Code InjectionWeakness · CWE-94

CVE-2024-55241

HIGH · 8.8 CVSS v3.1 Published 2025-02-06
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
94/100
Remediation priority · Urgent
Remotely reachable Zero-click

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
An issue in deep-diver LLM-As-Chatbot before commit 99c2c03 allows a remote attacker to execute arbitrary code via the modelsbyom.py component.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · moderate confidence

A remote code execution vulnerability exists in the modelsbyom.py component of the deep-diver LLM-As-Chatbot application. Attackers can execute arbitrary code by supplying malicious input to this component, which handles model operations (likely Bring Your Own Model functionality). The vulnerability is exploitable without authentication given its remote attack vector.

MitigationUpdate to the version after commit 99c2c03 which contains the security fix. Until then, restrict network access to the chatbot service and implement input validation on all model-related endpoints.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

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

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Confirm deep-diver LLM-As-Chatbot installation
    Locate the application by searching for the modelsbyom.py file or checking for the 'deep-diver' or 'LLM-As-Chatbot' directory in your environment
    Affected if The application directory and modelsbyom.py file are present on the system
  2. Identify the installed version or commit
    If using git, run 'git log' or 'git rev-parse HEAD' in the application repository to determine the current commit hash
    Affected if The commit hash is earlier than 99c2c03 or cannot be determined (meaning it predates the fix)
  3. Check if the vulnerable component is loaded
    Examine your application startup logs or configuration to see if modelsbyom.py is imported or initialized as part of the chatbot functionality
    Affected if modelsbyom.py is loaded and active in the running application
  4. Determine network exposure of the chatbot interface
    Review your firewall rules, reverse proxy configuration, or network ACLs to check if the chatbot HTTP endpoint is accessible from untrusted networks
    Affected if The chatbot interface is exposed to the internet or untrusted internal networks without authentication barriers
  5. Inspect runtime configuration for BYOM settings
    Check application configuration files or environment variables for 'bring-your-own-model' (BYOM) settings that enable the modelsbyom.py functionality
    Affected if BYOM features are enabled and the configuration allows arbitrary model loading
  6. Review access logs for suspicious input patterns
    Examine HTTP access logs for the chatbot endpoint for unusual parameters or payloads that might indicate exploitation attempts, such as serialized objects or code-like strings
    Affected if Unexpected payloads matching deserialization or code injection patterns are present in recent logs

A user is affected if deep-diver LLM-As-Chatbot with modelsbyom.py is running and the installed version predates commit 99c2c03 or the chatbot interface is exposed to untrusted networks.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Update to the version after commit 99c2c03 which contains the security fix. Until then, restrict network access to the chatbot service and implement input validation on all model-related endpoints.

Have this fixed Scoped from the published advisory
  • Consultation3.0 h
  • Implementation6.0 h
  • Testing5.0 h
  • Review / QA3.0 h
17.0 hours of engineering $2,970
Get help mitigating

An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $4,752.

Scan for this in your stack

Free · runs locally
dbcve dependency scanner

Check whether your project pulls in CVE-2024-55241 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.

References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2024-55241 in production — separate from our analysis above.

No notes yet

Be the first to add a field note for this CVE — a mitigation you’ve verified, a version caveat, or a link to a working fix. Sign in above to contribute.

What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
  • No spam, self-promotion, credentials, or personal data