CVE intelligence and bounded remediation

CVE-2021-29531 — TensorFlow is an end-to-end open source platform for machine learning

Medium CVSS 5.5

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when calling `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the first line of `png::WriteImageToBuffer`(https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service at…

Severity
Medium
CVSS
5.5 (3.1)
Published
2021-05-14
CISA KEV
Not currently listed
Ecosystem
software/application
Weaknesses
CWE-754

Affected products

  • google / tensorflow

Showing 1 representative product identities from 4 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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