{"answers":{"affected":"It affects 1 product.","exploited":"There is no known exploitation of CVE-2023-40724 in the wild and no public exploit code.","fix":"No fix has been published for CVE-2023-40724 yet. Limit exposure of the affected software until one is available.","what":"CVE-2023-40724 is a high-severity vulnerability in Siemens QMS Automotive, published on 12 Sep 2023. It can only be exploited from the same machine or local network, with no action from the victim."},"fix_prompt":"Check this codebase for CVE-2023-40724 and fix it if it is affected.\n\nWhat it is: CVE-2023-40724 is a high-severity vulnerability in Siemens QMS Automotive, published on 12 Sep 2023. It can only be exploited from the same machine or local network, with no action from the victim.\nExploitation: There is no known exploitation of CVE-2023-40724 in the wild and no public exploit code.\n\nAffected product: Siemens QMS Automotive. 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-2023-40724/ (Markdown: https://insights.sbomify.com/CVE-2023-40724/index.md)","id":"CVE-2023-40724","markdown":"https://insights.sbomify.com/CVE-2023-40724/index.md","name":"CVE-2023-40724","record":{"aliases":["GHSA-2g5w-f3gh-gfm8"],"analysis":{"component_type":"desktop_application","fix_type":"upgrade","impacts":["data_read","account_takeover"],"network_reachable":"adjacent_or_local","non_default_config":false,"product_category":"Siemens QMS Automotive","requires_auth":"low_privilege","summary":"Attackers can extract plaintext credentials from memory dumps to impersonate users in Siemens QMS Automotive.","user_interaction":"not_required","vuln_class":"information_disclosure"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"siemens","cpe":[{"product":"qms_automotive","vendor":"siemens"}],"cvss":{"score":7.3,"severity":"high","source":"cna","vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:L/E:P/RL:O/RC:C","version":"3.1"},"cwes":[{"id":"CWE-316","name":"Cleartext Storage of Sensitive Information in Memory"}],"description":"A vulnerability has been identified in QMS Automotive (All versions \u003c V12.39). User credentials are found in memory as plaintext. An attacker could perform a memory dump, and get access to credentials, and use it for impersonation.","ecosystems":[],"exploits":{"exploitdb":0,"first_seen":null,"github_poc":0,"max_poc_stars":null,"metasploit":0,"nuclei":0,"refs":[],"tier":"none_known"},"has_fix":null,"headline":"Information disclosure in QMS Automotive","id":"CVE-2023-40724","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":null,"product":null,"products":[],"type":"information_disclosure","year":"2023"},"n_packages":0,"n_references":1,"next":{"headline":"Information disclosure in QMS Automotive","id":"CVE-2023-40725"},"packages":[],"prev":{"headline":"Information disclosure in FortiSIEM","id":"CVE-2023-40723"},"products":["QMS Automotive"],"published":"2023-09-12","related":[{"cvss_score":8.8,"headline":"Information disclosure in QMS Automotive","id":"CVE-2023-40726","kev_date_added":null,"published":"2023-09-12"},{"cvss_score":7.8,"headline":"Security feature bypass in QMS Automotive","id":"CVE-2023-40727","kev_date_added":null,"published":"2023-09-12"},{"cvss_score":7.6,"headline":"Information disclosure in QMS Automotive","id":"CVE-2022-43958","kev_date_added":null,"published":"2022-11-08"},{"cvss_score":7.3,"headline":"Other in QMS Automotive","id":"CVE-2023-40728","kev_date_added":null,"published":"2023-09-12"},{"cvss_score":7.3,"headline":"Information disclosure in QMS Automotive","id":"CVE-2023-40729","kev_date_added":null,"published":"2023-09-12"},{"cvss_score":7.1,"headline":"Missing authorization in QMS Automotive","id":"CVE-2023-40730","kev_date_added":null,"published":"2023-09-12"}],"sources":[{"class":"attribution","licence":"CVE Terms of Use (MITRE)","name":"CVE List","prefix":"CVE"},{"class":"attribution","licence":"US public information, NVD API terms","name":"NVD"},{"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":"2025-02-27","vendors":["Siemens"]},"summary":"Attackers can extract plaintext credentials from memory dumps to impersonate users in Siemens QMS Automotive.","url":"https://insights.sbomify.com/CVE-2023-40724/"}