CVE-2025-0941 Vulnerability Analysis & Exploit Details

CVE-2025-0941
Vulnerability Scoring

5.8
/10
Significant Risk

Security assessments indicate that CVE-2025-0941 presents a notable risk, potentially requiring prompt mitigation.

Attack Complexity Details

  • Attack Complexity: High
    Exploits require significant effort and special conditions.
  • Attack Vector: Adjacent_network
    Attack Vector Under Analysis
  • Privileges Required: Low
    Some privileges are necessary to exploit the vulnerability.
  • Scope: Changed
    Successful exploitation can impact components beyond the vulnerable component.
  • User Interaction: None
    No user interaction is necessary for exploitation.

CVE-2025-0941 Details

Status: Received on 26 Feb 2025, 17:15 UTC

Published on: 26 Feb 2025, 17:15 UTC

CVSS Release: version 3

CVSS3 Source

4ad3d9a7-bd20-4af3-8862-46d6b5a570db

CVSS3 Type

Secondary

CVSS3 Vector

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

CVE-2025-0941 Vulnerability Summary

CVE-2025-0941: MET ONE 3400+ instruments running software v1.0.41 can, under rare conditions, temporarily store credentials in plain text within the system. This data is not available to unauthenticated users.

Assessing the Risk of CVE-2025-0941

Access Complexity Graph

The exploitability of CVE-2025-0941 depends on two key factors: attack complexity (the level of effort required to execute an exploit) and privileges required (the access level an attacker needs).

Exploitability Analysis for CVE-2025-0941

This vulnerability, CVE-2025-0941, requires a high level of attack complexity and low privileges, making it difficult but not impossible to exploit. Organizations should ensure robust security configurations to mitigate risks.

Understanding AC and PR

A lower complexity and fewer privilege requirements make exploitation easier. Security teams should evaluate these aspects to determine the urgency of mitigation strategies, such as patch management and access control policies.

Attack Complexity (AC) measures the difficulty in executing an exploit. A high AC means that specific conditions must be met, making an attack more challenging, while a low AC means the vulnerability can be exploited with minimal effort.

Privileges Required (PR) determine the level of system access necessary for an attack. Vulnerabilities requiring no privileges are more accessible to attackers, whereas high privilege requirements limit exploitation to authorized users with elevated access.

CVSS Score Breakdown Chart

Above is the CVSS Sub-score Breakdown for CVE-2025-0941, illustrating how Base, Impact, and Exploitability factors combine to form the overall severity rating. A higher sub-score typically indicates a more severe or easier-to-exploit vulnerability.

CIA Impact Analysis

Below is the Impact Analysis for CVE-2025-0941, showing how Confidentiality, Integrity, and Availability might be affected if the vulnerability is exploited. Higher values usually signal greater potential damage.

  • Confidentiality: High
    Exploiting CVE-2025-0941 can result in unauthorized access to sensitive data, severely compromising data privacy.
  • Integrity: None
    CVE-2025-0941 poses no threat to data integrity.
  • Availability: None
    CVE-2025-0941 does not impact system availability.

Exploit Prediction Scoring System (EPSS)

The EPSS score estimates the probability that this vulnerability will be exploited in the near future.

EPSS Score: 0.043% (probability of exploit)

EPSS Percentile: 12.0% (lower percentile = lower relative risk)
This vulnerability is less risky than approximately 88.0% of others.

CVE-2025-0941 References

External References

CWE Common Weakness Enumeration

CWE-209

CAPEC Common Attack Pattern Enumeration and Classification

  • Fuzzing for application mapping CAPEC-215 An attacker sends random, malformed, or otherwise unexpected messages to a target application and observes the application's log or error messages returned. The attacker does not initially know how a target will respond to individual messages but by attempting a large number of message variants they may find a variant that trigger's desired behavior. In this attack, the purpose of the fuzzing is to observe the application's log and error messages, although fuzzing a target can also sometimes cause the target to enter an unstable state, causing a crash.
  • Padding Oracle Crypto Attack CAPEC-463 An adversary is able to efficiently decrypt data without knowing the decryption key if a target system leaks data on whether or not a padding error happened while decrypting the ciphertext. A target system that leaks this type of information becomes the padding oracle and an adversary is able to make use of that oracle to efficiently decrypt data without knowing the decryption key by issuing on average 128*b calls to the padding oracle (where b is the number of bytes in the ciphertext block). In addition to performing decryption, an adversary is also able to produce valid ciphertexts (i.e., perform encryption) by using the padding oracle, all without knowing the encryption key.
  • Query System for Information CAPEC-54 An adversary, aware of an application's location (and possibly authorized to use the application), probes an application's structure and evaluates its robustness by submitting requests and examining responses. Often, this is accomplished by sending variants of expected queries in the hope that these modified queries might return information beyond what the expected set of queries would provide.
  • Blind SQL Injection CAPEC-7 Blind SQL Injection results from an insufficient mitigation for SQL Injection. Although suppressing database error messages are considered best practice, the suppression alone is not sufficient to prevent SQL Injection. Blind SQL Injection is a form of SQL Injection that overcomes the lack of error messages. Without the error messages that facilitate SQL Injection, the adversary constructs input strings that probe the target through simple Boolean SQL expressions. The adversary can determine if the syntax and structure of the injection was successful based on whether the query was executed or not. Applied iteratively, the adversary determines how and where the target is vulnerable to SQL Injection.

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