CVE-2024-12044
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 · uneditedA remote code execution vulnerability exists in open-mmlab/mmdetection version v3.3.0. The vulnerability is due to the use of the `pickle.loads()` function in the `all_reduce_dict()` distributed training API without proper sanitization. This allows an attacker to execute arbitrary code by broadcasting a malicious payload to the distributed training network.
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 · high confidenceA critical RCE vulnerability exists in open-mmlab/mmdetection v3.3.0 where the all_reduce_dict() distributed training API uses pickle.loads() without sanitization. Attackers can broadcast malicious pickle payloads across the distributed training network to achieve arbitrary code execution on all participating nodes.
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
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.0/AV:N/AC:L/PR:N/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 checksWork through these to decide whether this CVE applies to you.
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Check mmdetection versionRun 'pip show mmdet' or inspect the installed package metadata to confirm the exact version installed. Also check any requirements.txt or setup.py files for the version pinning.Affected if Version is exactly v3.3.0 (the specific affected version)
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Verify distributed training is enabledInspect training scripts and config files for distributed training flags such as --launcher='pytorch' or launcher='slurm', or check for init_method in PyTorch distributed initialization.Affected if Distributed training is enabled and multiple nodes/GPUs are configured to communicate
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Identify all_reduce_dict usageSearch codebase for calls to all_reduce_dict in training scripts, distributed utility files, or custom training loops. Use grep -r 'all_reduce_dict' in the project directory.Affected if Code calls all_reduce_dict from mmdetection/distributed/utils or similar modules
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Inspect serialization in inter-node communicationReview the all_reduce_dict implementation or its surrounding code to confirm pickle.loads() is being used for deserializing data received from other nodes.Affected if pickle.loads() is used without validation on data from distributed training peers
You are affected if running mmdetection v3.3.0 with distributed training enabled and the all_reduce_dict API uses pickle.loads on untrusted inter-node data.
Generated from the published advisory. Verify against your own configuration.
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 dataUntil an official patch is released, avoid using untrusted data sources in distributed training and implement input validation/signing on inter-node communication. Consider replacing pickle with a safer serialization format like JSON.
- Consultation3.0 h
- Implementation6.0 h
- Testing3.0 h
- Review / QA2.0 h
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Free · runs locallyCheck whether your project pulls in CVE-2024-12044 — 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 sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2024-12044 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Version or environment caveats, and links to real fixes
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