CVE-2026-53805
NVIDIA Spatial Intelligence Lab's (SIL) GEN3C contains an unauthenticated remote code execution vulnerability in the inference API server wh
CVSS
9.8
Crítico
EPSS
0.7%
p48
KEV
—
Exploit Today
15
0-100
Publicado: 17 jun 2026 · Última mod.: 14 jul 2026 · CWE-502
0.7%EPSS · 30 días0.7%
2026-06-302026-07-17
NVIDIA Spatial Intelligence Lab's (SIL) GEN3C contains an unauthenticated remote code execution vulnerability in the inference API server where the /request-inference and /seed-model endpoints deserialize raw HTTP request bodies using Python's pickle.loads() without authentication or input validation. Attackers can supply a crafted payload containing a __reduce__ gadget to the inference API port to achieve remote code execution as the inference process.
- github.comhttps://github.com/nv-tlabs/GEN3C/commit/db2ffe12ced12ddafcec5e0422ee46ce8520746b
- github.comhttps://github.com/nv-tlabs/GEN3C/pull/62
- github.comhttps://github.com/nv-tlabs/GEN3C/pull/63
- www.vulncheck.comhttps://www.vulncheck.com/advisories/nvidia-sil-gen3c-unauthenticated-rce-via-pickle-deserialization-in-inference-api
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——29An undocumented and unsafe feature in the PLY (Python Lex-Yacc) library 3.11 allows Remote Code Execution (RCE) via the `picklefile` parameter in the `yacc()` function. This parameter accepts a `.pkl` file that is deserialized with `pickle.load()` without validation. Because `pickle` allows execution of embedded code via `__reduce__()`, an attacker can achieve code execution by passing a malicious pickle file. The parameter is not mentioned in official documentation or the GitHub repository, yet it is active in the PyPI version. This introduces a stealthy backdoor and persistence risk. NOTE: A third-party states that this vulnerability should be rejected because the proof of concept does not demonstrate arbitrary code execution and fails to complete successfully.3d