Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessAttacker crafts malicious checkpoint index file
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DeliveryPublishes or delivers checkpoint to target environment
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ExploitVictim loads checkpoint via Transformers API
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ExecutionLibrary joins unsanitised shard path to model directory
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PersistTraversal resolves to arbitrary host filesystem path
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ImpactTargeted file contents disclosed to attacker
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V5 - File Handling Path canonicalization, traversal prevention
MITRE ATT&CK
2 techniques across 2 tactics: Discovery, Collection The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Exploitation requires that a victim uses the Hugging Face Transformers library to load a checkpoint whose index file was supplied or influenced by the attacker - either by downloading a malicious model from the Hub, receiving an archive from an untrusted source, or processing user-submitted model uploads in an application. The CVSS 4.0 vector UI:P confirms that user interaction (the act of loading the checkpoint) is mandatory; there is no remote network-reachable attack surface in the library itself. AV:L indicates the attack is local in the CVSS sense, meaning the attacker's malicious artifact must reach the local filesystem or be directly passed to the loader. Exploitation is limited by: (1) the victim must actively load a checkpoint from an untrusted source; (2) the process running the loader must have read access to the targeted files - privileged files such as /etc/shadow are inaccessible if inference runs as an unprivileged user; and (3) the attacker must know or guess valid absolute paths or traversal sequences to targeted files on the host. |
| Impact | The CVSS 4.0 vector (AV:L/AC:L/AT:N/PR:N/UI:P/VC:H) assigns high confidentiality impact but scopes the attack as local with user interaction required, reflecting that the attacker must deliver a malicious checkpoint that the victim actively loads rather than exploiting a remotely reachable network service. Attack complexity is low once a malicious checkpoint is placed or distributed, and no privileges are required of the attacker. EPSS data was not provided in the intelligence package, which is a gap worth noting; however, the supply-chain distribution model for ML models - where practitioners routinely download and load checkpoints from the Hugging Face Hub or third-party sources - substantially lowers the practical delivery barrier and means even a mid-sized municipal IT team in opole running local inference pipelines should treat this as a meaningful risk if models are sourced outside curated internal registries. There is no KEV listing and no confirmed public exploit, suggesting exploitation is not yet widespread, but the attack primitive is simple and the potential exposure of credentials, SSH keys, and configuration files on inference servers makes this a genuine priority for teams consuming untrusted model artifacts. The wildcard CPE version range means no version of Transformers has been confirmed as patched in the available data. |
| Exploit ScenarioDerived | An attacker publishes a model on the Hugging Face Hub or distributes a checkpoint archive containing an index file with shard entries such as '../../../etc/ssl/private/server.key'. When a developer or automated CI pipeline downloads and loads this model using the standard Transformers API (e.g., AutoModel.from_pretrained), the library resolves these crafted paths and opens the referenced files outside the model directory, disclosing their contents. No public exploit code has been confirmed, but the attack primitive requires only a text-editor and knowledge of the index file format. |
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Alert meAnalysisAIv1 – Aug 17, 2026
Arbitrary file read in Hugging Face Transformers allows an attacker who controls a model checkpoint index file to exfiltrate files from the host filesystem outside the intended model directory. The library fails to sanitize shard filenames in checkpoint index files before joining them to directory paths, meaning maliciously crafted entries containing parent-directory sequences or absolute paths resolve to unintended locations. Any user or automated pipeline that loads an attacker-supplied checkpoint - for example, by downloading a model from an untrusted Hub repository - can have host files disclosed without code execution. No public exploit has been identified at time of analysis, and the vulnerability is not listed in CISA KEV.
RemediationAI
No vendor-released patch with a confirmed fixed version was identified at time of analysis. The upstream disclosure references (https://github.com/huggingface/transformers/issues/47176 and https://github.com/huggingface/transformers/issues/47177) and the repository root (https://github.com/huggingface/transformers) should be monitored for a tagged release containing a fix; the vulnerable logic in src/transformers/utils/hub.py (https://github.com/huggingface/transformers/blob/main/src/transformers/utils/hub.py) is the focal point for any upstream patch. Until a patched release is available, the most actionable compensating control is to restrict model loading exclusively to checkpoints sourced from internally vetted or cryptographically signed repositories and to prohibit loading of index files from untrusted or public Hub namespaces without manual review. Operators running inference servers should also apply filesystem-level sandboxing - for example, running the inference process under a user with read access limited to the model directory tree using Linux namespace mounts or a seccomp/AppArmor profile - to limit the blast radius of a successful traversal. Note that path-based sandboxing at the OS level does not fix the vulnerability but substantially reduces what an attacker can read.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
Hugging Face Transformers (CPE: cpe:2.3:a:huggingface:transformers:*:*:*:*:*:*:*:*) uses checkpoint index files (e.g., pytorch_model.bin.index.json or safetensors index JSON) to enumerate model weight shard filenames, which are then loaded from disk. The vulnerable code path, identifiable in src/transformers/utils/hub.py per the references, performs a path join between the resolved checkpoint directory and the shard filenames extracted from the index file without applying CWE-22-class sanitisation - specifically, it does not strip leading slashes, canonicalise the result, or verify the resolved path remains under the model directory. An attacker who publishes or supplies a model with a crafted index file can embed entries such as '../../etc/passwd' or '/etc/shadow', causing the loader to open files at those absolute or relative-escaped paths and either return their contents or expose them through error messages or logging.
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Severity by source
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N
Local attack vector and required user interaction (loading a checkpoint) confirmed by description; no privileges needed from attacker; confidentiality-only impact with no integrity or availability effect.
Primary rating from Vendor (VulnCheck).
CVSS VectorVendor: VulnCheck
DescriptionCVE.org
Hugging Face Transformers fails to validate shard filenames in checkpoint index files, allowing attackers to read arbitrary files outside the model directory. Attackers can supply malicious index files with parent-directory references or absolute paths that are joined without validation, enabling file disclosure and filesystem reconnaissance.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Path traversal exploits occur when applications use user-controlled input to construct file system paths without proper validation.
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