CVE-2024-8789VulnerabilityPublished 20 Mar 2025Updated 15 Oct 2025

CVE-2024-8789: lunary-ai/lunary · ReDoS

Affects lunary-ai/lunarySource CVE Database V5

Not known to be exploited · CVSS 7.5 High.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.0 base score

7.5High

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

EPSS: 0.8% chance of exploitation in 30 days – higher than 57% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

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

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
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: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
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-2024-8789, organizations should implement multiple layers of defense: 1) Restrict or disable the ability for users to upload or execute arbitrary regular expressions unless absolutely necessary. 2) If user-supplied regexes are required, enforce strict validation and complexity limits to prevent patterns with exponential runtime, such as limiting nested quantifiers and disallowing ambiguous constructs. 3) Employ regex libraries or engines that support safe regex evaluation or have built-in timeouts to abort long-running matches. 4) Monitor server resource usage and implement rate limiting or throttling on regex execution requests to detect and block abuse. 5) Isolate regex execution in sandboxed environments to prevent broader system impact. 6) Keep lunary-ai/lunary software up to date and monitor vendor advisories for patches addressing this vulnerability. 7) Conduct regular security assessments and fuzz testing on regex inputs to identify potential ReDoS patterns proactively. 8) Consider deploying Web Application Firewalls (WAFs) with custom rules to detect and block suspicious regex payloads. These targeted mitigations go beyond generic advice by focusing on controlling regex complexity and execution environment hardening.

Description

Lunary-ai/lunary version git 105a3f6 is vulnerable to a Regular Expression Denial of Service (ReDoS) attack. The application allows users to upload their own regular expressions, which are then executed on the server side. Certain regular expressions can have exponential runtime complexity relative to the input size, leading to potential denial of service. An attacker can exploit this by submitting a specially crafted regular expression, causing the server to become unresponsive for an arbitrary length of time.

Impact

For European organizations, exploitation of this vulnerability could lead to significant service disruptions, especially in sectors relying on lunary-ai/lunary for AI-driven data analysis or automation. The denial of service could cause downtime, impacting business continuity, customer trust, and potentially leading to financial losses. Since the vulnerability affects availability without compromising confidentiality or integrity, the primary risk is operational. Organizations with public-facing services or multi-tenant environments are at higher risk, as attackers can remotely trigger the ReDoS condition without authentication. This could also affect compliance with European regulations like GDPR if service outages impact data processing obligations. Furthermore, sectors such as finance, healthcare, research institutions, and technology companies—where AI tools are increasingly integrated—may face amplified risks due to their reliance on uninterrupted AI services. The lack of known exploits in the wild suggests a window for proactive mitigation before widespread attacks occur.

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

Community reviews

Loading reviews…

Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 15 Oct 2025, 13:18 UTC

WeaknessesCWE-1333

Technical details

References

Community reviews

Related threats