GHSA-phhr-52qp-3mj4 CVE-2025-3777 PYSEC-2026-1986
Transformers's Improper Input Validation vulnerability can be exploited through username injection
Low
PyPI
- Severity
- 3.5 / 10
- Low · CVSS 3.0
- Exploit chance (EPSS)
- 0.41%
- Chance of exploitation in the next 30 days. Higher than 34.92% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-20 Improper Input Validation
- Fix
4.52.1- Upgrade transformers to this version or later
Description
Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the image_utils.py file. The vulnerability arises from insecure URL validation using the startswith() method, which can be bypassed through URL username injection. This allows attackers to craft URLs that appear to be from YouTube but resolve to malicious domains, potentially leading to phishing attacks, malware distribution, or data exfiltration. The issue is fixed in version 4.52.1.
Affected versions
PyPI
| Package | Vulnerable | Fixed in |
|---|---|---|
| transformers | < 4.52.1 |
4.52.1 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
transformers PyPI → 4.52.1
- pip
pip install --upgrade "transformers>=4.52.1"- poetry
poetry add "transformers>=4.52.1"- uv
uv add "transformers>=4.52.1"
Severity breakdown
CVSS 3.0 3.5
CVSS:3.0/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:N/A:N
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- Low
- User interaction
- Required
- Scope
- Unchanged
- Confidentiality
- Low
- Integrity
- None
- Availability
- None
Weakness
CWE-20: Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
How to prevent it
- Architecture and Design: Consider using language-theoretic security (LangSec) techniques that characterize inputs using a formal language and build "recognizers" for that language. This effectively requires parsing to be a distinct layer that effectively enforces a boundary between raw input and internal data representations, instead of allowing parser code to be scattered throughout the program, where it could be subject to errors or inconsistencies that create weaknesses. [REF-1109] [REF-1110] [REF-1111]
- Architecture and Design: Use an input validation framework such as Struts or the OWASP ESAPI Validation API. Note that using a framework does not automatically address all input validation problems; be mindful of weaknesses that could arise from misusing the framework itself (CWE-1173).
- Architecture and Design, Implementation: Understand all the potential areas where untrusted inputs can enter the product, including but not limited to: parameters or arguments, cookies, anything read from the network, environment variables, reverse DNS lookups, query results, request headers, URL components, e-mail, files, filenames, databases, and any external systems that provide data to the application. Remember that such inputs may be obtained indirectly through API calls.
- Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
- Architecture and Design: For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server. Even though client-side checks provide minimal benefits with respect to server-side security, they are still useful. First, they can support intrusion detection. If the server receives input that should have been rejected by the client, then it may be an indication of an attack. Second, client-side error-checking can provide helpful feedback to the user about the expectations for valid input. Third, there may be a reduction in server-side processing time for accidental input errors, although this is typically a small savings.
- Implementation: When your application combines data from multiple sources, perform the validation after the sources have been combined. The individual data elements may pass the validation step but violate the intended restrictions after they have been combined.
- Implementation: Be especially careful to validate all input when invoking code that crosses language boundaries, such as from an interpreted language to native code. This could create an unexpected interaction between the language boundaries. Ensure that you are not violating any of the expectations of the language with which you are interfacing. For example, even though Java may not be susceptible to buffer overflows, providing a large argument in a call to native code might trigger an overflow.
- Implementation: Directly convert your input type into the expected data type, such as using a conversion function that translates a string into a number. After converting to the expected data type, ensure that the input's values fall within the expected range of allowable values and that multi-field consistencies are maintained.
- Implementation: Inputs should be decoded and canonicalized to the application's current internal representation before being validated (CWE-180, CWE-181). Make sure that your application does not inadvertently decode the same input twice (CWE-174). Such errors could be used to bypass allowlist schemes by introducing dangerous inputs after they have been checked. Use libraries such as the OWASP ESAPI Canonicalization control. Consider performing repeated canonicalization until your input does not change any more. This will avoid double-decoding and similar scenarios, but it might inadvertently modify inputs that are allowed to contain properly-encoded dangerous content.
- Implementation: When exchanging data between components, ensure that both components are using the same character encoding. Ensure that the proper encoding is applied at each interface. Explicitly set the encoding you are using whenever the protocol allows you to do so.
References
Advisories
Packages
Other links
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-x9r9-c232-4q39 Hugging Face Transformers downloads custom generation code before trust consent | High | Also affects transformers |
| GHSA-xrqw-3rrv-vx5w Transformers save_pretrained path traversal allows arbitrary file writes through chat template names | High | Also affects transformers |
| GHSA-fgcw-684q-jj6r huggingface/transformers: Arbitrary Code Execution During Model Initialization in the LightGlue Model Loading Path | Critical | Also affects transformers |
| GHSA-29pf-2h5f-8g72 HuggingFace transformers vulnerable to remote code execution | High | Also affects transformers |
| GHSA-69w3-r845-3855 HuggingFace Transformers allows for arbitrary code execution in the `Trainer` class | High | Also affects transformers |
| PYSEC-2025-218 Hugging Face Transformers GLM4 Deserialization of Untrusted Data Remote Code Execution Vulnerability. | High | Also affects transformers |
| PYSEC-2025-217 Hugging Face Transformers X-CLIP Checkpoint Conversion Deserialization of Untrusted Data Remote Code Execution Vulnerability. | High | Also affects transformers |
| PYSEC-2025-216 Hugging Face Transformers HuBERT convert_config Code Injection Remote Code Execution Vulnerability. | High | Also affects transformers |
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