{"answers":{"affected":"28 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-2021-29571 in the wild and no public exploit code.","fix":"Upgrade tensorflow to a fixed version for your release line: 2.1.4, 2.2.3, 2.3.3 or 2.4.2.","what":"CVE-2021-29571 is a medium-severity memory corruption vulnerability in Google Tensorflow, published on 14 May 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-2021-29571 and fix it if it is affected.\n\nWhat it is: CVE-2021-29571 is a medium-severity memory corruption vulnerability in Google Tensorflow, published on 14 May 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-2021-29571 in the wild and no public exploit code.\n\nAffected packages and fixed versions:\n- tensorflow (Bitnami): affected all versions; fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2\n- tensorflow (PyPI): affected all versions; fixed in 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3\n- tensorflow (PyPI): affected all versions; fixed in 2.1.4\n- tensorflow (PyPI): affected all versions; fixed in 2.1.4\n- tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.3\n- tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.3\n- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.3\n- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.3\n- tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.2\n- tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.2\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3\n- tensorflow-cpu (PyPI): affected all versions; fixed in 2.1.4\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-2021-29571/ (Markdown: https://insights.sbomify.com/CVE-2021-29571/index.md)","id":"CVE-2021-29571","markdown":"https://insights.sbomify.com/CVE-2021-29571/index.md","name":"CVE-2021-29571","record":{"aliases":["BIT-tensorflow-2021-29571","GHSA-whr9-vfh2-7hm6","PYSEC-2021-208","PYSEC-2021-499","PYSEC-2021-697"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["code_execution","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 trigger out-of-bounds writes in TensorFlow's DrawBoundingBoxesV2 operation via crafted inputs, leading to memory corruption and potential code execution.","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":4.5,"severity":"medium","source":"cna","vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:L","version":"3.1"},"cwes":[{"id":"CWE-787","name":"Out-of-bounds Write"}],"description":"TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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":"Memory corruption in `DrawBoundingBoxesV2`","id":"CVE-2021-29571","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow"],"type":"memory_corruption","year":"2021"},"n_packages":28,"n_references":2,"next":{"headline":"Reference binding to nullptr in `SdcaOptimizer`","id":"CVE-2021-29572"},"packages":[{"ecosystem":"Bitnami","fixed":["2.1.4","2.2.3","2.3.3","2.4.2"],"introduced":["0","2.2.0","2.3.0","2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:bitnami/tensorflow","source":"BIT-tensorflow-2021-29571"},{"ecosystem":"PyPI","fixed":["2.2.0rc0","2.3.0rc0","2.3.4","2.4.3"],"introduced":["0","2.2.0","2.3.0","2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"PYSEC-2021-208"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.0rc0","2.3.0rc0","2.3.4","2.4.3"],"introduced":["0","2.2.0","2.3.0","2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"PYSEC-2021-499"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.0rc0","2.3.0rc0","2.3.4","2.4.3"],"introduced":["0","2.2.0","2.3.0","2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"PYSEC-2021-697"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-whr9-vfh2-7hm6"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-whr9-vfh2-7hm6"}],"prev":{"headline":"Heap out of bounds read in `MaxPoolGradWithArgmax`","id":"CVE-2021-29570"},"products":["tensorflow"],"published":"2021-05-14","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":"2024-08-03","vendors":["tensorflow"]},"summary":"Attackers can trigger out-of-bounds writes in TensorFlow's DrawBoundingBoxesV2 operation via crafted inputs, leading to memory corruption and potential code execution.","url":"https://insights.sbomify.com/CVE-2021-29571/"}