Cyber Resilience

CVE-2024-12391

Binary-Husky Gpt Academic 2024-10-15

Public PoC
Published
20 March 2025
Modified
15 October 2025
CVSS Score v3 6.5
Click a component to see what it means
Raw vectorCVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0087 55th percentile
Risk Priority 52 floored blend · peak EPSS

Summary

CVE-2024-12391 is a medium-severity Inefficient Regular Expression Complexity (CWE-1333) vulnerability in Binary-Husky Gpt Academic. Its CVSS base score is 6.5 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked in the top 45% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-15 (Development Process, Standards, and Tools) — see the control section below for these in your framework.

EU & UK References

Vulnerability Data

A vulnerability in binary-husky/gpt_academic, as of commit 310122f, allows for a Regular Expression Denial of Service (ReDoS) attack. The function '解析项目源码(手动指定和筛选源码文件类型)' permits the execution of user-provided regular expressions. Certain regular expressions can cause the Python RE engine to take exponential…

more

time to execute, leading to a Denial of Service (DoS) condition. An attacker who controls both the regular expression and the search string can exploit this vulnerability to hang the server for an arbitrary amount of time.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1499 Endpoint Denial of Service Impact
Adversaries may perform Endpoint Denial of Service (DoS) attacks to degrade or block the availability of services to users.
T1499.003 Application Exhaustion Flood Impact
Adversaries may target resource intensive features of applications to cause a denial of service (DoS), denying availability to those applications.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2024-12388Same product: Binary-Husky Gpt Academic
CVE-2024-12387Same product: Binary-Husky Gpt Academic
CVE-2024-11033Same product: Binary-Husky Gpt Academic
CVE-2024-10714Same product: Binary-Husky Gpt Academic
CVE-2024-10948Same product: Binary-Husky Gpt Academic
CVE-2024-10819Same product: Binary-Husky Gpt Academic
CVE-2024-12392Same product: Binary-Husky Gpt Academic
CVE-2025-10236Same product: Binary-Husky Gpt Academic
CVE-2024-12389Same product: Binary-Husky Gpt Academic
CVE-2025-0183Same product: Binary-Husky Gpt Academic

Affected Assets

binary-husky
gpt academic
2024-10-15

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and evaluation can discover inefficient regex patterns via performance or static analysis.

Development standards and tools can require safe regex construction and forbid known exponential patterns.

Denial-of-service protections limit resource exhaustion caused by expensive regex evaluation.

Input validation can constrain data that would otherwise trigger worst-case regex complexity.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly prevent inefficient regex via reviews, static analysis, and safe libraries.

ID.RA-01 partial match
prevents

Vulnerability identification processes can discover ReDoS issues in existing code but do not stop their introduction.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

finds

Security testing can detect and reject regex patterns with exponential worst-case complexity.

prevents

Secure development lifecycle mandates review of algorithmic efficiency, directly addressing ReDoS-prone regex.

prevents

Application security requirements can specify input-validation rules that limit regex complexity.

prevents

Secure architecture principles encourage avoidance of computationally expensive constructs such as catastrophic backtracking.

prevents

Secure coding standards explicitly prohibit or limit the use of inefficient regular expressions.

References