{"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-2021-37677 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-2021-37677 is a medium-severity denial of service 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-2021-37677 and fix it if it is affected.\n\nWhat it is: CVE-2021-37677 is a medium-severity denial of service 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-2021-37677 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-2021-37677/ (Markdown: https://insights.sbomify.com/CVE-2021-37677/index.md)","id":"CVE-2021-37677","markdown":"https://insights.sbomify.com/CVE-2021-37677/index.md","name":"CVE-2021-37677","record":{"aliases":["BIT-tensorflow-2021-37677","GHSA-qfpc-5pjr-mh26","PYSEC-2021-299","PYSEC-2021-590","PYSEC-2021-788"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["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 cause a denial of service via a segmentation fault in TensorFlow by providing invalid arguments to the Dequantize operation.","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":5.5,"severity":"medium","source":"cna","vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","version":"3.1"},"cwes":[{"id":"CWE-1284","name":"Improper Validation of Specified Quantity in Input"},{"id":"CWE-20","name":"Improper Input Validation"}],"description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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":"Missing validation in shape inference for `Dequantize` in TensorFlow","id":"CVE-2021-37677","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow"],"type":"denial_of_service","year":"2021"},"n_packages":22,"n_references":2,"next":{"headline":"Arbitrary code execution due to YAML deserialization","id":"CVE-2021-37678"},"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-2021-37677"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-qfpc-5pjr-mh26"},{"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-2021-299"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-qfpc-5pjr-mh26"},{"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-2021-590"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.3.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-qfpc-5pjr-mh26"},{"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-2021-788"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.4.3"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-qfpc-5pjr-mh26"},{"ecosystem":"PyPI","fixed":["2.5.1"],"introduced":["2.5.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-qfpc-5pjr-mh26"}],"prev":{"headline":"Reference binding to nullptr in shape inference in TensorFlow","id":"CVE-2021-37676"},"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 cause a denial of service via a segmentation fault in TensorFlow by providing invalid arguments to the Dequantize operation.","url":"https://insights.sbomify.com/CVE-2021-37677/"}