CVE-2025-10236 Vulnerability Analysis & Exploit Details

CVE-2025-10236
Vulnerability Scoring

4.3
/10
Medium Risk

The vulnerability CVE-2025-10236 could compromise system integrity but typically requires user interaction to be exploited.

Attack Complexity Details

  • Attack Complexity: Low
    Exploits can be performed without significant complexity or 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-2025-10236 Details

Status: Analyzed

Last updated: 🕝 31 Oct 2025, 14:39 UTC
Originally published on: 🕑 11 Sep 2025, 02:15 UTC

Time between publication and last update: 50 days

CVSS Release: version 3

CVSS3 Source

cna@vuldb.com

CVSS3 Type

Secondary

CVSS3 Vector

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

CVE-2025-10236 Vulnerability Summary

CVE-2025-10236: A vulnerability has been found in binary-husky gpt_academic up to 3.91. Impacted is the function merge_tex_files_ of the file crazy_functions/latex_fns/latex_toolbox.py of the component LaTeX File Handler. Such manipulation of the argument \input{} leads to path traversal. The attack may be launched remotely. The exploit has been disclosed to the public and may be used. The vendor was contacted early about this disclosure but did not respond in any way.

Assessing the Risk of CVE-2025-10236

Access Complexity Graph

The exploitability of CVE-2025-10236 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-2025-10236

CVE-2025-10236 presents an accessible attack vector with minimal effort required. Restricting access controls and implementing security updates are critical to reducing exploitation 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-2025-10236, 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-2025-10236, showing how Confidentiality, Integrity, and Availability might be affected if the vulnerability is exploited. Higher values usually signal greater potential damage.

  • Confidentiality: Low
    CVE-2025-10236 could lead to minor leaks of non-critical information without major privacy breaches.
  • Integrity: None
    CVE-2025-10236 poses no threat to data integrity.
  • Availability: None
    CVE-2025-10236 does not impact system availability.

CVE-2025-10236 References

External References

CWE Common Weakness Enumeration

CWE-22

CAPEC Common Attack Pattern Enumeration and Classification

  • Path Traversal CAPEC-126 An adversary uses path manipulation methods to exploit insufficient input validation of a target to obtain access to data that should be not be retrievable by ordinary well-formed requests. A typical variety of this attack involves specifying a path to a desired file together with dot-dot-slash characters, resulting in the file access API or function traversing out of the intended directory structure and into the root file system. By replacing or modifying the expected path information the access function or API retrieves the file desired by the attacker. These attacks either involve the attacker providing a complete path to a targeted file or using control characters (e.g. path separators (/ or \) and/or dots (.)) to reach desired directories or files.
  • Using Slashes and URL Encoding Combined to Bypass Validation Logic CAPEC-64 This attack targets the encoding of the URL combined with the encoding of the slash characters. An attacker can take advantage of the multiple ways of encoding a URL and abuse the interpretation of the URL. A URL may contain special character that need special syntax handling in order to be interpreted. Special characters are represented using a percentage character followed by two digits representing the octet code of the original character (%HEX-CODE). For instance US-ASCII space character would be represented with %20. This is often referred as escaped ending or percent-encoding. Since the server decodes the URL from the requests, it may restrict the access to some URL paths by validating and filtering out the URL requests it received. An attacker will try to craft an URL with a sequence of special characters which once interpreted by the server will be equivalent to a forbidden URL. It can be difficult to protect against this attack since the URL can contain other format of encoding such as UTF-8 encoding, Unicode-encoding, etc.
  • Manipulating Web Input to File System Calls CAPEC-76 An attacker manipulates inputs to the target software which the target software passes to file system calls in the OS. The goal is to gain access to, and perhaps modify, areas of the file system that the target software did not intend to be accessible.
  • Using Escaped Slashes in Alternate Encoding CAPEC-78 This attack targets the use of the backslash in alternate encoding. An adversary can provide a backslash as a leading character and causes a parser to believe that the next character is special. This is called an escape. By using that trick, the adversary tries to exploit alternate ways to encode the same character which leads to filter problems and opens avenues to attack.
  • Using Slashes in Alternate Encoding CAPEC-79 This attack targets the encoding of the Slash characters. An adversary would try to exploit common filtering problems related to the use of the slashes characters to gain access to resources on the target host. Directory-driven systems, such as file systems and databases, typically use the slash character to indicate traversal between directories or other container components. For murky historical reasons, PCs (and, as a result, Microsoft OSs) choose to use a backslash, whereas the UNIX world typically makes use of the forward slash. The schizophrenic result is that many MS-based systems are required to understand both forms of the slash. This gives the adversary many opportunities to discover and abuse a number of common filtering problems. The goal of this pattern is to discover server software that only applies filters to one version, but not the other.

Vulnerable Configurations

  • cpe:2.3:a:binary-husky:gpt_academic:-:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:-:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.4:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.4:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.5:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.5:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.68-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.68-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.68-3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.68-3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.68-4:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.68-4:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.7:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.7:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.67:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.67:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:2.68:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:2.68:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.1:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.1:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.1-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.1-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.1-3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.1-3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.3-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.3-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.3-3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.3-3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.3-4:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.3-4:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.33-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.33-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.37-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.37-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.37-3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.37-3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.37-4:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.37-4:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.4:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.4:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.4-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.4-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.41-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.41-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.41-3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.41-3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.42-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.42-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.48-1:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.48-1:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.50-1:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.50-1:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.50-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.50-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.50-3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.50-3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.52-1:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.52-1:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.53-1:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.53-1:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.53-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.53-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.54-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.54-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.55-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.55-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.60-1:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.60-1:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.60-2:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.60-2:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.60-3:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.60-3:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.64-1:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.64-1:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.9:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.9:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.15:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.15:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.32:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.32:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.33:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.33:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.34:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.34:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.35:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.35:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.36:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.36:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.37:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.37:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.41:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.41:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.42:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.42:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.43:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.43:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.44:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.44:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.45:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.45:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.47:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.47:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.48:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.48:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.50:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.50:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.52:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.52:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.53:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.53:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.54:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.54:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.55:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.55:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.56:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.56:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.70:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.70:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.74:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.74:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.75:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.75:*:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.83:-:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.83:-:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.83:fix1:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.83:fix1:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.90:-:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.90:-:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.90:patch1:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.90:patch1:*:*:*:*:*:*
  • cpe:2.3:a:binary-husky:gpt_academic:3.91:*:*:*:*:*:*:*
    cpe:2.3:a:binary-husky:gpt_academic:3.91:*:*:*:*:*:*:*

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