{"answers":{"affected":"34 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-2020-26270 in the wild and no public exploit code.","fix":"Upgrade tensorflow to a fixed version for your release line: 1.15.5, 2.0.4, 2.1.3 or 2.2.2.","what":"CVE-2020-26270 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 10 Dec 2020. 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-2020-26270 and fix it if it is affected.\n\nWhat it is: CVE-2020-26270 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 10 Dec 2020. 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-2020-26270 in the wild and no public exploit code.\n\nAffected packages and fixed versions:\n- tensorflow (Bitnami): affected all versions; fixed in 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2\n- tensorflow (PyPI): affected all versions; fixed in 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2\n- tensorflow (PyPI): affected all versions; fixed in 1.15.5\n- tensorflow (PyPI): affected all versions; fixed in 1.15.5\n- tensorflow (PyPI): affected from 2.0.0; fixed in 2.0.4\n- tensorflow (PyPI): affected from 2.0.0; fixed in 2.0.4\n- tensorflow (PyPI): affected from 2.1.0; fixed in 2.1.3\n- tensorflow (PyPI): affected from 2.1.0; fixed in 2.1.3\n- tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.2\n- tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.2\n- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.2\n- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.2\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-2020-26270/ (Markdown: https://insights.sbomify.com/CVE-2020-26270/index.md)","id":"CVE-2020-26270","markdown":"https://insights.sbomify.com/CVE-2020-26270/index.md","name":"CVE-2020-26270","record":{"aliases":["BIT-tensorflow-2020-26270","GHSA-m648-33qf-v3gp","PYSEC-2020-256","PYSEC-2020-301","PYSEC-2020-336"],"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":"Attackers can cause a denial of service in TensorFlow LSTM/GRU models by providing zero-length inputs, triggering a CHECK failure on CUDA backends.","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":4.4,"severity":"medium","source":"cna","vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L","version":"3.1"},"cwes":[{"id":"CWE-20","name":"Improper Input Validation"}],"description":"In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.","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":"CHECK-fail in LSTM with zero-length input in TensorFlow","id":"CVE-2020-26270","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow"],"type":"denial_of_service","year":"2020"},"n_packages":34,"n_references":2,"next":{"headline":"Heap out of bounds access in MakeEdge in TensorFlow","id":"CVE-2020-26271"},"packages":[{"ecosystem":"Bitnami","fixed":["1.15.5","2.0.4","2.1.3","2.2.2","2.3.2"],"introduced":["0","2.0.0","2.1.0","2.2.0","2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:bitnami/tensorflow","source":"BIT-tensorflow-2020-26270"},{"ecosystem":"PyPI","fixed":["1.15.5","2.0.4","2.1.3","2.2.2","2.3.2"],"introduced":["0","2.0.0","2.1.0","2.2.0","2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"PYSEC-2020-256"},{"ecosystem":"PyPI","fixed":["1.15.5"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["1.15.5"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.0.4"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.0.4"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.1.3"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.1.3"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.2.2"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.2.2"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.3.2"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.3.2"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["1.15.5","2.0.4","2.1.3","2.2.2","2.3.2"],"introduced":["0","2.0.0","2.1.0","2.2.0","2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"PYSEC-2020-301"},{"ecosystem":"PyPI","fixed":["1.15.5"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["1.15.5"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.0.4"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.0.4"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.1.3"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.1.3"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.2.2"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.2.2"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.3.2"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.3.2"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["1.15.5","2.0.4","2.1.3","2.2.2","2.3.2"],"introduced":["0","2.0.0","2.1.0","2.2.0","2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"PYSEC-2020-336"},{"ecosystem":"PyPI","fixed":["1.15.5"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["1.15.5"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.0.4"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.0.4"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.1.3"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.1.3"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.2.2"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.2.2"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.3.2"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-m648-33qf-v3gp"},{"ecosystem":"PyPI","fixed":["2.3.2"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-m648-33qf-v3gp"}],"prev":{"headline":"Heap out of bounds read in filesystem glob matching in TensorFlow","id":"CVE-2020-26269"},"products":["tensorflow"],"published":"2020-12-10","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":"Attackers can cause a denial of service in TensorFlow LSTM/GRU models by providing zero-length inputs, triggering a CHECK failure on CUDA backends.","url":"https://insights.sbomify.com/CVE-2020-26270/"}