CVE-2024-0654VulnerabilityPublished 18 Jan 2024Updated 2 Jun 2025

CVE-2024-0654: DeepFaceLab · Deserialization

Affects DeepFaceLabSource CVE Database V5

Not known to be exploited · CVSS 5.3 Medium.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score

5.3Medium

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

EPSS: 0.2% chance of exploitation in 30 days – higher than 19% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

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

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

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: 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: 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: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.
Availability: Low: Performance is reduced or there are interruptions in resource availability. Even if repeated exploitation of the vulnerability is possible, the attacker does not have the ability to completely deny service to legitimate users. The resources in the impacted component are either partially available all of the time, or fully available only some of the time, but overall there is no direct, serious consequence to the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 18 Jan 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 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

1. Restrict local access to systems running DeepFaceLab to trusted users only, enforcing strict user privilege management and endpoint security controls. 2. Avoid running DeepFaceLab or loading pretrained models from untrusted or unknown sources to reduce the risk of maliciously crafted serialized data. 3. Implement application-level sandboxing or containerization to isolate DeepFaceLab processes and limit the impact of potential exploitation. 4. Monitor file integrity and system logs for unusual deserialization activities or unexpected process behaviors related to DeepFaceLab. 5. Encourage developers or users of DeepFaceLab to update to patched versions once available and to follow secure coding practices for deserialization, such as using safe serialization libraries or validating input data rigorously. 6. Educate users about the risks of loading external pretrained models and the importance of verifying their provenance. 7. Employ endpoint detection and response (EDR) solutions to detect anomalous local activities that could indicate exploitation attempts.

Description

A vulnerability, which was classified as problematic, was found in DeepFaceLab pretrained DF.wf.288res.384.92.72.22. Affected is an unknown function of the file mainscripts/Util.py. The manipulation leads to deserialization. Local access is required to approach this attack. The exploit has been disclosed to the public and may be used. VDB-251382 is the identifier assigned to this vulnerability.

Impact

For European organizations, the impact of CVE-2024-0654 depends largely on the extent to which DeepFaceLab is used internally or by contractors. Organizations involved in media production, digital forensics, academic research, or AI development may use DeepFaceLab or similar tools. An attacker exploiting this vulnerability could gain unauthorized code execution capabilities on affected systems, leading to data leakage, tampering with media content, or disruption of workflows. This could damage intellectual property, violate data protection regulations such as GDPR, and harm organizational reputation. Since the attack requires local access, the risk is higher in environments with weak endpoint security, shared workstations, or insufficient user privilege separation. The vulnerability also poses a risk in hybrid or remote work scenarios where endpoint devices may be less controlled. Although no active exploits are reported, the public disclosure increases the risk of opportunistic attacks, especially in environments where pretrained models are shared or downloaded from untrusted sources.

CWE-502Deserialization of Untrusted Data (opens in a new tab)
Base weaknessLikelihood of exploit: MediumCWE Top 25 (2025): #15OWASP Top 10 A08:2025: Software or Data Integrity Failures (opens in a new tab)
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
Architecture and Design · Implementation
If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
Implementation
When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
Implementation
Explicitly define a final object() to prevent deserialization.
OWASP Cheat Sheets
Abuse Case (opens in a new tab)
Deserialization (opens in a new tab)
XML Security (opens in a new tab)
XML External Entity Prevention (opens in a new tab)
Software Supply Chain Security (opens in a new tab)
OWASP ASVS 4.0.3
V1.5.2 (opens in a new tab)
V5.5.3 (opens in a new tab)
V5.5.1 (opens in a new tab)
Attack patterns
Object Injection (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 3 Jul 2025, 17:01 UTC

WeaknessesCWE-502

Technical details

References

Community reviews

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