CVE intelligence and bounded remediation
CVE-2022-21732 — Tensorflow is an Open Source Machine Learning Framework
Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. 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.
- Severity
- Medium
- CVSS
- 6.5 (3.1)
- Published
- 2022-02-03
- CISA KEV
- Not currently listed
- Ecosystem
- software/application
- Weaknesses
- CWE-770
Affected products
- google / tensorflow
- google / tensorflow / 2.7.0
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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