{"answers":{"affected":"34 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 2 products.","exploited":"There is no known exploitation of CVE-2020-15210 in the wild and no public exploit code.","fix":"Upgrade tensorflow to a fixed version for your release line: 1.15.4, 2.0.3, 2.1.2 or 2.2.1.","what":"CVE-2020-15210 is a medium-severity memory corruption vulnerability in Google Tensorflow, published on 25 Sep 2020. An attacker can exploit it over the internet without logging in, with no action from the victim."},"fix_prompt":"Check this codebase for CVE-2020-15210 and fix it if it is affected.\n\nWhat it is: CVE-2020-15210 is a medium-severity memory corruption vulnerability in Google Tensorflow, published on 25 Sep 2020. An attacker can exploit it over the internet without logging in, with no action from the victim.\nExploitation: There is no known exploitation of CVE-2020-15210 in the wild and no public exploit code.\n\nAffected packages and fixed versions:\n- tensorflow (Bitnami): affected all versions; fixed in 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1\n- tensorflow (PyPI): affected all versions; fixed in 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1\n- tensorflow (PyPI): affected all versions; fixed in 1.15.4\n- tensorflow (PyPI): affected all versions; fixed in 1.15.4\n- tensorflow (PyPI): affected from 2.0.0; fixed in 2.0.3\n- tensorflow (PyPI): affected from 2.0.0; fixed in 2.0.3\n- tensorflow (PyPI): affected from 2.1.0; fixed in 2.1.2\n- tensorflow (PyPI): affected from 2.1.0; fixed in 2.1.2\n- tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.1\n- tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.1\n- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.1\n- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.1\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-2020-15210/ (Markdown: https://insights.sbomify.com/CVE-2020-15210/index.md)","id":"CVE-2020-15210","markdown":"https://insights.sbomify.com/CVE-2020-15210/index.md","name":"CVE-2020-15210","record":{"aliases":["BIT-tensorflow-2020-15210","GHSA-x9j7-x98r-r4w2","PYSEC-2020-133","PYSEC-2020-290","PYSEC-2020-325"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["denial_of_service","code_execution"],"network_reachable":"yes","non_default_config":false,"product_category":"TensorFlow Lite library","requires_auth":"none","summary":"Attackers can cause segmentation faults or memory corruption in TensorFlow Lite by using a model where an operator shares input and output tensors.","user_interaction":"not_required","vuln_class":"memory_corruption"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"GitHub_M","cpe":[{"product":"tensorflow","vendor":"google"},{"product":"leap","vendor":"opensuse"}],"cvss":{"score":6.5,"severity":"medium","source":"cna","vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H","version":"3.1"},"cwes":[{"id":"CWE-787","name":"Out-of-bounds Write"},{"id":"CWE-20","name":"Improper Input Validation"}],"description":"In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.","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":"Segmentation fault in tensorflow-lite","id":"CVE-2020-15210","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow","opensuse:leap"],"type":"memory_corruption","year":"2020"},"n_packages":34,"n_references":4,"next":{"headline":"Out of bounds access in tensorflow-lite","id":"CVE-2020-15211"},"packages":[{"ecosystem":"Bitnami","fixed":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"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-2020-15210"},{"ecosystem":"PyPI","fixed":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"introduced":["0","2.0.0","2.1.0","2.2.0","2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"PYSEC-2020-133"},{"ecosystem":"PyPI","fixed":["1.15.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["1.15.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.0.3"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.0.3"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.1.2"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.1.2"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.2.1"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.2.1"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"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-2020-290"},{"ecosystem":"PyPI","fixed":["1.15.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["1.15.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.0.3"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.0.3"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.1.2"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.1.2"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.2.1"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.2.1"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["1.15.4","2.0.3","2.1.2","2.2.1","2.3.1"],"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-2020-325"},{"ecosystem":"PyPI","fixed":["1.15.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["1.15.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.0.3"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.0.3"],"introduced":["2.0.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.1.2"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.1.2"],"introduced":["2.1.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.2.1"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.2.1"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-x9j7-x98r-r4w2"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-x9j7-x98r-r4w2"}],"prev":{"headline":"Null pointer dereference in tensorflow-lite","id":"CVE-2020-15209"},"products":["tensorflow"],"published":"2020-09-25","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 segmentation faults or memory corruption in TensorFlow Lite by using a model where an operator shares input and output tensors.","url":"https://insights.sbomify.com/CVE-2020-15210/"}