CVE-2025-3933: Transformers: ReDoS in DonutProcessor causes DoS
GHSA-37mw-44qp-f5jmMEDIUMPoC AVAILABLECISA: TRACK*If your document-processing pipelines use Hugging Face Transformers' Donut model (DonutProcessor), upgrade to 4.52.1 now. This is network-exploitable with zero authentication required, making any public-facing endpoint using this processor a trivial DoS target. Impact is availability-only—no data leakage—but service disruption requires minimal attacker skill.
What is the risk?
Moderate operational risk despite low CVSS (5.3). The attack profile is highly favorable for adversaries: AV:N/AC:L/PR:N/UI:N means zero friction to exploit remotely. However, blast radius is scoped to services specifically using DonutProcessor for document understanding tasks. EPSS of 0.00035 reflects low real-world exploitation today, but any public API endpoint accepting unvalidated document input is a standing target. Cloud-hosted document processing workloads face secondary cost-exhaustion risk.
What systems are affected?
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| Transformers | pip | — | No patch |
| Transformers | pip | <= 4.51.3 | 4.52.1 |
How severe is it?
What is the attack surface?
What should I do?
6 stepsPATCH
Upgrade transformers to >= 4.52.1 across all environments.
AUDIT
Enumerate affected deployments with
pip show transformersor lockfile scanning in CI/CD.WORKAROUND (pre-patch): Add input length caps and strip/reject tag-pattern inputs before passing to DonutProcessor.
HARDEN
Enforce rate limiting and request timeouts on document ingestion endpoints.
MONITOR
Alert on sustained CPU spikes in document-processing workers as a detection signal.
SBOM
If you maintain a software bill of materials for AI components, flag this dependency version for remediation tracking.
What does CISA's SSVC say?
Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.
How is it classified?
Which compliance frameworks are affected?
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2025-3933?
If your document-processing pipelines use Hugging Face Transformers' Donut model (DonutProcessor), upgrade to 4.52.1 now. This is network-exploitable with zero authentication required, making any public-facing endpoint using this processor a trivial DoS target. Impact is availability-only—no data leakage—but service disruption requires minimal attacker skill.
Is CVE-2025-3933 actively exploited?
Proof-of-concept exploit code is publicly available for CVE-2025-3933, increasing the risk of exploitation.
How to fix CVE-2025-3933?
1. PATCH: Upgrade transformers to >= 4.52.1 across all environments. 2. AUDIT: Enumerate affected deployments with `pip show transformers` or lockfile scanning in CI/CD. 3. WORKAROUND (pre-patch): Add input length caps and strip/reject tag-pattern inputs before passing to DonutProcessor. 4. HARDEN: Enforce rate limiting and request timeouts on document ingestion endpoints. 5. MONITOR: Alert on sustained CPU spikes in document-processing workers as a detection signal. 6. SBOM: If you maintain a software bill of materials for AI components, flag this dependency version for remediation tracking.
What systems are affected by CVE-2025-3933?
This vulnerability affects the following AI/ML architecture patterns: document processing pipelines, model serving, OCR and document understanding systems.
What is the CVSS score for CVE-2025-3933?
CVE-2025-3933 has a CVSS v3.1 base score of 5.3 (MEDIUM). The EPSS exploitation probability is 0.50%.
What is the AI security impact?
Affected AI Architectures
MITRE ATLAS Techniques
AML.T0010.001AI SoftwareAML.T0029Denial of AI ServiceAML.T0034Cost HarvestingAML.T0049Exploit Public-Facing ApplicationCompliance Controls Affected
What are the technical details?
Original Advisory
A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically within the DonutProcessor class's `token2json()` method. This vulnerability affects versions 4.50.3 and earlier, and is fixed in version 4.52.1. The issue arises from the regex pattern `<s_(.*?)>` which can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. This vulnerability can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting document processing tasks using the Donut model.
Exploitation Scenario
Attacker identifies a public document-processing API (invoice digitizer, form parser) running HF Transformers <= 4.51.3. Crafts a malicious payload that, when processed by the Donut model, generates deeply nested tag sequences (e.g., `<s_a<s_a<s_a...>`) in the model output. The `token2json()` regex `<s_(.*?)>` undergoes catastrophic backtracking against this input, pinning a CPU core at near-100% for multiple seconds per request. Attacker sends 20-50 concurrent requests via a script, causing full service unavailability or triggering auto-scaling cost explosion in cloud environments. No authentication, no ML knowledge, and no model access required—only a crafted HTTP POST.
Weaknesses (CWE)
CWE-1333Inefficient Regular Expression ComplexityPrimaryCWE-1333Inefficient Regular Expression ComplexityCWE-1333 — Inefficient Regular Expression Complexity: The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.
- [Architecture and Design] Use regular expressions that do not support backtracking, e.g. by removing nested quantifiers.
- [System Configuration] Set backtracking limits in the configuration of the regular expression implementation, such as PHP's pcre.backtrack_limit. Also consider limits on execution time for the process.
Source: MITRE CWE corpus.
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:LReferences
Timeline
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