VulnerabilityPublished 11 Sep 2025

CVE-2025-10236: binary-husky gpt_academic · Path Traversal

Affects binary-husky gpt_academicSource CVE Database V5

Not known to be exploited · CVSS 5.3 Medium.

Data as of 26 Oct 2026, 09:08 UTC

CVSS 4.0 base score

5.3Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.7% chance of exploitation in 30 days – higher than 55% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P

Base metrics

Attack Vector: Network
Attack Complexity: Low
Attack Requirements: None
Privileges Required: Low
User Interaction: None
Vulnerable system confidentiality: Low
Vulnerable system integrity: None
Vulnerable system availability: None
Subsequent system confidentiality: None
Subsequent system integrity: None
Subsequent system availability: None

Threat metrics

Exploit Maturity: POC

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.
Attack Requirements: None: The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
Privileges Required: Low: The attacker requires privileges that provide basic capabilities that are typically limited to settings and resources owned by a single low-privileged user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without interaction from any human user, other than the attacker.
Vulnerable system confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the Vulnerable System.
Vulnerable system integrity: None: There is no loss of integrity within the Vulnerable System.
Vulnerable system availability: None: There is no impact to availability within the Vulnerable System.
Subsequent system confidentiality: None: There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.
Subsequent system integrity: None: There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.
Subsequent system availability: None: There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.
Exploit Maturity: POC: Based on threat intelligence sources each of the following must apply: · Proof-of-concept is publicly available · No knowledge of reported attempts to exploit this vulnerability · No knowledge of publicly available solutions used to simplify attempts to exploit the vulnerability

Definitions: FIRST CVSS v4.0 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 11 Sep 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
binary-husky gpt_academic	Affected =3.0 =3.1 =3.2 =3.3 =3.4 =3.5 =3.6 =3.7 =3.8 =3.9 =3.10 =3.11 =3.12 =3.13 =3.14 =3.15 =3.16 =3.17 =3.18 =3.19 =3.20 =3.21 =3.22 =3.23 =3.24 =3.25 =3.26 =3.27 =3.28 =3.29 =3.30 =3.31 =3.32 =3.33 =3.34 =3.35 =3.36 =3.37 =3.38 =3.39 =3.40 =3.41 =3.42 =3.43 =3.44 =3.45 =3.46 =3.47 =3.48 =3.49 =3.50 =3.51 =3.52 =3.53 =3.54 =3.55 =3.56 =3.57 =3.58 =3.59 =3.60 =3.61 =3.62 =3.63 =3.64 =3.65 =3.66 =3.67 =3.68 =3.69 =3.70 =3.71 =3.72 =3.73 =3.74 =3.75 =3.76 =3.77 =3.78 =3.79 =3.80 =3.81 =3.82 =3.83 =3.84 =3.85 =3.86 =3.87 =3.88 =3.89 =3.90 =3.91	Fixed in–

AI-suggested

1. Immediate mitigation should include restricting network access to gpt_academic services, limiting exposure to trusted internal networks only. 2. Implement input validation and sanitization at the application or proxy level to block malicious \input{} arguments containing path traversal sequences (e.g., ../). 3. Use containerization or sandboxing to isolate the gpt_academic process, minimizing the impact of potential file access beyond intended directories. 4. Monitor file access logs and system logs for unusual activity indicative of path traversal exploitation attempts. 5. Where possible, replace or upgrade to versions of gpt_academic that have addressed this vulnerability once available. 6. As a temporary workaround, restrict file system permissions of the user running gpt_academic to limit accessible files to only those necessary for operation. 7. Educate users and administrators about the risk of processing untrusted LaTeX inputs and encourage cautious handling of external documents. 8. Employ Web Application Firewalls (WAFs) or Intrusion Detection Systems (IDS) with custom rules to detect and block exploitation attempts targeting \input{} parameters.

Description

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.

Impact

For European organizations, this vulnerability poses a risk primarily to academic, research, and educational institutions that utilize the gpt_academic software for LaTeX document processing. Successful exploitation could allow attackers to read sensitive files on the host system, potentially exposing confidential research data, intellectual property, or personal information. Although the vulnerability does not directly impact system integrity or availability, unauthorized file disclosure can lead to further targeted attacks or data breaches. Given the remote exploitability and lack of required authentication, attackers could leverage this vulnerability to gain footholds in networks or escalate privileges by harvesting sensitive configuration or credential files. The impact is heightened in environments where gpt_academic is integrated into automated workflows or exposed to untrusted inputs, such as public-facing document submission portals. The absence of vendor response and patches increases the window of exposure, necessitating proactive mitigation by affected organizations.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 11 Sep 2025, 02:00 UTC

Technical details

References

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