{"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-2021-29550 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-2021-29550 is a low-severity denial of service 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-2021-29550 and fix it if it is affected.\n\nWhat it is: CVE-2021-29550 is a low-severity denial of service 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-2021-29550 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-2021-29550/ (Markdown: https://insights.sbomify.com/CVE-2021-29550/index.md)","id":"CVE-2021-29550","markdown":"https://insights.sbomify.com/CVE-2021-29550/index.md","name":"CVE-2021-29550","record":{"aliases":["BIT-tensorflow-2021-29550","GHSA-f78g-q7r4-9wcv","PYSEC-2021-187","PYSEC-2021-478","PYSEC-2021-676"],"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":"An attacker can cause a denial of service in TensorFlow by triggering a division by zero error in the FractionalAvgPool operation.","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":2.5,"severity":"low","source":"cna","vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L","version":"3.1"},"cwes":[{"id":"CWE-369","name":"Divide By Zero"}],"description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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":"Division by 0 in `FractionalAvgPool`","id":"CVE-2021-29550","indexable":true,"kev":null,"kind":"cve","links":{"ecosystem":"Bitnami","product":"google:tensorflow","products":["google:tensorflow"],"type":"denial_of_service","year":"2021"},"n_packages":28,"n_references":2,"next":{"headline":"OOB read in `MatrixTriangularSolve`","id":"CVE-2021-29551"},"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-2021-29550"},{"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-2021-187"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-f78g-q7r4-9wcv"},{"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-2021-478"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-f78g-q7r4-9wcv"},{"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-2021-676"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-f78g-q7r4-9wcv"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-f78g-q7r4-9wcv"}],"prev":{"headline":"Division by 0 in `QuantizedAdd`","id":"CVE-2021-29549"},"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":"An attacker can cause a denial of service in TensorFlow by triggering a division by zero error in the FractionalAvgPool operation.","url":"https://insights.sbomify.com/CVE-2021-29550/"}