{"answers":{"affected":"","exploited":"There is no known exploitation of CVE-2025-13708 in the wild and no public exploit code.","fix":"No fix has been published for CVE-2025-13708 yet. Limit exposure of the affected software until one is available.","what":"CVE-2025-13708 is a high-severity unsafe deserialization vulnerability in Tencent NeuralNLP-NeuralClassifier, published on 23 Dec 2025. It can only be exploited from the same machine or local network, and only if a user opens a file or follows a link."},"fix_prompt":"Check this codebase for CVE-2025-13708 and fix it if it is affected.\n\nWhat it is: CVE-2025-13708 is a high-severity unsafe deserialization vulnerability in Tencent NeuralNLP-NeuralClassifier, published on 23 Dec 2025. It can only be exploited from the same machine or local network, and only if a user opens a file or follows a link.\nExploitation: There is no known exploitation of CVE-2025-13708 in the wild and no public exploit code.\n\nAffected product: Tencent NeuralNLP-NeuralClassifier. No package-level version data is available, so check the vendor advisory linked from the reference page.\n\nTask:\n1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies.\n2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it.\n3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead.\n4. Run the tests and summarise what changed and why.\n5. If nothing in the project is affected, say so and change nothing.\n\nReference: https://insights.sbomify.com/CVE-2025-13708/ (Markdown: https://insights.sbomify.com/CVE-2025-13708/index.md)","id":"CVE-2025-13708","markdown":"https://insights.sbomify.com/CVE-2025-13708/index.md","name":"CVE-2025-13708","record":{"aliases":["GHSA-728p-cgm9-jmpv"],"analysis":{"component_type":"library","fix_type":"patch","impacts":["code_execution","privilege_escalation"],"network_reachable":"adjacent_or_local","non_default_config":false,"product_category":"Tencent NeuralNLP library","requires_auth":"none","summary":"Remote attackers can execute arbitrary code with root privileges by tricking users into opening malicious files processed by the Tencent NeuralNLP-NeuralClassifier library.","user_interaction":"required","vuln_class":"deserialization"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"zdi","cpe":[],"cvss":{"score":7.8,"severity":"high","source":"cna","vector":"CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H","version":"3.0"},"cwes":[{"id":"CWE-502","name":"Deserialization of Untrusted Data"}],"description":"Tencent NeuralNLP-NeuralClassifier _load_checkpoint Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent NeuralNLP-NeuralClassifier. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the _load_checkpoint function. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of root. Was ZDI-CAN-27184.","ecosystems":[],"exploits":{"exploitdb":0,"first_seen":null,"github_poc":0,"max_poc_stars":null,"metasploit":0,"nuclei":0,"refs":[],"tier":"none_known"},"has_fix":false,"headline":"Deserialization in NeuralNLP-NeuralClassifier","id":"CVE-2025-13708","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":null,"product":null,"products":[],"type":"deserialization","year":"2025"},"n_packages":0,"n_references":2,"next":{"headline":"Tencent TFace restore_checkpoint Deserialization of Untrusted Data Remote Code Execution Vulnerability","id":"CVE-2025-13709"},"packages":[],"prev":{"headline":"Tencent HunyuanDiT model_resume Deserialization of Untrusted Data Remote Code Execution Vulnerability","id":"CVE-2025-13707"},"products":["NeuralNLP-NeuralClassifier"],"published":"2025-12-23","related":[],"sources":[{"class":"attribution","licence":"CVE Terms of Use (MITRE)","name":"CVE List","prefix":"CVE"},{"class":"attribution","licence":"CWE Terms of Use","name":"CWE (MITRE)"},{"class":"attribution","licence":"FIRST CVSS licence","name":"CVSS (FIRST)"}],"ssvc":{"automatable":"no","exploitation":"none","technical_impact":"total"},"state":"PUBLISHED","updated":"2025-12-30","vendors":["Tencent"]},"summary":"Remote attackers can execute arbitrary code with root privileges by tricking users into opening malicious files processed by the Tencent NeuralNLP-NeuralClassifier library.","url":"https://insights.sbomify.com/CVE-2025-13708/"}