{"answers":{"affected":"10 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-2020-15265 in the wild and no public exploit code.","fix":"Upgrade tensorflow to 2.4.0 or later.","what":"CVE-2020-15265 is a medium-severity memory corruption vulnerability in Google Tensorflow, published on 21 Oct 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-2020-15265 and fix it if it is affected.\n\nWhat it is: CVE-2020-15265 is a medium-severity memory corruption vulnerability in Google Tensorflow, published on 21 Oct 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-2020-15265 in the wild and no public exploit code.\n\nAffected packages and fixed versions:\n- tensorflow (Bitnami): affected all versions; fixed in 2.4.0\n- tensorflow (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow-gpu (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow-gpu (PyPI): affected all versions; fixed in 2.4.0\n- tensorflow-gpu (PyPI): affected all versions; fixed in 2.4.0\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-2020-15265/ (Markdown: https://insights.sbomify.com/CVE-2020-15265/index.md)","id":"CVE-2020-15265","markdown":"https://insights.sbomify.com/CVE-2020-15265/index.md","name":"CVE-2020-15265","record":{"aliases":["BIT-tensorflow-2020-15265","GHSA-rrfp-j2mp-hq9c","PYSEC-2020-138","PYSEC-2020-295","PYSEC-2020-330"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["denial_of_service"],"network_reachable":"yes","non_default_config":false,"product_category":"TensorFlow library","requires_auth":"none","summary":"An attacker can cause a segmentation fault and denial of service in TensorFlow by passing an invalid axis value to the quantization function.","user_interaction":"not_required","vuln_class":"memory_corruption"},"analysis_generated_by":"qwen3.8-flash-next","assigner":"GitHub_M","cpe":[{"product":"tensorflow","vendor":"google"}],"cvss":{"score":5.9,"severity":"medium","source":"cna","vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","version":"3.1"},"cwes":[{"id":"CWE-125","name":"Out-of-bounds Read"}],"description":"In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.","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":"Segfault in Tensorflow","id":"CVE-2020-15265","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow"],"type":"memory_corruption","year":"2020"},"n_packages":10,"n_references":3,"next":{"headline":"Undefined behavior in Tensorflow","id":"CVE-2020-15266"},"packages":[{"ecosystem":"Bitnami","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:bitnami/tensorflow","source":"BIT-tensorflow-2020-15265"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-rrfp-j2mp-hq9c"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-rrfp-j2mp-hq9c"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"PYSEC-2020-138"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-rrfp-j2mp-hq9c"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-rrfp-j2mp-hq9c"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"PYSEC-2020-295"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-rrfp-j2mp-hq9c"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-rrfp-j2mp-hq9c"},{"ecosystem":"PyPI","fixed":["2.4.0"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"PYSEC-2020-330"}],"prev":{"headline":"Privilege Escalation in Boxstarter","id":"CVE-2020-15264"},"products":["tensorflow"],"published":"2020-10-21","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 segmentation fault and denial of service in TensorFlow by passing an invalid axis value to the quantization function.","url":"https://insights.sbomify.com/CVE-2020-15265/"}