Ecosyste.ms: Advisories

Security Advisories: GSA_kwCzR0hTQS02Z212LXBqcDktcDh3OM0obg

Out of bounds read in Tensorflow

Impact

The implementation of shape inference for ReverseSequence does not fully validate the value of batch_dim and can result in a heap OOB read:

import tensorflow as tf

@tf.function
def test():
  y = tf.raw_ops.ReverseSequence(
    input = ['aaa','bbb'],
    seq_lengths = [1,1,1],
    seq_dim = -10,
    batch_dim = -10 )
  return y
    
test()

There is a check to make sure the value of batch_dim does not go over the rank of the input, but there is no check for negative values:

  const int32_t input_rank = c->Rank(input);
  if (batch_dim >= input_rank) {
    return errors::InvalidArgument( 
        "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank);
  }
  // ...
  
  DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);

Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of Dim would access elements before the start of an array:

  DimensionHandle Dim(ShapeHandle s, int64_t idx) {
    if (!s.Handle() || s->rank_ == kUnknownRank) {
      return UnknownDim();
    }
    return DimKnownRank(s, idx);
  } 
·
  static DimensionHandle DimKnownRank(ShapeHandle s, int64_t idx) {
    CHECK_NE(s->rank_, kUnknownRank);
    if (idx < 0) {
      return s->dims_[s->dims_.size() + idx];
    }
    return s->dims_[idx];
  }

Patches

We have patched the issue in GitHub commit 37c01fb5e25c3d80213060460196406c43d31995.

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.

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 Yu Tian of Qihoo 360 AIVul Team.

Permalink: https://github.com/advisories/GHSA-6gmv-pjp9-p8w8
JSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS02Z212LXBqcDktcDh3OM0obg
Source: GitHub Advisory Database
Origin: Unspecified
Severity: High
Classification: General
Published: about 2 years ago
Updated: about 1 year ago

CVSS Score: 8.1
CVSS vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H

Identifiers: GHSA-6gmv-pjp9-p8w8, CVE-2022-21728
References:

• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8
• https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995
• https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428
• https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671
• https://nvd.nist.gov/vuln/detail/CVE-2022-21728
• https://github.com/advisories/GHSA-6gmv-pjp9-p8w8

Repository: https://github.com/tensorflow/tensorflow
Blast Radius: 39.4

Affected Packages