :

Oct. 31, 2025, 5:15 p.m.

Remotely Exploit :

No
Affected Products

The following products are affected by CVE-2025-63675 vulnerability. Even if cvefeed.io is aware of the exact versions of the products that are affected, the information is not represented in the table below.

No affected product recoded yet

CVSS Scores
The Common Vulnerability Scoring System is a standardized framework for assessing the severity of vulnerabilities in software and systems. We collect and displays CVSS scores from various sources for each CVE.
Score Version Severity Vector Exploitability Score Impact Score Source
CVSS 3.1 MEDIUM [email protected]
Solution
Avoid using pickle.loads with untrusted data to prevent code execution vulnerabilities.
  • Avoid deserializing untrusted data with pickle.loads.
  • Update cryptidy to a version that does not use pickle.loads.
  • Use safe serialization formats like JSON instead.
  • Validate all input data before processing.
References to Advisories, Solutions, and Tools

Here, you will find a curated list of external links that provide in-depth information, practical solutions, and valuable tools related to CVE-2025-63675.

URL Resource
https://github.com/javiermorales36/cryptidy-analysis
https://github.com/netinvent/cryptidy/blob/cebc9ffd54cc20679d15a1a43ca9a5da645b0c58/cryptidy/symmetric_encryption.py#L220-L238
https://github.com/javiermorales36/cryptidy-analysis
CWE - Common Weakness Enumeration

While CVE identifies specific instances of vulnerabilities, CWE categorizes the common flaws or weaknesses that can lead to vulnerabilities. CVE-2025-63675 is associated with the following CWEs:

Common Attack Pattern Enumeration and Classification (CAPEC)

Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit the CVE-2025-63675 weaknesses.

We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).

Results are limited to the first 15 repositories due to potential performance issues.

The following list is the news that have been mention CVE-2025-63675 vulnerability anywhere in the article.

The following table lists the changes that have been made to the CVE-2025-63675 vulnerability over time.

Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.

  • CVE Modified by 134c704f-9b21-4f2e-91b3-4a467353bcc0

    Oct. 31, 2025

    Action Type Old Value New Value
    Added Reference https://github.com/javiermorales36/cryptidy-analysis
  • New CVE Received by [email protected]

    Oct. 31, 2025

    Action Type Old Value New Value
    Added Description cryptidy through 1.2.4 allows code execution via untrusted data because pickle.loads is used. This occurs in aes_decrypt_message in symmetric_encryption.py.
    Added CVSS V3.1 AV:L/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:L
    Added CWE CWE-502
    Added Reference https://github.com/javiermorales36/cryptidy-analysis
    Added Reference https://github.com/netinvent/cryptidy/blob/cebc9ffd54cc20679d15a1a43ca9a5da645b0c58/cryptidy/symmetric_encryption.py#L220-L238
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days. Following chart shows the EPSS score history of the vulnerability.
Vulnerability Scoring Details
Base CVSS Score: 6.9
Attack Vector
Attack Complexity
Privileges Required
User Interaction
Scope
Confidentiality Impact
Integrity Impact
Availability Impact