Vulnerability-Lookup

PYSEC-2020-128

Vulnerability from pysec - Published: 2020-09-25 19:15 - Updated: 2020-10-29 16:15

Details

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the data_splits argument of tf.raw_ops.StringNGrams lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after ee ff are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Impacted products

Name	purl
tensorflow	pkg:pypi/tensorflow

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0462de5b544ed4731aa2fb23946ac22c01856b80"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            },
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            },
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            },
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            },
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0rc0",
        "0.12.0rc1",
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0rc0",
        "1.1.0rc1",
        "1.1.0rc2",
        "1.1.0",
        "1.2.0rc0",
        "1.2.0rc1",
        "1.2.0rc2",
        "1.2.0",
        "1.2.1",
        "1.3.0rc0",
        "1.3.0rc1",
        "1.3.0rc2",
        "1.3.0",
        "1.4.0rc0",
        "1.4.0rc1",
        "1.4.0",
        "1.4.1",
        "1.5.0rc0",
        "1.5.0rc1",
        "1.5.0",
        "1.5.1",
        "1.6.0rc0",
        "1.6.0rc1",
        "1.6.0",
        "1.7.0rc0",
        "1.7.0rc1",
        "1.7.0",
        "1.7.1",
        "1.8.0rc0",
        "1.8.0rc1",
        "1.8.0",
        "1.9.0rc0",
        "1.9.0rc1",
        "1.9.0rc2",
        "1.9.0",
        "1.10.0rc0",
        "1.10.0rc1",
        "1.10.0",
        "1.10.1",
        "1.11.0rc0",
        "1.11.0rc1",
        "1.11.0rc2",
        "1.11.0",
        "1.12.0rc0",
        "1.12.0rc1",
        "1.12.0rc2",
        "1.12.0",
        "1.12.2",
        "1.12.3",
        "1.13.0rc0",
        "1.13.0rc1",
        "1.13.0rc2",
        "1.13.1",
        "1.13.2",
        "1.14.0rc0",
        "1.14.0rc1",
        "1.14.0",
        "1.15.0rc0",
        "1.15.0rc1",
        "1.15.0rc2",
        "1.15.0rc3",
        "1.15.0",
        "1.15.2",
        "1.15.3",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.1.0",
        "2.1.1",
        "2.2.0",
        "2.3.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15205",
    "GHSA-g7p5-5759-qv46"
  ],
  "details": "In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
  "id": "PYSEC-2020-128",
  "modified": "2020-10-29T16:15:00Z",
  "published": "2020-09-25T19:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ]
}

CVE-2020-15205 (GCVE-0-2020-15205)

Vulnerability from cvelistv5 – Published: 2020-09-25 18:45 – Updated: 2024-08-04 13:08

Title

Data leak in Tensorflow

Summary

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Severity

9 (Critical)


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

CWE

CWE-122 - {"CWE-122":"Heap-based Buffer Overflow"}
CWE-119 - {"CWE-119":"Improper Restriction of Operations within the Bounds of a Memory Buffer"}

Assigner

GitHub_M mitre root

References

4 references

URL	Tags
https://github.com/tensorflow/tensorflow/releases…	x_refsource_MISC
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/commit/0…	x_refsource_MISC
http://lists.opensuse.org/opensuse-security-annou…	vendor-advisoryx_refsource_SUSE

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: < 1.15.4 Affected: >= 2.0.0, < 2.0.3 Affected: >= 2.1.0, < 2.1.2 Affected: >= 2.2.0, < 2.2.1 Affected: >= 2.3.0, < 2.3.1

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-04T13:08:22.698Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
          },
          {
            "tags": [
              "x_refsource_CONFIRM",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80"
          },
          {
            "name": "openSUSE-SU-2020:1766",
            "tags": [
              "vendor-advisory",
              "x_refsource_SUSE",
              "x_transferred"
            ],
            "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "tensorflow",
          "vendor": "tensorflow",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 1.15.4"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.0.0, \u003c 2.0.3"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.1.0, \u003c 2.1.2"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.2.0, \u003c 2.2.1"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.3.0, \u003c 2.3.1"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 9,
            "baseSeverity": "CRITICAL",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "NONE",
            "scope": "CHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-122",
              "description": "{\"CWE-122\":\"Heap-based Buffer Overflow\"}",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-119",
              "description": "{\"CWE-119\":\"Improper Restriction of Operations within the Bounds of a Memory Buffer\"}",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2020-10-29T15:06:23.000Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
        },
        {
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46"
        },
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80"
        },
        {
          "name": "openSUSE-SU-2020:1766",
          "tags": [
            "vendor-advisory",
            "x_refsource_SUSE"
          ],
          "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
        }
      ],
      "source": {
        "advisory": "GHSA-g7p5-5759-qv46",
        "discovery": "UNKNOWN"
      },
      "title": "Data leak in Tensorflow",
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2020-15205",
          "STATE": "PUBLIC",
          "TITLE": "Data leak in Tensorflow"
        },
        "affects": {
          "vendor": {
            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "tensorflow",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "\u003c 1.15.4"
                          },
                          {
                            "version_value": "\u003e= 2.0.0, \u003c 2.0.3"
                          },
                          {
                            "version_value": "\u003e= 2.1.0, \u003c 2.1.2"
                          },
                          {
                            "version_value": "\u003e= 2.2.0, \u003c 2.2.1"
                          },
                          {
                            "version_value": "\u003e= 2.3.0, \u003c 2.3.1"
                          }
                        ]
                      }
                    }
                  ]
                },
                "vendor_name": "tensorflow"
              }
            ]
          }
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "eng",
              "value": "In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1."
            }
          ]
        },
        "impact": {
          "cvss": {
            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 9,
            "baseSeverity": "CRITICAL",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "NONE",
            "scope": "CHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H",
            "version": "3.1"
          }
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "{\"CWE-122\":\"Heap-based Buffer Overflow\"}"
                }
              ]
            },
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "{\"CWE-119\":\"Improper Restriction of Operations within the Bounds of a Memory Buffer\"}"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46",
              "refsource": "CONFIRM",
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80"
            },
            {
              "name": "openSUSE-SU-2020:1766",
              "refsource": "SUSE",
              "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
            }
          ]
        },
        "source": {
          "advisory": "GHSA-g7p5-5759-qv46",
          "discovery": "UNKNOWN"
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2020-15205",
    "datePublished": "2020-09-25T18:45:57.000Z",
    "dateReserved": "2020-06-25T00:00:00.000Z",
    "dateUpdated": "2024-08-04T13:08:22.698Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

GHSA-G7P5-5759-QV46

Vulnerability from github – Published: 2020-09-25 18:28 – Updated: 2024-10-30 21:11

Summary

Data leak in Tensorflow

Details

Impact

The data_splits argument of tf.raw_ops.StringNGrams lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory

>>> tf.raw_ops.StringNGrams(data=["aa", "bb", "cc", "dd", "ee", "ff"], data_splits=[0,8], separator=" ", ngram_widths=[3], left_pad="", right_pad="", pad_width=0, preserve_short_sequences=False)
StringNGrams(ngrams=<tf.Tensor: shape=(6,), dtype=string, numpy=
array([b'aa bb cc', b'bb cc dd', b'cc dd ee', b'dd ee ff',
       b'ee ff \xf4j\xa7q\x7f\x00\x00q\x00\x00\x00\x00\x00\x00\x00\xd8\x9b~\xa8q\x7f\x00',
       b'ff \xf4j\xa7q\x7f\x00\x00q\x00\x00\x00\x00\x00\x00\x00\xd8\x9b~\xa8q\x7f\x00 \x9b~\xa8q\x7f\x00\x00p\xf5j\xa7q\x7f\x00\x00H\xf8j\xa7q\x7f\x00\x00\xf0\xf3\xf7\x85q\x7f\x00\x00`}\xa6\x00\x00\x00\x00\x00`~\xa6\x00\x00\x00\x00\x00\xb0~\xeb\x9bq\x7f\x00'],...

All the binary strings after ee ff are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR.

Patches

We have patched the issue in 0462de5b544ed4731aa2fb23946ac22c01856b80 and will release patch releases for all versions between 1.15 and 2.3.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

For more information

Please consult our security guide 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.

Severity

9.0 (Critical)


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

6.5 (Medium)


                  
                    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15205"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119",
      "CWE-122",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-09-25T17:37:04Z",
    "nvd_published_at": "2020-09-25T19:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe `data_splits` argument of [`tf.raw_ops.StringNGrams`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/StringNGrams) lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory\n```python\n\u003e\u003e\u003e tf.raw_ops.StringNGrams(data=[\"aa\", \"bb\", \"cc\", \"dd\", \"ee\", \"ff\"], data_splits=[0,8], separator=\" \", ngram_widths=[3], left_pad=\"\", right_pad=\"\", pad_width=0, preserve_short_sequences=False)\nStringNGrams(ngrams=\u003ctf.Tensor: shape=(6,), dtype=string, numpy=\narray([b\u0027aa bb cc\u0027, b\u0027bb cc dd\u0027, b\u0027cc dd ee\u0027, b\u0027dd ee ff\u0027,\n       b\u0027ee ff \\xf4j\\xa7q\\x7f\\x00\\x00q\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xd8\\x9b~\\xa8q\\x7f\\x00\u0027,\n       b\u0027ff \\xf4j\\xa7q\\x7f\\x00\\x00q\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xd8\\x9b~\\xa8q\\x7f\\x00 \\x9b~\\xa8q\\x7f\\x00\\x00p\\xf5j\\xa7q\\x7f\\x00\\x00H\\xf8j\\xa7q\\x7f\\x00\\x00\\xf0\\xf3\\xf7\\x85q\\x7f\\x00\\x00`}\\xa6\\x00\\x00\\x00\\x00\\x00`~\\xa6\\x00\\x00\\x00\\x00\\x00\\xb0~\\xeb\\x9bq\\x7f\\x00\u0027],...\n```\n\nAll the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR.\n\n### Patches\nWe have patched the issue in 0462de5b544ed4731aa2fb23946ac22c01856b80 and will release patch releases for all versions between 1.15 and 2.3.\n\nWe recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.\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.",
  "id": "GHSA-g7p5-5759-qv46",
  "modified": "2024-10-30T21:11:46Z",
  "published": "2020-09-25T18:28:38Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g7p5-5759-qv46"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15205"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/0462de5b544ed4731aa2fb23946ac22c01856b80"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-285.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-320.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-128.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Data leak in Tensorflow"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

Action not permitted

PYSEC-2020-128

CVE-2020-15205 (GCVE-0-2020-15205)

GHSA-G7P5-5759-QV46

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature

Related by attack behaviour