CVE-2024-12388VulnerabilityPublished 20 Mar 2025Updated 15 Oct 2025

CVE-2024-12388: binary-husky/gpt_academic · ReDoS

Affects binary-husky/gpt_academicSource CVE Database V5

Not known to be exploited · CVSS 6.5 Medium.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.0 base score

6.5Medium

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

EPSS: 0.7% chance of exploitation in 30 days – higher than 54% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Attack Vector: Network
Attack Complexity: Low
Privileges Required: Low
User Interaction: None
Scope: Unchanged
Confidentiality: None
Integrity: None
Availability: High

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

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, 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: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: Low: The attacker is authorized with (i.e., requires) privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges may have the ability to cause an impact only to non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: High: There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 20 Mar 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 2026-10-25.

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

AI-suggested

To mitigate CVE-2024-12388, organizations should first identify all instances of binary-husky/gpt_academic in their environment. Since no official patches are currently available, immediate steps include: 1) Reviewing and refactoring the vulnerable regular expressions to use more efficient patterns or alternative parsing methods that avoid catastrophic backtracking. 2) Implementing input validation to reject or sanitize inputs that could trigger the ReDoS condition before they reach the regex engine. 3) Applying rate limiting and connection throttling on network interfaces to reduce the impact of repeated malicious requests. 4) Monitoring application performance and logs for signs of abnormal CPU usage or request patterns indicative of ReDoS attempts. 5) Isolating the vulnerable service behind web application firewalls (WAFs) or reverse proxies that can detect and block suspicious payloads. 6) Engaging with the vendor or open-source maintainers for updates or patches and applying them promptly once available. 7) Considering temporary disabling or restricting access to the vulnerable functionality if feasible until a fix is deployed.

Description

A vulnerability in binary-husky/gpt_academic version 310122f allows for a Regular Expression Denial of Service (ReDoS) attack. The application uses a regular expression to parse user input, which can take polynomial time to match certain crafted inputs. This allows an attacker to send a small malicious payload to the server, causing it to become unresponsive and unable to handle any requests from other users.

Impact

For European organizations, the primary impact of CVE-2024-12388 is the potential for denial of service attacks against systems running binary-husky/gpt_academic. This could disrupt academic, research, or other institutional services relying on this software, leading to downtime and loss of productivity. Since the vulnerability affects availability only, confidentiality and integrity remain intact. However, service outages can indirectly affect operational continuity and user trust. Organizations with public-facing instances of the software are at higher risk, as attackers can exploit the vulnerability remotely without user interaction. The lack of known exploits reduces immediate risk, but the medium CVSS score and ease of exploitation suggest that attackers could develop exploits. Additionally, the vulnerability could be leveraged as part of a larger attack chain or to cause distraction during other malicious activities. European academic institutions and research centers using this software may face targeted attacks aiming to disrupt their operations.

CWE-1333Inefficient Regular Expression Complexity (opens in a new tab)
Base weaknessLikelihood of exploit: High
The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.
Architecture and Design
Use regular expressions that do not support backtracking, e.g. by removing nested quantifiers.
System Configuration
Set backtracking limits in the configuration of the regular expression implementation, such as PHP's pcre.backtrack_limit. Also consider limits on execution time for the process.
Implementation
Do not use regular expressions with untrusted input. If regular expressions must be used, avoid using backtracking in the expression.
OWASP Cheat Sheets
File Upload (opens in a new tab)
OWASP ASVS 4.0.3
V12.1.1 (opens in a new tab)
Attack patterns
Regular Expression Exponential Blowup (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

huntr.com/bounties/b1c01c94-e477-41db-9d17-601aa25e351c (opens in a new tab)

Community reviews

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Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 15 Oct 2025, 13:22 UTC

WeaknessesCWE-1333

Technical details

References

Community reviews

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