CVE-2020-26268: Tensorflow Write To Immutable Memory Region Vulnerability

Q: What is CVE-2020-26268?

CVE-2020-26268 is a security vulnerability in Tensorflow involving Write to immutable memory region in TensorFlow under CWE-471: Modification of Assumed-Immutable Data (MAID).

Q: Which Tensorflow versions are affected?

Affected versions include releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

Q: What version fixes CVE-2020-26268?

Upgrading to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 (or the latest patched release for your respective branch) resolves the vulnerability.

Q: Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2. Upgrade your dependency to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or later.

Q: Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2. Upgrade your dependency to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or later.

Q: What is the CVSS score of CVE-2020-26268?

CVE-2020-26268 has a CVSS v3.1 base score of 4.4 (MODERATE) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L.

Q: What CWE is associated with CVE-2020-26268?

CVE-2020-26268 is classified under CWE-471: Modification of Assumed-Immutable Data (MAID) (The product does not properly protect an assumed-immutable element from being modified by an attacker.).

Q: How can I check PyPI dependencies for CVE-2020-26268?

Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.

MODERATE

Advisory Identifier: GHSA-hhvc-g5hv-48c6

CVSS 4.4

CWE-471

Published 2020-12-10

Advisory Summary

CVE-2020-26268 is a MODERATE (CVSS 4.4) write to immutable memory region vulnerability (CWE-471: Modification of Assumed-Immutable Data (MAID)) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves write to immutable memory region in tensorflow. Remediation is available by upgrading affected packages to version 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2.

CVE-2020-26268 at a Glance

CVE Identifier CVE-2020-26268

GHSA Identifier GHSA-hhvc-g5hv-48c6

Severity MODERATE

CVSS v3.1 Base Score 4.4

CWE Classification CWE-471: Modification of Assumed-Immutable Data (MAID)

Affected Product Tensorflow

Package Ecosystem PyPI

Published Date 2020-12-10

Last Updated 2024-10-28

Security Impact

CVSS: 4.4

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L).

Attack Vector Local (AV:L)

Attack Complexity Low (AC:L)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity Low (I:L)

Availability Low (A:L)

How to Fix CVE-2020-26268

To remediate this vulnerability, upgrade all affected Tensorflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

tensorflow fixed: 1.15.5

pip install tensorflow>=1.15.5

tensorflow fixed: 2.0.4

pip install tensorflow>=2.0.4

tensorflow fixed: 2.1.3

pip install tensorflow>=2.1.3

tensorflow fixed: 2.2.2

pip install tensorflow>=2.2.2

tensorflow fixed: 2.3.2

pip install tensorflow>=2.3.2

tensorflow-cpu fixed: 1.15.5

pip install tensorflow-cpu>=1.15.5

tensorflow-cpu fixed: 2.0.4

pip install tensorflow-cpu>=2.0.4

tensorflow-cpu fixed: 2.1.3

pip install tensorflow-cpu>=2.1.3

tensorflow-cpu fixed: 2.2.2

pip install tensorflow-cpu>=2.2.2

tensorflow-cpu fixed: 2.3.2

pip install tensorflow-cpu>=2.3.2

tensorflow-gpu fixed: 1.15.5

pip install tensorflow-gpu>=1.15.5

tensorflow-gpu fixed: 2.0.4

pip install tensorflow-gpu>=2.0.4

tensorflow-gpu fixed: 2.1.3

pip install tensorflow-gpu>=2.1.3

tensorflow-gpu fixed: 2.2.2

pip install tensorflow-gpu>=2.2.2

tensorflow-gpu fixed: 2.3.2

pip install tensorflow-gpu>=2.3.2

Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show tensorflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2020-26268, inspect your installed packages using pip:

pip show tensorflow

Analyze the terminal output to locate any version of Tensorflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 1.15.5), your application is affected.

Note: The pip show tensorflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-471: Modification of Assumed-Immutable Data (MAID), where the product does not properly protect an assumed-immutable element from being modified by an attacker. In Tensorflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Impact The `tf.raw_ops.ImmutableConst` operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the memory area: ```python >>> import tensorflow as tf >>> with open('/tmp/test.txt','w') as f: f.write('a'*128) >>> tf.raw_ops.ImmutableConst(dtype=tf.string,shape=2, memory_region_name='/tmp/test.txt') ``` If the file is too small, TensorFlow properly returns an error as the memory area has fewer bytes than what is needed for the tensor it creates. However, as soon as there are enough bytes, the above snippet causes a segmentation fault. This is because the alocator used to return the buffer data is not marked as returning an opaque handle since the [needed virtual method](https://github.com/tensorflow/tensorflow/blob/c1e1fc899ad5f8c725dcbb6470069890b5060bc7/tensorflow/core/framework/typed_allocator.h#L78-L85) is [not overriden](https://github.com/tensorflow/tensorflow/blob/acdf3c04fcfa767ae8d109b9e1f727ef050dba4d/tensorflow/core/kernels/immutable_constant_op.cc). ### Patches We have patched the issue in GitHub commit [c1e1fc899ad5f8c725dcbb6470069890b5060bc7](https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

CVE-2020-26268 Affected Tensorflow Versions

15 component(s)

Fixed Versions:

1.15.52.0.42.1.32.2.22.3.2

Product / Package	Ecosystem	Affected Versions	Fixed Version
tensorflow pypi/tensorflow	PyPI	< 1.15.5	1.15.5
tensorflow pypi/tensorflow	PyPI	≥ 2.0.0 < 2.0.4	2.0.4
tensorflow pypi/tensorflow	PyPI	≥ 2.1.0 < 2.1.3	2.1.3
tensorflow pypi/tensorflow	PyPI	≥ 2.2.0 < 2.2.2	2.2.2
tensorflow pypi/tensorflow	PyPI	≥ 2.3.0 < 2.3.2	2.3.2
tensorflow-cpu pypi/tensorflow-cpu	PyPI	< 1.15.5	1.15.5
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.0.0 < 2.0.4	2.0.4
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.1.0 < 2.1.3	2.1.3
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.2.0 < 2.2.2	2.2.2
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.3.0 < 2.3.2	2.3.2
tensorflow-gpu pypi/tensorflow-gpu	PyPI	< 1.15.5	1.15.5
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.0.0 < 2.0.4	2.0.4
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.1.0 < 2.1.3	2.1.3
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.2.0 < 2.2.2	2.2.2
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.3.0 < 2.3.2	2.3.2

References

GitHub Advisory / Wiki ADVISORY

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hhvc-g5hv-48c6

NVD — CVE-2020-26268 NVD

https://nvd.nist.gov/vuln/detail/CVE-2020-26268

Security Fix Commit FIX COMMIT

https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-299.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-334.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-255.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/tensorflow/tensorflow

Frequently Asked Questions

What is CVE-2020-26268?

CVE-2020-26268 is a security vulnerability in Tensorflow involving Write to immutable memory region in TensorFlow under CWE-471: Modification of Assumed-Immutable Data (MAID).

Which Tensorflow versions are affected?

Affected versions include releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

What version fixes CVE-2020-26268?

Upgrading to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 (or the latest patched release for your respective branch) resolves the vulnerability.

Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2. Upgrade your dependency to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or later.

Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2. Upgrade your dependency to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or later.

What is the CVSS score of CVE-2020-26268?

CVE-2020-26268 has a CVSS v3.1 base score of 4.4 (MODERATE) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L.

What CWE is associated with CVE-2020-26268?

CVE-2020-26268 is classified under CWE-471: Modification of Assumed-Immutable Data (MAID) (The product does not properly protect an assumed-immutable element from being modified by an attacker.).

How can I check PyPI dependencies for CVE-2020-26268?

Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.

Machine-readable OSV JSON OSV v1.5 Schema

Normalized schema output

View Raw JSON

{
  "schema_version" : "1.4.0",
  "id" : "GHSA-hhvc-g5hv-48c6",
  "modified" : "2024-10-28T20:04:42Z",
  "published" : "2020-12-10T19:07:28Z",
  "aliases" : [ "CVE-2020-26268" ],
  "summary" : "Write to immutable memory region in TensorFlow",
  "details" : "### Impact\nThe `tf.raw_ops.ImmutableConst` operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the memory area:\n\n```python\n>>> import tensorflow as tf\n>>> with open('/tmp/test.txt','w') as f: f.write('a'*128)\n>>> tf.raw_ops.ImmutableConst(dtype=tf.string,shape=2,\n                              memory_region_name='/tmp/test.txt')\n```\n\nIf the file is too small, TensorFlow properly returns an error as the memory area has fewer bytes than what is needed for the tensor it creates. However, as soon as there are enough bytes, the above snippet causes a segmentation fault.\n\nThis is because the alocator used to return the buffer data is not marked as returning an opaque handle since the [needed virtual method](https://github.com/tensorflow/tensorflow/blob/c1e1fc899ad5f8c725dcbb6470069890b5060bc7/tensorflow/core/framework/typed_allocator.h#L78-L85) is [not overriden](https://github.com/tensorflow/tensorflow/blob/acdf3c04fcfa767ae8d109b9e1f727ef050dba4d/tensorflow/core/kernels/immutable_constant_op.cc).\n\n### Patches\nWe have patched the issue in GitHub commit [c1e1fc899ad5f8c725dcbb6470069890b5060bc7](https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.\n\nSince this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by members of the Aivul Team from Qihoo 360.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "1.15.5"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.0.0"
      }, {
        "fixed" : "2.0.4"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.1.0"
      }, {
        "fixed" : "2.1.3"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.2.0"
      }, {
        "fixed" : "2.2.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.3.0"
      }, {
        "fixed" : "2.3.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "1.15.5"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.0.0"
      }, {
        "fixed" : "2.0.4"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.1.0"
      }, {
        "fixed" : "2.1.3"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.2.0"
      }, {
        "fixed" : "2.2.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.3.0"
      }, {
        "fixed" : "2.3.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "1.15.5"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.0.0"
      }, {
        "fixed" : "2.0.4"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.1.0"
      }, {
        "fixed" : "2.1.3"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.2.0"
      }, {
        "fixed" : "2.2.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.3.0"
      }, {
        "fixed" : "2.3.2"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hhvc-g5hv-48c6"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2020-26268"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-299.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-334.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-255.yaml"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/tensorflow/tensorflow"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-471" ],
    "severity" : "MODERATE",
    "github_reviewed" : true,
    "github_reviewed_at" : "2020-12-10T19:05:24Z",
    "nvd_published_at" : null
  }
}

CVSS V3

4.4 MODERATE

Attack Vector Local (AV:L)

Attack Complexity Low (AC:L)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity Low (I:L)

Availability Low (A:L)

Vector String

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

Advisory Metadata

Source ID: GHSA-hhvc-g5hv-48c6
Schema Version: 1.4.0
Published: 2020-12-10 19:07
Last Modified: 2024-10-28 20:04
Database Record File: advisories/github-reviewed/2020/12/GHSA-hhvc-g5hv-48c6/GHSA-hhvc-g5hv-48c6.json