VulnerabilityPublished 26 Sep 2024Updated 27 Sep 2024

CVE-2024-45989: Monica AI Assistant desktop application · Command Injection

Source CVE Database V5

Not known to be exploited · CVSS 4.0 Medium.

Data as of 26 Oct 2026, 14:05 UTC

CVSS 3.1 base score

4.0Medium

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

EPSS: 0.3% chance of exploitation in 30 days – higher than 23% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

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

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

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

Attack Vector: Local: The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or remotely (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., tricking a legitimate user into opening a malicious document).
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: 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 impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 26 Sep 2024
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 or the CVSS exploit maturity 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-2024-45989, organizations should implement the following specific measures: 1) Restrict local access to systems running Monica AI Assistant to trusted users only, employing strict access controls and endpoint security solutions to prevent unauthorized local access. 2) Monitor and audit local user activities for suspicious behavior indicative of prompt injection attempts or unauthorized chatbot manipulation. 3) Disable or restrict the use of external content loading within chatbot responses if configurable, to prevent exfiltration via unloaded images or similar techniques. 4) Employ network monitoring to detect unusual outbound requests from the Monica AI Assistant process, especially to unknown or suspicious external servers. 5) Until a patch is available, consider isolating the application environment or using virtual machines to limit data exposure. 6) Educate users about the risks of local threats and the importance of securing their endpoints. 7) Engage with the vendor for updates and patches and apply them promptly once released.

Description

Monica AI Assistant desktop application v2.3.0 is vulnerable to Exposure of Sensitive Information to an Unauthorized Actor. A prompt injection allows an attacker to modify chatbot answer with an unloaded image that exfiltrates the user's sensitive chat data of the current session to a malicious third-party or attacker-controlled server.

Impact

The primary impact of CVE-2024-45989 is the unauthorized disclosure of sensitive information contained within the Monica AI Assistant chat sessions. Organizations using this application risk leakage of confidential communications, potentially exposing personal data, business secrets, or other sensitive content. Since the vulnerability requires local access, the threat is mainly from insider attackers or malware that has already compromised the endpoint. The lack of integrity or availability impact means the system's operation remains unaffected, but confidentiality breaches can lead to reputational damage, regulatory penalties, and loss of trust. This vulnerability could be exploited in environments where Monica AI Assistant is used for sensitive conversations, such as corporate, legal, or healthcare settings. The absence of known exploits reduces immediate risk, but the availability of technical details means attackers could develop exploits if local access is gained.

CWE-77Improper Neutralization of Special Elements used in a Command ('Command Injection') (opens in a new tab)
Class weaknessLikelihood of exploit: HighCWE Top 25 (2025): #23OWASP Top 10 A05:2025: Injection (opens in a new tab)
The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.
Architecture and Design
If at all possible, use library calls rather than external processes to recreate the desired functionality.
Implementation
If possible, ensure that all external commands called from the program are statically created.
Implementation · Input Validation
Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
OWASP Cheat Sheets
Abuse Case (opens in a new tab)
Deserialization (opens in a new tab)
Injection Prevention (opens in a new tab)
SQL Injection Prevention (opens in a new tab)
Injection Prevention in Java (opens in a new tab)
OWASP ASVS 4.0.3
V1.5.1 (opens in a new tab)
Attack patterns
LDAP Injection (opens in a new tab)
Command Delimiters (opens in a new tab)
IMAP/SMTP Command Injection (opens in a new tab)
Manipulating Writeable Terminal Devices (opens in a new tab)
Exploiting Multiple Input Interpretation Layers (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 28 Feb 2026, 07:12 UTC

WeaknessesCWE-77

Technical details

References

Community reviews

Related threats