CVE-2025-32789 Vulnerability Analysis & Exploit Details

CVE-2025-32789
Vulnerability Scoring

3.1
/10
Moderate Risk

Exploiting CVE-2025-32789 requires specific conditions, leading to a moderate security impact.

Attack Complexity Details

  • Attack Complexity: High
    Exploits require significant effort and special conditions.
  • Attack Vector: Network
    Vulnerability is exploitable over a network without physical access.
  • Privileges Required: Low
    Some privileges are necessary to exploit the vulnerability.
  • Scope: Unchanged
    Exploit remains within the originally vulnerable component.
  • User Interaction: None
    No user interaction is necessary for exploitation.

CVE-2025-32789 Details

Status: Awaiting Analysis

Last updated: 🕗 17 Apr 2025, 20:21 UTC
Originally published on: 🕙 16 Apr 2025, 22:15 UTC

CVSS Release: version 3

CVSS3 Source

security-advisories@github.com

CVSS3 Type

Secondary

CVSS3 Vector

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

CVE-2025-32789 Vulnerability Summary

CVE-2025-32789: EspoCRM is an Open Source Customer Relationship Management software. Prior to version 9.0.7, users can be sorted by their password hash. This flaw allows an attacker to make assumptions about the hash values of other users stored in the password column of the user table, based on the results of the sorted list of users. Although unlikely, if an attacker knows the hash value of their password, they can change the password and repeat the sorting until the other user's password hash is fully revealed. This issue is patched in version 9.0.7.

Assessing the Risk of CVE-2025-32789

Access Complexity Graph

The exploitability of CVE-2025-32789 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-2025-32789

This vulnerability, CVE-2025-32789, 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-2025-32789, 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-2025-32789, showing how Confidentiality, Integrity, and Availability might be affected if the vulnerability is exploited. Higher values usually signal greater potential damage.

  • Confidentiality: Low
    CVE-2025-32789 could lead to minor leaks of non-critical information without major privacy breaches.
  • Integrity: None
    CVE-2025-32789 poses no threat to data integrity.
  • Availability: None
    CVE-2025-32789 does not impact system availability.

CVE-2025-32789 References

External References

CWE Common Weakness Enumeration

CWE-203

CAPEC Common Attack Pattern Enumeration and Classification

  • Black Box Reverse Engineering CAPEC-189 An adversary discovers the structure, function, and composition of a type of computer software through black box analysis techniques. 'Black Box' methods involve interacting with the software indirectly, in the absence of direct access to the executable object. Such analysis typically involves interacting with the software at the boundaries of where the software interfaces with a larger execution environment, such as input-output vectors, libraries, or APIs. Black Box Reverse Engineering also refers to gathering physical side effects of a hardware device, such as electromagnetic radiation or sounds.

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