{"id":"PYSEC-2026-3946","summary":"Xinference vulnerable to remote code execution via unsafe `eval()` in Llama3 tool-call parsing","details":"### Summary\n\nXinference used Python's unsafe `eval()` function when parsing Llama3 tool-call output generated by a large language model. Because the model output can be influenced by attacker-controlled prompts sent to the chat completion API, a remote attacker can craft prompts that cause the model to return a Python expression. Xinference then evaluates that expression on the server while post-processing the tool-call result. In the tested default deployment, authentication was not enabled, so the vulnerability was exploitable by an unauthenticated remote attacker through the `/v1/chat/completions` endpoint.\n\n### Details\n\nUsers can interact with deployed models through Xinference's OpenAI-compatible `/v1/chat/completions` API. The request entry point is implemented in `xinference/api/restful_api.py`; non-streaming requests call the model instance's `chat()` method and return the inference result.\n\nWhen the Transformers backend is used, inference results flow through the batching logic in `xinference/model/llm/transformers/core.py`. Non-streaming chat results are handled by `handle_chat_result_non_streaming()`. If the request contains a `tools` field, Xinference calls `_post_process_completion()` to parse tool-call output from the model response.\n\nThe Llama3 tool-call parser is implemented in `xinference/model/llm/tool_parsers/llama3_tool_parser.py`. In affected versions, `extract_tool_calls()` parsed model output with `eval()`:\n\n```python\ndef extract_tool_calls(\n    self, model_output: str\n) -\u003e List[Tuple[Optional[str], Optional[str], Optional[Dict[str, Any]]]]:\n    try:\n        data = eval(model_output, {}, {})\n        return [(None, data[\"name\"], data[\"parameters\"])]\n    except Exception:\n        return [(model_output, None, None)]\n```\n\nThe intended behavior was to convert a Python dictionary-like string generated by the model into a dictionary object. However, `eval()` executes the input as a Python expression, and `eval(model_output, {}, {})` is not a security sandbox. If an attacker can influence the model output through prompt injection or direct chat input, the attacker can cause the model to return an expression such as:\n\n```python\n__import__('os').system('touch /tmp/hacked')\n```\n\nWhen the expression reaches `eval()`, it is executed in the Xinference server process context. The harmless `touch /tmp/hacked` command can be replaced with other payloads, such as a reverse shell, malware download, sensitive file read, or lateral-movement payload.\n\n### Score\n\nSeverity: Critical\n\nCVSS v3.1: 10.0\n\nVector: `CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H`\n\nRationale:\n\n- AV:N: the vulnerable API is remotely reachable over the network;\n- AC:L: exploitation only requires a crafted chat-completion request and tool-call parameter;\n- PR:N: the tested default configuration did not require authentication;\n- UI:N: no user interaction is required;\n- S:C: command execution can affect resources beyond the Xinference application boundary;\n- C:H/I:H/A:H: remote code execution can fully compromise confidentiality, integrity, and availability.\n\n### Credit\n\nThis vulnerability was discovered by:\n\n- XlabAI Team of Tencent Xuanwu Lab (xlabai@tencent.com)\n- Atuin Automated Vulnerability Discovery Engine\n- Guannan Wang (wgnbuaa@gmail.com), Zhanpeng Liu (pkugenuine@gmail.com), Guancheng Li (lgcpku@gmail.com)","aliases":["CVE-2026-61539","GHSA-x2rj-828p-hx9m"],"modified":"2026-09-10T12:15:15.622746554Z","published":"2026-09-10T09:44:52.936049Z","references":[{"type":"WEB","url":"https://github.com/xorbitsai/inference/security/advisories/GHSA-x2rj-828p-hx9m"},{"type":"WEB","url":"https://github.com/xorbitsai/inference/pull/4786"},{"type":"WEB","url":"https://github.com/xorbitsai/inference/commit/1b3d220f342ce68d34cec4586d9409d457dadc42"},{"type":"PACKAGE","url":"https://github.com/xorbitsai/inference"},{"type":"WEB","url":"https://github.com/xorbitsai/inference/releases/tag/v2.7.0"},{"type":"PACKAGE","url":"https://pypi.org/project/xinference"},{"type":"ADVISORY","url":"https://github.com/advisories/GHSA-x2rj-828p-hx9m"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-61539"}],"affected":[{"package":{"name":"xinference","ecosystem":"PyPI","purl":"pkg:pypi/xinference"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.0"}]}],"versions":["0.0.0","0.0.1","0.0.2","0.0.3","0.0.4","0.0.5","0.0.6","0.1.0","0.1.1","0.1.2","0.1.3","0.10.0","0.10.1","0.10.2","0.10.2.post1","0.10.3","0.11.0","0.11.1","0.11.2","0.11.2.post1","0.11.3","0.12.0","0.12.1","0.12.2","0.12.2.post1","0.12.3","0.13.0","0.13.1","0.13.2","0.13.3","0.13.4","0.14.0","0.14.0.post1","0.14.1","0.14.1.post1","0.14.2","0.14.3","0.14.4","0.14.4.post1","0.15.0","0.15.1","0.15.2","0.15.3","0.15.4","0.16.0","0.16.1","0.16.2","0.16.3","0.2.0","0.2.1","0.2.2","0.2.3","0.3.0","0.4.0","0.4.1","0.4.2","0.4.3","0.4.4","0.5.0","0.5.1","0.5.2","0.5.3","0.5.4","0.5.5","0.5.6","0.6.0","0.6.1","0.6.2","0.6.3","0.6.4","0.6.5","0.7.0","0.7.1","0.7.2","0.7.3","0.7.3.1","0.7.4","0.7.4.1","0.7.5","0.8.0","0.8.1","0.8.2","0.8.3","0.8.3.1","0.8.4","0.8.5","0.9.0","0.9.1","0.9.2","0.9.3","0.9.4","1.0.0","1.0.1","1.1.0","1.1.1","1.10.0","1.10.1","1.11.0","1.11.0.post1","1.12.0","1.13.0","1.14.0","1.15.0","1.16.0","1.17.0","1.17.1","1.2.0","1.2.1","1.2.2","1.3.0","1.3.0.post1","1.3.0.post2","1.3.1","1.3.1.post1","1.4.0","1.4.1","1.5.0","1.5.0.post1","1.5.0.post2","1.5.1","1.6.0","1.6.0.post1","1.6.1","1.7.0","1.7.0.post1","1.7.1","1.7.1.post1","1.8.0","1.8.1","1.8.1rc1","1.9.0","1.9.1","2.0.0","2.1.0","2.2.0","2.3.0","2.4.0","2.5.0"],"database_specific":{"source":"https://github.com/pypa/advisory-database/blob/main/vulns/xinference/PYSEC-2026-3946.yaml"}}],"schema_version":"1.9.0","severity":[{"type":"CVSS_V3","score":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H"}]}