{"answers":{"affected":"22 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.","exploited":"It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-21731 exists.","fix":"Upgrade tensorflow to a fixed version for your release line: 2.5.3, 2.6.3 or 2.7.1.","what":"CVE-2022-21731 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 3 Feb 2022. Any signed-in user can exploit it over the network, with no action from the victim."},"fix_prompt":"Check this codebase for CVE-2022-21731 and fix it if it is affected.\n\nWhat it is: CVE-2022-21731 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 3 Feb 2022. Any signed-in user can exploit it over the network, with no action from the victim.\nExploitation: It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-21731 exists.\n\nAffected packages and fixed versions:\n- tensorflow (Bitnami): affected all versions; fixed in 2.5.3, 2.6.3, 2.7.1\n- tensorflow (PyPI): affected all versions; fixed in 2.5.3, 2.6.3, 2.7.1\n- tensorflow (PyPI): affected all versions; fixed in 2.5.3\n- tensorflow (PyPI): affected all versions; fixed in 2.5.3\n- tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.3\n- tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.3\n- tensorflow (PyPI): affected from 2.7.0; fixed in 2.7.1\n- tensorflow (PyPI): affected from 2.7.0; fixed in 2.7.1\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3, 2.6.3\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3\n- tensorflow-cpu (PyPI): affected from 2.6.0; fixed in 2.6.3\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-2022-21731/ (Markdown: https://insights.sbomify.com/CVE-2022-21731/index.md)","id":"CVE-2022-21731","markdown":"https://insights.sbomify.com/CVE-2022-21731/index.md","name":"CVE-2022-21731","record":{"aliases":["BIT-tensorflow-2022-21731","GHSA-m4hf-j54p-p353","PYSEC-2022-110","PYSEC-2022-55","PYSEC-2026-3211"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["denial_of_service"],"network_reachable":"yes","non_default_config":false,"product_category":"TensorFlow ML library","requires_auth":"low_privilege","summary":"A type confusion in TensorFlow's ConcatV2 shape inference allows attackers to trigger a segmentation fault, causing a denial of service.","user_interaction":"not_required","vuln_class":"denial_of_service"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"GitHub_M","cpe":[{"product":"tensorflow","vendor":"google"}],"cvss":{"score":6.5,"severity":"medium","source":"cna","vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","version":"3.1"},"cwes":[{"id":"CWE-843","name":"Access of Resource Using Incompatible Type"}],"description":"Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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":"weaponised"},"has_fix":true,"headline":"Type confusion leading to segfault in Tensorflow","id":"CVE-2022-21731","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow"],"type":"denial_of_service","year":"2022"},"n_packages":22,"n_references":4,"next":{"headline":"Memory exhaustion in Tensorflow","id":"CVE-2022-21732"},"packages":[{"ecosystem":"Bitnami","fixed":["2.5.3","2.6.3","2.7.1"],"introduced":["0","2.6.0","2.7.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:bitnami/tensorflow","source":"BIT-tensorflow-2022-21731"},{"ecosystem":"PyPI","fixed":["2.5.3","2.6.3","2.7.1"],"introduced":["0","2.6.0","2.7.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"PYSEC-2026-3211"},{"ecosystem":"PyPI","fixed":["2.5.3"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.5.3"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.6.3"],"introduced":["2.6.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.6.3"],"introduced":["2.6.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.7.1"],"introduced":["2.7.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.7.1"],"introduced":["2.7.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.5.3","2.6.3"],"introduced":["0","2.6.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"PYSEC-2022-55"},{"ecosystem":"PyPI","fixed":["2.5.3"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.5.3"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.6.3"],"introduced":["2.6.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.6.3"],"introduced":["2.6.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.7.1"],"introduced":["2.7.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.7.1"],"introduced":["2.7.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.5.3","2.6.3"],"introduced":["0","2.6.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"PYSEC-2022-110"},{"ecosystem":"PyPI","fixed":["2.5.3"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.5.3"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.6.3"],"introduced":["2.6.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.6.3"],"introduced":["2.6.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.7.1"],"introduced":["2.7.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m4hf-j54p-p353"},{"ecosystem":"PyPI","fixed":["2.7.1"],"introduced":["2.7.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m4hf-j54p-p353"}],"prev":{"headline":"Out of bounds read in Tensorflow","id":"CVE-2022-21730"},"products":["n/a"],"published":"2022-02-03","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":"no","exploitation":"poc","technical_impact":"partial"},"state":"PUBLISHED","updated":"2025-05-05","vendors":["n/a"]},"summary":"A type confusion in TensorFlow's ConcatV2 shape inference allows attackers to trigger a segmentation fault, causing a denial of service.","url":"https://insights.sbomify.com/CVE-2022-21731/"}