{"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-2021-29533 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-2021-29533 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-2021-29533 and fix it if it is affected.\n\nWhat it is: CVE-2021-29533 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-2021-29533 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-2021-29533/ (Markdown: https://insights.sbomify.com/CVE-2021-29533/index.md)","id":"CVE-2021-29533","markdown":"https://insights.sbomify.com/CVE-2021-29533/index.md","name":"CVE-2021-29533","record":{"aliases":["BIT-tensorflow-2021-29533","GHSA-393f-2jr3-cp69","PYSEC-2021-170","PYSEC-2021-461","PYSEC-2021-659"],"analysis":{"component_type":"library","fix_type":"upgrade","impacts":["denial_of_service"],"network_reachable":"adjacent_or_local","non_default_config":false,"product_category":"TensorFlow ML library","requires_auth":"low_privilege","summary":"An attacker can cause a denial of service in TensorFlow by passing an empty image to DrawBoundingBoxes, triggering a CHECK failure and crashing the application.","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-754","name":"Improper Check for Unusual or Exceptional Conditions"}],"description":"TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`. In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution. 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":"CHECK-fail in DrawBoundingBoxes","id":"CVE-2021-29533","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":"CHECK-fail in SparseConcat","id":"CVE-2021-29534"},"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-2021-29533"},{"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-2021-170"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow","purl":"pkg:pypi/tensorflow","source":"GHSA-393f-2jr3-cp69"},{"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-2021-461"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-cpu","purl":"pkg:pypi/tensorflow-cpu","source":"GHSA-393f-2jr3-cp69"},{"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-2021-659"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.1.4"],"introduced":["0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.2.3"],"introduced":["2.2.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.3.3"],"introduced":["2.3.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":null,"source":"GHSA-393f-2jr3-cp69"},{"ecosystem":"PyPI","fixed":["2.4.2"],"introduced":["2.4.0"],"last_affected":[],"package":"tensorflow-gpu","purl":"pkg:pypi/tensorflow-gpu","source":"GHSA-393f-2jr3-cp69"}],"prev":{"headline":"Heap out of bounds read in `RaggedCross`","id":"CVE-2021-29532"},"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 passing an empty image to DrawBoundingBoxes, triggering a CHECK failure and crashing the application.","url":"https://insights.sbomify.com/CVE-2021-29533/"}