Lookup for vulnerable packages by Package URL.

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{
    "url": "http://public2.vulnerablecode.io/api/packages/24864?format=api",
    "purl": "pkg:pypi/tensorflow@2.6.0",
    "type": "pypi",
    "namespace": "",
    "name": "tensorflow",
    "version": "2.6.0",
    "qualifiers": {},
    "subpath": "",
    "is_vulnerable": true,
    "next_non_vulnerable_version": "2.6.1",
    "latest_non_vulnerable_version": "2.12.0",
    "affected_by_vulnerabilities": [
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/36029?format=api",
            "vulnerability_id": "VCID-217a-71wn-nybg",
            "summary": "Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.",
            "references": [
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-81.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-81.yaml"
                },
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-136.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-136.yaml"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rww7-2gpw-fv6j",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rww7-2gpw-fv6j"
                },
                {
                    "reference_url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23572",
                    "reference_id": "CVE-2022-23572",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23572"
                },
                {
                    "reference_url": "https://github.com/advisories/GHSA-rww7-2gpw-fv6j",
                    "reference_id": "GHSA-rww7-2gpw-fv6j",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/advisories/GHSA-rww7-2gpw-fv6j"
                }
            ],
            "fixed_packages": [
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60393?format=api",
                    "purl": "pkg:pypi/tensorflow@2.6.3",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.6.3"
                },
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60383?format=api",
                    "purl": "pkg:pypi/tensorflow@2.7.1",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.7.1"
                }
            ],
            "aliases": [
                "CVE-2022-23572",
                "GHSA-rww7-2gpw-fv6j",
                "PYSEC-2022-136",
                "PYSEC-2022-81"
            ],
            "risk_score": null,
            "exploitability": null,
            "weighted_severity": null,
            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-217a-71wn-nybg"
        },
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/36002?format=api",
            "vulnerability_id": "VCID-2hj4-bbfq-xqfj",
            "summary": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateTensorSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
            "references": [
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-84.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-84.yaml"
                },
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-139.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-139.yaml"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c94w-c95p-phf8",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c94w-c95p-phf8"
                },
                {
                    "reference_url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23575",
                    "reference_id": "CVE-2022-23575",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23575"
                },
                {
                    "reference_url": "https://github.com/advisories/GHSA-c94w-c95p-phf8",
                    "reference_id": "GHSA-c94w-c95p-phf8",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/advisories/GHSA-c94w-c95p-phf8"
                }
            ],
            "fixed_packages": [
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60393?format=api",
                    "purl": "pkg:pypi/tensorflow@2.6.3",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.6.3"
                },
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60383?format=api",
                    "purl": "pkg:pypi/tensorflow@2.7.1",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.7.1"
                }
            ],
            "aliases": [
                "CVE-2022-23575",
                "GHSA-c94w-c95p-phf8",
                "PYSEC-2022-139",
                "PYSEC-2022-84"
            ],
            "risk_score": null,
            "exploitability": null,
            "weighted_severity": null,
            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-2hj4-bbfq-xqfj"
        },
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/36004?format=api",
            "vulnerability_id": "VCID-2sak-438s-bbg8",
            "summary": "Tensorflow is an Open Source Machine Learning Framework. TensorFlow is vulnerable to a heap OOB write in `Grappler`. The `set_output` function writes to an array at the specified index. Hence, this gives a malicious user a write primitive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
            "references": [
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-75.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-75.yaml"
                },
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-130.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-130.yaml"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.h#L394",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.h#L394"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/graph_properties.cc#L1132-L1141",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/graph_properties.cc#L1132-L1141"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/commit/97282c6d0d34476b6ba033f961590b783fa184cd",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/commit/97282c6d0d34476b6ba033f961590b783fa184cd"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5qw5-89mw-wcg2",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5qw5-89mw-wcg2"
                },
                {
                    "reference_url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23566",
                    "reference_id": "CVE-2022-23566",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23566"
                },
                {
                    "reference_url": "https://github.com/advisories/GHSA-5qw5-89mw-wcg2",
                    "reference_id": "GHSA-5qw5-89mw-wcg2",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/advisories/GHSA-5qw5-89mw-wcg2"
                }
            ],
            "fixed_packages": [
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60393?format=api",
                    "purl": "pkg:pypi/tensorflow@2.6.3",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.6.3"
                },
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60383?format=api",
                    "purl": "pkg:pypi/tensorflow@2.7.1",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.7.1"
                }
            ],
            "aliases": [
                "CVE-2022-23566",
                "GHSA-5qw5-89mw-wcg2",
                "PYSEC-2022-130",
                "PYSEC-2022-75"
            ],
            "risk_score": null,
            "exploitability": null,
            "weighted_severity": null,
            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-2sak-438s-bbg8"
        },
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/36033?format=api",
            "vulnerability_id": "VCID-2t7w-zpd8-suc9",
            "summary": "Tensorflow is an Open Source Machine Learning Framework. In multiple places, TensorFlow uses `tempfile.mktemp` to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename in `mktemp` and the actual creation of the file by a subsequent operation (a TOC/TOU type of weakness). In several instances, TensorFlow was supposed to actually create a temporary directory instead of a file. This logic bug is hidden away by the `mktemp` function usage. We have patched the issue in several commits, replacing `mktemp` with the safer `mkstemp`/`mkdtemp` functions, according to the usage pattern. Users are advised to upgrade as soon as possible.",
            "references": [
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-72.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-72.yaml"
                },
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-127.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-127.yaml"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wc4g-r73w-x8mm",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wc4g-r73w-x8mm"
                },
                {
                    "reference_url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23563",
                    "reference_id": "CVE-2022-23563",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23563"
                },
                {
                    "reference_url": "https://github.com/advisories/GHSA-wc4g-r73w-x8mm",
                    "reference_id": "GHSA-wc4g-r73w-x8mm",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/advisories/GHSA-wc4g-r73w-x8mm"
                }
            ],
            "fixed_packages": [
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60393?format=api",
                    "purl": "pkg:pypi/tensorflow@2.6.3",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.6.3"
                },
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60383?format=api",
                    "purl": "pkg:pypi/tensorflow@2.7.1",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.7.1"
                }
            ],
            "aliases": [
                "CVE-2022-23563",
                "GHSA-wc4g-r73w-x8mm",
                "PYSEC-2022-127",
                "PYSEC-2022-72"
            ],
            "risk_score": null,
            "exploitability": null,
            "weighted_severity": null,
            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-2t7w-zpd8-suc9"
        },
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/42296?format=api",
            "vulnerability_id": "VCID-3nws-uqh8-wydf",
            "summary": "NULL Pointer Dereference and Access of Uninitialized Pointer in TensorFlow\n### Impact \nThe code for boosted trees in TensorFlow is still missing validation. This allows malicious users to read and write outside of bounds of heap allocated data as well as trigger denial of service (via dereferencing `nullptr`s or via `CHECK`-failures).\n\nThis follows after CVE-2021-41208 where these APIs were still vulnerable to multiple security issues.\n\n**Note**: Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs.  Instead, please use the downstream [TensorFlow Decision Forests] project which is newer and supports more features. \n  \nThese APIs are now deprecated in TensorFlow 2.8. We will remove TensorFlow's boosted trees APIs in subsequent releases.\n  \n### Patches\nWe have patched the known issues in multiple GitHub commits.\n  \nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.\n\nThis should allow users to use existing boosted trees APIs for a while until they migrate to TensorFlow Decision Forests while guaranteeing that known vulnerabilities are fixed.\n\n### For more information\nPlease consult our security guide for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThese vulnerabilities have been reported by Yu Tian of Qihoo 360 AIVul Team and Faysal Hossain Shezan from University of Virginia. Some of the issues have been discovered internally after a careful audit of the APIs.",
            "references": [
                {
                    "reference_url": "https://github.com/advisories/GHSA-h6gw-r52c-724r",
                    "reference_id": "GHSA-h6gw-r52c-724r",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/advisories/GHSA-h6gw-r52c-724r"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6gw-r52c-724r",
                    "reference_id": "GHSA-h6gw-r52c-724r",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6gw-r52c-724r"
                }
            ],
            "fixed_packages": [
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60393?format=api",
                    "purl": "pkg:pypi/tensorflow@2.6.3",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.6.3"
                },
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60383?format=api",
                    "purl": "pkg:pypi/tensorflow@2.7.1",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/tensorflow@2.7.1"
                }
            ],
            "aliases": [
                "GHSA-h6gw-r52c-724r",
                "GMS-2022-49",
                "GMS-2022-52",
                "GMS-2022-55"
            ],
            "risk_score": null,
            "exploitability": null,
            "weighted_severity": null,
            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-3nws-uqh8-wydf"
        },
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/35981?format=api",
            "vulnerability_id": "VCID-3y5w-424q-8qcn",
            "summary": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
            "references": [
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-50.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-50.yaml"
                },
                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-105.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-105.yaml"
                },
                {
                    "reference_url": "https://github.com/tensorflow/tensorflow",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/tensorflow/tensorflow"
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            "summary": "Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, Grappler component of TensorFlow is vulnerable to an integer overflow during cost estimation for crop and resize. Since the cropping parameters are user controlled, a malicious person can trigger undefined behavior. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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                "GHSA-vwhq-49r4-gj9v",
                "PYSEC-2021-406",
                "PYSEC-2021-623",
                "PYSEC-2021-821"
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            "vulnerability_id": "VCID-87r3-u8t5-m7d2",
            "summary": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `UnravelIndex` is vulnerable to a division by zero caused by an integer overflow bug. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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                {
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                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23588"
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                            "value": "High",
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                    "scores": [
                        {
                            "value": "High",
                            "scoring_system": "archlinux",
                            "scoring_elements": ""
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                    "reference_url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41221",
                    "reference_id": "CVE-2021-41221",
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                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41221"
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                        {
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                        {
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                        {
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                        {
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                        {
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                        {
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                        {
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                        {
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                        {
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                        {
                            "vulnerability": "VCID-psey-gff8-nyg8"
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                        {
                            "vulnerability": "VCID-pve4-4466-tqah"
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                        {
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                        {
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                        {
                            "vulnerability": "VCID-tdw3-fns6-6baz"
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                        {
                            "vulnerability": "VCID-u197-te8d-jydm"
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                        {
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                        {
                            "vulnerability": "VCID-w1s8-6nq3-4bgp"
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                        {
                            "vulnerability": "VCID-xftt-xdnj-fuhd"
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                        {
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                        {
                            "vulnerability": "VCID-zj5j-12r4-4bhp"
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                        {
                            "vulnerability": "VCID-zztr-pqqn-w7fd"
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                "CVE-2021-41221",
                "GHSA-cqv6-3phm-hcwx",
                "PYSEC-2021-413",
                "PYSEC-2021-630",
                "PYSEC-2021-828"
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            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-bh5b-u3zt-puf9"
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            "vulnerability_id": "VCID-bmvq-fjkr-2fc3",
            "summary": "Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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                    "reference_id": "",
                    "reference_type": "",
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                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-65.yaml"
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                {
                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-120.yaml",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-120.yaml"
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                    "reference_id": "",
                    "reference_type": "",
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                    "reference_id": "CVE-2022-21741",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-21741"
                },
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                    "reference_url": "https://github.com/advisories/GHSA-428x-9xc2-m8mj",
                    "reference_id": "GHSA-428x-9xc2-m8mj",
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                    "url": "https://github.com/advisories/GHSA-428x-9xc2-m8mj"
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            "summary": "Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of `ImmutableExecutorState::Initialize`. Here, we set `item->kernel` to `nullptr` but it is a simple `OpKernel*` pointer so the memory that was previously allocated to it would leak. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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                    "reference_url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-142.yaml",
                    "reference_id": "",
                    "reference_type": "",
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                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-142.yaml"
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                    "reference_id": "CVE-2022-23578",
                    "reference_type": "",
                    "scores": [],
                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23578"
                },
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                    "reference_url": "https://github.com/advisories/GHSA-8r7c-3cm2-3h8f",
                    "reference_id": "GHSA-8r7c-3cm2-3h8f",
                    "reference_type": "",
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                    "url": "http://public2.vulnerablecode.io/api/packages/60383?format=api",
                    "purl": "pkg:pypi/tensorflow@2.7.1",
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                "GHSA-8r7c-3cm2-3h8f",
                "PYSEC-2022-142",
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            "summary": "Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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                    "reference_id": "",
                    "reference_type": "",
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                    "reference_id": "",
                    "reference_type": "",
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                    "reference_type": "",
                    "scores": [],
                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23561"
                },
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                    "reference_url": "https://github.com/advisories/GHSA-9c78-vcq7-7vxq",
                    "reference_id": "GHSA-9c78-vcq7-7vxq",
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                {
                    "url": "http://public2.vulnerablecode.io/api/packages/60383?format=api",
                    "purl": "pkg:pypi/tensorflow@2.7.1",
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                "GHSA-9c78-vcq7-7vxq",
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            "summary": "multiple issues",
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                    "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-409.yaml"
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            "summary": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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                {
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            "summary": "Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that `TensorByteSize` would trigger `CHECK` failures. `TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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            "summary": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseCountSparseOutput` is vulnerable to a heap overflow. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
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                    "reference_url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23591",
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                    "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23591"
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