Summary
CHECK-fail in CTCGreedyDecoder
For more information
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Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.
Impact
An attacker can trigger a denial of service via a CHECK-fail in tf.raw_ops.CTCGreedyDecoder:
import tensorflow as tf
inputs = tf.constant([], shape=[18, 2, 0], dtype=tf.float32)
sequence_length = tf.constant([-100, 17], shape=[2], dtype=tf.int32)
merge_repeated = False
tf.raw_ops.CTCGreedyDecoder(inputs=inputs, sequence_length=sequence_length, merge_repeated=merge_repeated)
This is because the implementation has a CHECK_LT inserted to validate some invariants. When this condition is false, the program aborts, instead of returning a valid error to the user. This abnormal termination can be weaponized in denial of service attacks.
CVE-2021-29543 has a CVSS score of 2.5 (Low). The vector is requires local access, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (2.1.4, 2.2.3, 2.3.3, 2.4.2); upgrading removes the vulnerable code path.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
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We have patched the issue in GitHub commit ea3b43e98c32c97b35d52b4c66f9107452ca8fb2.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Frequently Asked Questions
- What is CVE-2021-29543? CVE-2021-29543 is a low-severity security vulnerability in tensorflow (pip), affecting versions < 2.1.4. It is fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2.
- How severe is CVE-2021-29543? CVE-2021-29543 has a CVSS score of 2.5 (Low). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
- Which packages are affected by CVE-2021-29543?
tensorflow(pip) (versions < 2.1.4)tensorflow-cpu(pip) (versions < 2.1.4)tensorflow-gpu(pip) (versions < 2.1.4)
- Is there a fix for CVE-2021-29543? Yes. CVE-2021-29543 is fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade to this version or later.
- Is CVE-2021-29543 exploitable, and should I be worried? Whether CVE-2021-29543 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
- What actually determines whether CVE-2021-29543 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
- How do I fix CVE-2021-29543?
- Upgrade
tensorflowto 2.1.4 or later - Upgrade
tensorflowto 2.2.3 or later - Upgrade
tensorflowto 2.3.3 or later - Upgrade
tensorflowto 2.4.2 or later - Upgrade
tensorflow-cputo 2.1.4 or later - Upgrade
tensorflow-cputo 2.2.3 or later - Upgrade
tensorflow-cputo 2.3.3 or later - Upgrade
tensorflow-cputo 2.4.2 or later - Upgrade
tensorflow-gputo 2.1.4 or later - Upgrade
tensorflow-gputo 2.2.3 or later - Upgrade
tensorflow-gputo 2.3.3 or later - Upgrade
tensorflow-gputo 2.4.2 or later
- Upgrade