ghsa-g7p5-5759-qv46
Vulnerability from github
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
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
```python
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.
{ "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 |
---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.