ghsa-8h46-5m9h-7553
Vulnerability from github
Impact
If the splits
argument of RaggedBincount
does not specify a valid SparseTensor
, then an attacker can trigger a heap buffer overflow:
python
import tensorflow as tf
tf.raw_ops.RaggedBincount(splits=[7,8], values= [5, 16, 51, 76, 29, 27, 54, 95],\
size= 59, weights= [0, 0, 0, 0, 0, 0, 0, 0],\
binary_output=False)
This will cause a read from outside the bounds of the splits
tensor buffer in the implementation of the RaggedBincount
op:
cc
for (int idx = 0; idx < num_values; ++idx) {
while (idx >= splits(batch_idx)) {
batch_idx++;
}
...
if (bin < size) {
if (binary_output_) {
out(batch_idx - 1, bin) = T(1);
} else {
T value = (weights_size > 0) ? weights(idx) : T(1);
out(batch_idx - 1, bin) += value;
}
}
}
Before the for
loop, batch_idx
is set to 0. The attacker sets splits(0)
to be 7, hence the while
loop does not execute and batch_idx
remains 0. This then results in writing to out(-1, bin)
, which is before the heap allocated buffer for the output tensor.
Patches
We have patched the issue in GitHub commit eebb96c2830d48597d055d247c0e9aebaea94cd5.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected.
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": "2.3.0" }, { "fixed": "2.3.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.4.0" }, { "fixed": "2.4.2" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.3.0" }, { "fixed": "2.3.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.4.0" }, { "fixed": "2.4.2" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.3.0" }, { "fixed": "2.3.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.4.0" }, { "fixed": "2.4.2" } ], "type": "ECOSYSTEM" } ] } ], "aliases": [ "CVE-2021-29514" ], "database_specific": { "cwe_ids": [ "CWE-787" ], "github_reviewed": true, "github_reviewed_at": "2021-05-18T23:40:54Z", "nvd_published_at": "2021-05-14T20:15:00Z", "severity": "LOW" }, "details": "### Impact\nIf the `splits` argument of `RaggedBincount` does not specify a valid [`SparseTensor`](https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow:\n\n```python\nimport tensorflow as tf\ntf.raw_ops.RaggedBincount(splits=[7,8], values= [5, 16, 51, 76, 29, 27, 54, 95],\\\n size= 59, weights= [0, 0, 0, 0, 0, 0, 0, 0],\\\n binary_output=False)\n```\n\nThis will cause a read from outside the bounds of the `splits` tensor buffer in the [implementation of the `RaggedBincount` op](https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L446):\n \n```cc \n for (int idx = 0; idx \u003c num_values; ++idx) {\n while (idx \u003e= splits(batch_idx)) {\n batch_idx++;\n }\n ...\n if (bin \u003c size) {\n if (binary_output_) {\n out(batch_idx - 1, bin) = T(1);\n } else {\n T value = (weights_size \u003e 0) ? weights(idx) : T(1);\n out(batch_idx - 1, bin) += value;\n }\n } \n }\n```\n\nBefore the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. This then results in writing to `out(-1, bin)`, which is before the heap allocated buffer for the output tensor.\n\n### Patches\nWe have patched the issue in GitHub commit [eebb96c2830d48597d055d247c0e9aebaea94cd5](https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected.\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-8h46-5m9h-7553", "modified": "2024-10-30T21:30:51Z", "published": "2021-05-21T14:20:51Z", "references": [ { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8h46-5m9h-7553" }, { "type": "ADVISORY", "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29514" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-442.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-640.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-151.yaml" }, { "type": "PACKAGE", "url": "https://github.com/tensorflow/tensorflow" } ], "schema_version": "1.4.0", "severity": [ { "score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", "type": "CVSS_V3" }, { "score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:P/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N", "type": "CVSS_V4" } ], "summary": "Heap out of bounds write in `RaggedBinCount`" }
Sightings
Author | Source | Type | Date |
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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.