CVE intelligence and bounded remediation

CVE-2020-5215 — Google Tensorflow security vulnerability

High CVSS 7.5

In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant("hello", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.

Severity
High
CVSS
7.5 (3.1)
Published
2020-01-28
CISA KEV
Not currently listed
Ecosystem
python/pypi
Weaknesses
CWE-754, CWE-20

Affected products

  • google / tensorflow

Showing 1 representative product identities from 2 source matches. Confirm exact affected versions with the linked vendor and NVD evidence.

Matched remediation archetype

Resource exhaustion and denial of service

This catalog composition supplies bounded fallback guidance. Explicitly reviewed curated workflows load with the complete record below.

Check exposure

  • Identify attacker-influenced work factors including input size, nesting, compression, fan-out, regex cost, allocation, recursion, retries, and connection lifetime.
  • Map per-request and shared CPU, memory, disk, descriptor, thread, queue, and downstream-service limits.
  • Determine whether authentication, tenancy, quotas, and rate controls apply before expensive processing begins.

Remediate safely

  • Bound input size, nesting, expansion, work, concurrency, queue depth, retries, and execution time before resource-intensive processing.
  • Release resources on every success, error, cancellation, and timeout path and use backpressure instead of unbounded buffering.
  • Update affected components and add small deterministic tests that assert resource ceilings rather than exhausting a host.

Authoritative sources

Complete CVE record and remediation plan

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