{"answers":{"affected":"22 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.","exploited":"There is no known exploitation of CVE-2021-37652 in the wild and no public exploit code.","fix":"Upgrade tensorflow to a fixed version for your release line: 2.3.4, 2.4.3 or 2.5.1.","what":"CVE-2021-37652 is a high-severity use after free vulnerability in Google Tensorflow, published on 12 Aug 2021. 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-2021-37652 and fix it if it is affected.\n\nWhat it is: CVE-2021-37652 is a high-severity use after free vulnerability in Google Tensorflow, published on 12 Aug 2021. 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-2021-37652 in the wild and no public exploit code.\n\nAffected packages and fixed versions:\n- tensorflow (Bitnami): affected from 2.3.0; fixed in 2.3.4, 2.4.3, 2.5.1\n- tensorflow (PyPI): affected all versions; fixed in 2.3.4\n- tensorflow (PyPI): affected all versions; fixed in 2.3.4\n- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3\n- tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.3\n- tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.3\n- tensorflow (PyPI): affected from 2.5.0; fixed in 2.5.1\n- tensorflow (PyPI): affected from 2.5.0; fixed in 2.5.1\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.3.4\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.3.4\n- tensorflow-cpu (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3\n- tensorflow-cpu (PyPI): affected from 2.4.0; fixed in 2.4.3\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-2021-37652/ (Markdown: https://insights.sbomify.com/CVE-2021-37652/index.md)","id":"CVE-2021-37652","markdown":"https://insights.sbomify.com/CVE-2021-37652/index.md","name":"CVE-2021-37652","record":{"aliases":["BIT-tensorflow-2021-37652","GHSA-m7fm-4jfh-jrg6","PYSEC-2021-274","PYSEC-2021-565","PYSEC-2021-763"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["code_execution","denial_of_service"],"network_reachable":"adjacent_or_local","non_default_config":false,"product_category":"TensorFlow machine learning library","requires_auth":"low_privilege","summary":"An attacker can trigger a use-after-free error in TensorFlow's boosted trees creation, potentially leading to code execution or denial of service.","user_interaction":"not_required","vuln_class":"use_after_free"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"GitHub_M","cpe":[{"product":"tensorflow","vendor":"google"}],"cvss":{"score":7.8,"severity":"high","source":"cna","vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H","version":"3.1"},"cwes":[{"id":"CWE-415","name":"Double Free"},{"id":"CWE-416","name":"Use After Free"}],"description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.BoostedTreesCreateEnsemble` can result in a use after free error if an attacker supplies specially crafted arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/boosted_trees/resource_ops.cc#L55) uses a reference counted resource and decrements the refcount if the initialization fails, as it should. However, when the code was written, the resource was represented as a naked pointer but later refactoring has changed it to be a smart pointer. Thus, when the pointer leaves the scope, a subsequent `free`-ing of the resource occurs, but this fails to take into account that the refcount has already reached 0, thus the resource has been already freed. During this double-free process, members of the resource object are accessed for cleanup but they are invalid as the entire resource has been freed. We have patched the issue in GitHub commit 5ecec9c6fbdbc6be03295685190a45e7eee726ab. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","ecosystems":["Bitnami","PyPI"],"exploits":{"exploitdb":0,"first_seen":null,"github_poc":0,"max_poc_stars":null,"metasploit":0,"nuclei":0,"refs":[],"tier":"none_known"},"has_fix":true,"headline":"Use after free in boosted trees creation in TensorFlow","id":"CVE-2021-37652","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow"],"type":"use_after_free","year":"2021"},"n_packages":22,"n_references":2,"next":{"headline":"Division by 0 in `ResourceGather` in TensorFlow","id":"CVE-2021-37653"},"packages":[{"ecosystem":"Bitnami","fixed":["2.3.4","2.4.3","2.5.1"],"introduced":["2.3.0","2.4.0","2.5.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:bitnami/tensorflow","source":"BIT-tensorflow-2021-37652"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4","2.4.3"],"introduced":["2.3.0","2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"PYSEC-2021-274"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4","2.4.3"],"introduced":["2.3.0","2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"PYSEC-2021-565"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.3.4","2.4.3"],"introduced":["2.3.0","2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"PYSEC-2021-763"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m7fm-4jfh-jrg6"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m7fm-4jfh-jrg6"}],"prev":{"headline":"Heap buffer overflow in `FractionalAvgPoolGrad` in TensorFlow","id":"CVE-2021-37651"},"products":["tensorflow"],"published":"2021-08-12","related":[{"cvss_score":9.8,"headline":"TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation","id":"CVE-2023-25668","kev_date_added":null,"published":"2023-03-24"},{"cvss_score":9.8,"headline":"Integer Overflow or Wraparound in Google TensorFlow","id":"CVE-2018-7575","kev_date_added":null,"published":"2019-04-24"},{"cvss_score":9.3,"headline":"Arbitrary code execution due to YAML deserialization","id":"CVE-2021-37678","kev_date_added":null,"published":"2021-08-12"},{"cvss_score":9.1,"headline":"Path traversal in n/a","id":"CVE-2021-35958","kev_date_added":null,"published":"2021-06-30"},{"cvss_score":9,"headline":"Integer truncation in Shard API usage","id":"CVE-2020-15202","kev_date_added":null,"published":"2020-09-25"},{"cvss_score":9,"headline":"Data leak in Tensorflow","id":"CVE-2020-15205","kev_date_added":null,"published":"2020-09-25"},{"cvss_score":9,"headline":"Denial of Service in Tensorflow","id":"CVE-2020-15206","kev_date_added":null,"published":"2020-09-25"}],"sources":[{"class":"attribution","licence":"Apache-2.0","name":"Bitnami","prefix":"BIT"},{"class":"attribution","licence":"CVE Terms of Use (MITRE)","name":"CVE List","prefix":"CVE"},{"class":"attribution","licence":"CC BY 4.0","name":"GitHub Advisory Database","prefix":"GHSA"},{"class":"attribution","licence":"CC BY 4.0","name":"PyPA Advisory Database","prefix":"PYSEC"},{"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":null,"exploitation":null,"technical_impact":null},"state":"PUBLISHED","updated":"2024-08-04","vendors":["tensorflow"]},"summary":"An attacker can trigger a use-after-free error in TensorFlow's boosted trees creation, potentially leading to code execution or denial of service.","url":"https://insights.sbomify.com/CVE-2021-37652/"}