Security readout for executives and security teams
Plain-English summary
CVE-2021-29617 is a low-severity TensorFlow denial-of-service issue. Invalid arguments to `tf.strings.substr` can trigger an internal CHECK failure and crash the process. It does not indicate data theft or code execution, but it can interrupt workloads that expose this function path to untrusted or low-privileged users.
Executive priority
Treat this as a routine patching item unless affected TensorFlow workloads are multi-tenant, user-facing, or business-critical. The business risk is service interruption, not data exposure or system takeover based on the provided evidence.
Technical view
The issue is classified as CWE-755 and affects TensorFlow versions before patched maintenance releases across 2.1, 2.2, 2.3, and 2.4. The CVSS 3.1 vector is local, high complexity, low privileges, no user interaction, unchanged scope, and low availability impact only.
Likely exposure
Exposure is most likely in ML applications, notebooks, batch jobs, or services using affected TensorFlow versions where a user can influence arguments passed to `tf.strings.substr`. Systems not using TensorFlow string substring operations have lower practical exposure.
Exploitation context
The provided sources do not show active exploitation, and the CVE is not listed as KEV. The issue requires local access or a local-equivalent application path with low privileges and invalid function arguments, resulting in process denial of service rather than compromise.
Researcher notes
The primary evidence is the TensorFlow advisory and linked fix commit. The vulnerability is a CHECK-fail denial of service caused by invalid arguments. Sources do not provide evidence of remote exploitation, weaponization, or impacts beyond availability.
Mitigation direction
- Upgrade TensorFlow to 2.5.0 or a patched maintenance release for your supported branch.
- Use TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4 where staying on those branches.
- Inventory containers, notebooks, CI images, and production ML runtimes for affected TensorFlow versions.
- Review vendor advisory guidance if an immediate upgrade is not possible.
- Restrict untrusted control over TensorFlow substring arguments until patched.
Validation and detection
- Check deployed TensorFlow versions against the affected version ranges in the advisory.
- Identify code paths that call `tf.strings.substr` with user-controlled inputs.
- Confirm upgraded environments use the patched branch versions or TensorFlow 2.5.0 or later.
- Review crash logs for TensorFlow CHECK failures involving string substring operations.
Public sources used
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Conservative CVE-to-ATT&CK context
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ATT&CK lookup starting points
Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.
CWE-755: Exact CWE lookup
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Open ATT&CK lookupCVE-2021-29617 mapping review
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Open ATT&CK lookup- Severity
- Low
- CVSS
- 2.5 (3.1)
- Known Exploited
- No
- Published
Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
CNA and ADP enrichment extracted from CVE v5
These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.
CVSS vector scores
1 official scoreWe collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L11.4Primary CVE scoreVulnerability scoring details
Base CVSS 3.1 score
2.5LowVector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Source materials
- CVE List V5 sourceCVE List V5
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mmq6-q8r3-48fmCVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/890f7164b70354c57d40eda52dcdd7658677c09fCVE reference · x_refsource_MISC
- https://github.com/tensorflow/issues/46900CVE reference · x_refsource_MISC
- https://github.com/tensorflow/issues/46974CVE reference · x_refsource_MISC
Products and packages named in the record
CWE details
CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.
Improper Handling of Exceptional Conditions
Improper Handling of Exceptional Conditions represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.