{"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-2020-15200 in the wild and no public exploit code.","fix":"Upgrade tensorflow to 2.3.1 or later.","what":"CVE-2020-15200 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-2020-15200 and fix it if it is affected.\n\nWhat it is: CVE-2020-15200 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-2020-15200 in the wild and no public exploit code.\n\nAffected packages and fixed versions:\n- tensorflow (Bitnami): affected from 2.3.0; fixed in 2.3.1\n- tensorflow (PyPI): affected all versions; fixed in 2.3.1\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- tensorflow-cpu (PyPI): affected all versions; fixed in 2.3.1\n- tensorflow-cpu (PyPI): affected from 2.3.0; fixed in 2.3.1\n- tensorflow-cpu (PyPI): affected from 2.3.0; fixed in 2.3.1\n- tensorflow-gpu (PyPI): affected all versions; fixed in 2.3.1\n- tensorflow-gpu (PyPI): affected from 2.3.0; fixed in 2.3.1\n- tensorflow-gpu (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-2020-15200/ (Markdown: https://insights.sbomify.com/CVE-2020-15200/index.md)","id":"CVE-2020-15200","markdown":"https://insights.sbomify.com/CVE-2020-15200/index.md","name":"CVE-2020-15200","record":{"aliases":["BIT-tensorflow-2020-15200","GHSA-x7rp-74x2-mjf3","PYSEC-2020-123","PYSEC-2020-280","PYSEC-2020-315"],"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 providing invalid ragged tensor inputs to RaggedCountSparseOutput.","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-787","name":"Out-of-bounds Write"},{"id":"CWE-20","name":"Improper Input Validation"},{"id":"CWE-122","name":"Heap-based Buffer Overflow"}],"description":"In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 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":"Segfault in Tensorflow","id":"CVE-2020-15200","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":"Heap buffer overflow in Tensorflow","id":"CVE-2020-15201"},"packages":[{"ecosystem":"Bitnami","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:bitnami/tensorflow","source":"BIT-tensorflow-2020-15200"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"PYSEC-2020-123"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-x7rp-74x2-mjf3"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-x7rp-74x2-mjf3"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"PYSEC-2020-280"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-x7rp-74x2-mjf3"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-x7rp-74x2-mjf3"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"PYSEC-2020-315"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-x7rp-74x2-mjf3"},{"ecosystem":"PyPI","fixed":["2.3.1"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-x7rp-74x2-mjf3"}],"prev":{"headline":"Denial of Service in Tensorflow","id":"CVE-2020-15199"},"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":"An attacker can cause a segmentation fault and denial of service in TensorFlow by providing invalid ragged tensor inputs to RaggedCountSparseOutput.","url":"https://insights.sbomify.com/CVE-2020-15200/"}