Vulnerable Library - sentence_transformers-2.5.1-py3-none-any.whl
Multilingual text embeddings
Library home page: https://files.pythonhosted.org/packages/68/0d/27475988a3daade7516ea02dbc607b57d4a30f01bb49614a6430e76685c2/sentence_transformers-2.5.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/sentence_transformers-2.5.1.dist-info
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Vulnerabilities
*For some transitive vulnerabilities, there is no version of direct dependency with a fix. Check the "Details" section below to see if there is a version of transitive dependency where vulnerability is fixed.
**In some cases, Remediation PR cannot be created automatically for a vulnerability despite the availability of remediation
Details
Partial details (15 vulnerabilities) are displayed below due to a content size limitation in GitHub. To view information on the remaining vulnerabilities, navigate to the Mend Application.
CVE-2026-68770
Vulnerable Library - sentence_transformers-2.5.1-py3-none-any.whl
Multilingual text embeddings
Library home page: https://files.pythonhosted.org/packages/68/0d/27475988a3daade7516ea02dbc607b57d4a30f01bb49614a6430e76685c2/sentence_transformers-2.5.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/sentence_transformers-2.5.1.dist-info
Dependency Hierarchy:
- ❌ sentence_transformers-2.5.1-py3-none-any.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
This vulnerability is potentially reachable
AutoPrompt/utils/dedup.py (Application)
-> sentence_transformers-2.5.1/sentence_transformers/SentenceTransformer.py (Extension)
-> ❌ sentence_transformers-2.5.1/sentence_transformers/models/Transformer.py (Vulnerable Component)
Vulnerability Details
sentence-transformers contains a security control bypass vulnerability that allows attackers to achieve arbitrary code execution by exploiting a logic flaw in the import_module_class helper within sentence_transformers/util/misc.py, where the guard condition includes an 'or os.path.exists(model_name_or_path)' clause that satisfies the trust gate whenever the supplied path exists on the local filesystem, regardless of the trust_remote_code=False argument. Attackers who can control or influence the contents of a model directory on disk can place malicious Python files such as modeling_*.py referenced via modules.json, causing the code to execute at import time when an application loads the model with SentenceTransformer(path, trust_remote_code=False), bypassing the documented security contract and achieving code execution within the loading process.
Publish Date: 2026-07-31
URL: CVE-2026-68770
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.521%
CVSS 3 Score Details (9.8)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2026-07-31
Fix Resolution: 5.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-32434
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.
Publish Date: 2025-04-18
URL: CVE-2025-32434
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 1.94%
CVSS 3 Score Details (9.8)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Origin: GHSA-53q9-r3pm-6pq6
Release Date: 2025-04-18
Fix Resolution: pytorch - 2.6.0,https://github.com/pytorch/pytorch.git - v2.6.0,pytorch - 2.6.0
CVE-2026-24747
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's "weights_only" unpickler allows an attacker to craft a malicious checkpoint file (".pth") that, when loaded with "torch.load(..., weights_only=True)", can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.
Publish Date: 2026-01-27
URL: CVE-2026-24747
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.706%
CVSS 3 Score Details (8.8)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2026-01-27
Fix Resolution (torch): 2.10.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-55560
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
An issue in pytorch v2.7.0 can lead to a Denial of Service (DoS) when a PyTorch model consists of torch.Tensor.to_sparse() and torch.Tensor.to_dense() and is compiled by Inductor.
Publish Date: 2025-09-25
URL: CVE-2025-55560
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.411%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-55558
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tensor.view-torch.mv() and is compiled by Inductor, leading to a Denial of Service (DoS).
Publish Date: 2025-09-25
URL: CVE-2025-55558
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.454%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-55557
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A Name Error occurs in pytorch v2.7.0 when a PyTorch model consists of torch.cummin and is compiled by Inductor, leading to a Denial of Service (DoS).
Publish Date: 2025-09-25
URL: CVE-2025-55557
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.408%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-55553
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).
Publish Date: 2025-09-25
URL: CVE-2025-55553
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.408%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-55551
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
An issue in the component torch.linalg.lu of pytorch v2.8.0 allows attackers to cause a Denial of Service (DoS) when performing a slice operation.
Publish Date: 2025-09-25
URL: CVE-2025-55551
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.423%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.9.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2024-56326
Vulnerable Library - Jinja2-3.1.3-py3-none-any.whl
A very fast and expressive template engine.
Library home page: https://files.pythonhosted.org/packages/30/6d/6de6be2d02603ab56e72997708809e8a5b0fbfee080735109b40a3564843/Jinja2-3.1.3-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/Jinja2-3.1.3.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
- ❌ Jinja2-3.1.3-py3-none-any.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
Jinja is an extensible templating engine. Prior to 3.1.5, An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox. This vulnerability is fixed in 3.1.5.
Publish Date: 2024-12-23
URL: CVE-2024-56326
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.521%
CVSS 3 Score Details (7.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: Low
- Privileges Required: Low
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Origin: GHSA-q2x7-8rv6-6q7h
Release Date: 2024-12-23
Fix Resolution (Jinja2): 3.1.5
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2024-56201
Vulnerable Library - Jinja2-3.1.3-py3-none-any.whl
A very fast and expressive template engine.
Library home page: https://files.pythonhosted.org/packages/30/6d/6de6be2d02603ab56e72997708809e8a5b0fbfee080735109b40a3564843/Jinja2-3.1.3-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/Jinja2-3.1.3.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
- ❌ Jinja2-3.1.3-py3-none-any.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
Jinja is an extensible templating engine. In versions on the 3.x branch prior to 3.1.5, a bug in the Jinja compiler allows an attacker that controls both the content and filename of a template to execute arbitrary Python code, regardless of if Jinja's sandbox is used. To exploit the vulnerability, an attacker needs to control both the filename and the contents of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates where the template author can also choose the template filename. This vulnerability is fixed in 3.1.5.
Publish Date: 2024-12-23
URL: CVE-2024-56201
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.307%
CVSS 3 Score Details (7.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: Low
- Privileges Required: Low
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Origin: GHSA-gmj6-6f8f-6699
Release Date: 2024-12-23
Fix Resolution (Jinja2): 3.1.5
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-68146
Vulnerable Library - filelock-3.13.1-py3-none-any.whl
A platform independent file lock.
Library home page: https://files.pythonhosted.org/packages/81/54/84d42a0bee35edba99dee7b59a8d4970eccdd44b99fe728ed912106fc781/filelock-3.13.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/filelock-3.13.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
- ❌ filelock-3.13.1-py3-none-any.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
filelock is a platform-independent file lock for Python. In versions prior to 3.20.1, a Time-of-Check-Time-of-Use (TOCTOU) race condition allows local attackers to corrupt or truncate arbitrary user files through symlink attacks. The vulnerability exists in both Unix and Windows lock file creation where filelock checks if a file exists before opening it with O_TRUNC. An attacker can create a symlink pointing to a victim file in the time gap between the check and open, causing os.open() to follow the symlink and truncate the target file. All users of filelock on Unix, Linux, macOS, and Windows systems are impacted. The vulnerability cascades to dependent libraries. The attack requires local filesystem access and ability to create symlinks (standard user permissions on Unix; Developer Mode on Windows 10+). Exploitation succeeds within 1-3 attempts when lock file paths are predictable. The issue is fixed in version 3.20.1. If immediate upgrade is not possible, use SoftFileLock instead of UnixFileLock/WindowsFileLock (note: different locking semantics, may not be suitable for all use cases); ensure lock file directories have restrictive permissions (chmod 0700) to prevent untrusted users from creating symlinks; and/or monitor lock file directories for suspicious symlinks before running trusted applications. These workarounds provide only partial mitigation. The race condition remains exploitable. Upgrading to version 3.20.1 is strongly recommended.
Publish Date: 2025-12-16
URL: CVE-2025-68146
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.201%
CVSS 3 Score Details (6.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: High
- Privileges Required: Low
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2025-12-16
Fix Resolution (filelock): 3.20.1
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2024-35195
Vulnerable Library - requests-2.31.0-py3-none-any.whl
Python HTTP for Humans.
Library home page: https://files.pythonhosted.org/packages/70/8e/0e2d847013cb52cd35b38c009bb167a1a26b2ce6cd6965bf26b47bc0bf44/requests-2.31.0-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/requests-2.31.0.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- huggingface_hub-0.21.4-py3-none-any.whl
- ❌ requests-2.31.0-py3-none-any.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
Requests is a HTTP library. Prior to 2.32.0, when making requests through a Requests "Session", if the first request is made with "verify=False" to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of "verify". This behavior will continue for the lifecycle of the connection in the connection pool. This vulnerability is fixed in 2.32.0.
Mend Note: The description of this vulnerability differs from MITRE.
Publish Date: 2024-05-20
URL: CVE-2024-35195
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.34%
CVSS 3 Score Details (5.6)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: High
- Privileges Required: High
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: None
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Origin: GHSA-9wx4-h78v-vm56
Release Date: 2024-05-20
Fix Resolution (requests): 2.32.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2026-4538
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A vulnerability was identified in PyTorch 2.10.0. The affected element is an unknown function of the component pt2 Loading Handler. The manipulation leads to deserialization. The attack can only be performed from a local environment. The exploit is publicly available and might be used. The project was informed of the problem early through a pull request but has not reacted yet.
Publish Date: 2026-03-22
URL: CVE-2026-4538
Threat Assessment
Exploit Maturity: Proof of concept
EPSS: 0.239%
CVSS 3 Score Details (5.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: Low
- Privileges Required: Low
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: Low
- Integrity Impact: Low
- Availability Impact: Low
For more information on CVSS3 Scores, click here.
CVE-2026-22701
Vulnerable Library - filelock-3.13.1-py3-none-any.whl
A platform independent file lock.
Library home page: https://files.pythonhosted.org/packages/81/54/84d42a0bee35edba99dee7b59a8d4970eccdd44b99fe728ed912106fc781/filelock-3.13.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/filelock-3.13.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
- ❌ filelock-3.13.1-py3-none-any.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
filelock is a platform-independent file lock for Python. Prior to version 3.20.3, a TOCTOU race condition vulnerability exists in the SoftFileLock implementation of the filelock package. An attacker with local filesystem access and permission to create symlinks can exploit a race condition between the permission validation and file creation to cause lock operations to fail or behave unexpectedly. The vulnerability occurs in the _acquire() method between raise_on_not_writable_file() (permission check) and os.open() (file creation). During this race window, an attacker can create a symlink at the lock file path, potentially causing the lock to operate on an unintended target file or leading to denial of service. This issue has been patched in version 3.20.3.
Publish Date: 2026-01-10
URL: CVE-2026-22701
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.12%
CVSS 3 Score Details (5.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: High
- Privileges Required: Low
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: Low
- Availability Impact: High
For more information on CVSS3 Scores, click here.
Suggested Fix
Type: Upgrade version
Release Date: 2026-01-10
Fix Resolution (filelock): 3.20.3
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
CVE-2025-55552
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
- sentence_transformers-2.5.1-py3-none-any.whl (Root Library)
- ❌ torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl (Vulnerable Library)
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.
Publish Date: 2025-09-25
URL: CVE-2025-55552
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.418%
CVSS 3 Score Details (5.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: Low
For more information on CVSS3 Scores, click here.
In order to enable automatic remediation for this issue, please create workflow rules
Multilingual text embeddings
Library home page: https://files.pythonhosted.org/packages/68/0d/27475988a3daade7516ea02dbc607b57d4a30f01bb49614a6430e76685c2/sentence_transformers-2.5.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/sentence_transformers-2.5.1.dist-info
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Vulnerabilities
*For some transitive vulnerabilities, there is no version of direct dependency with a fix. Check the "Details" section below to see if there is a version of transitive dependency where vulnerability is fixed.
**In some cases, Remediation PR cannot be created automatically for a vulnerability despite the availability of remediation
Details
Vulnerable Library - sentence_transformers-2.5.1-py3-none-any.whl
Multilingual text embeddings
Library home page: https://files.pythonhosted.org/packages/68/0d/27475988a3daade7516ea02dbc607b57d4a30f01bb49614a6430e76685c2/sentence_transformers-2.5.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/sentence_transformers-2.5.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
This vulnerability is potentially reachable
Vulnerability Details
sentence-transformers contains a security control bypass vulnerability that allows attackers to achieve arbitrary code execution by exploiting a logic flaw in the import_module_class helper within sentence_transformers/util/misc.py, where the guard condition includes an 'or os.path.exists(model_name_or_path)' clause that satisfies the trust gate whenever the supplied path exists on the local filesystem, regardless of the trust_remote_code=False argument. Attackers who can control or influence the contents of a model directory on disk can place malicious Python files such as modeling_*.py referenced via modules.json, causing the code to execute at import time when an application loads the model with SentenceTransformer(path, trust_remote_code=False), bypassing the documented security contract and achieving code execution within the loading process.
Publish Date: 2026-07-31
URL: CVE-2026-68770
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.521%
CVSS 3 Score Details (9.8)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2026-07-31
Fix Resolution: 5.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.
Publish Date: 2025-04-18
URL: CVE-2025-32434
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 1.94%
CVSS 3 Score Details (9.8)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Origin: GHSA-53q9-r3pm-6pq6
Release Date: 2025-04-18
Fix Resolution: pytorch - 2.6.0,https://github.com/pytorch/pytorch.git - v2.6.0,pytorch - 2.6.0
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's "weights_only" unpickler allows an attacker to craft a malicious checkpoint file (".pth") that, when loaded with "torch.load(..., weights_only=True)", can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.
Publish Date: 2026-01-27
URL: CVE-2026-24747
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.706%
CVSS 3 Score Details (8.8)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2026-01-27
Fix Resolution (torch): 2.10.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
An issue in pytorch v2.7.0 can lead to a Denial of Service (DoS) when a PyTorch model consists of torch.Tensor.to_sparse() and torch.Tensor.to_dense() and is compiled by Inductor.
Publish Date: 2025-09-25
URL: CVE-2025-55560
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.411%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tensor.view-torch.mv() and is compiled by Inductor, leading to a Denial of Service (DoS).
Publish Date: 2025-09-25
URL: CVE-2025-55558
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.454%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A Name Error occurs in pytorch v2.7.0 when a PyTorch model consists of torch.cummin and is compiled by Inductor, leading to a Denial of Service (DoS).
Publish Date: 2025-09-25
URL: CVE-2025-55557
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.408%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).
Publish Date: 2025-09-25
URL: CVE-2025-55553
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.408%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.8.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
An issue in the component torch.linalg.lu of pytorch v2.8.0 allows attackers to cause a Denial of Service (DoS) when performing a slice operation.
Publish Date: 2025-09-25
URL: CVE-2025-55551
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.423%
CVSS 3 Score Details (7.5)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2025-09-25
Fix Resolution (torch): 2.9.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - Jinja2-3.1.3-py3-none-any.whl
A very fast and expressive template engine.
Library home page: https://files.pythonhosted.org/packages/30/6d/6de6be2d02603ab56e72997708809e8a5b0fbfee080735109b40a3564843/Jinja2-3.1.3-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/Jinja2-3.1.3.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
Jinja is an extensible templating engine. Prior to 3.1.5, An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox. This vulnerability is fixed in 3.1.5.
Publish Date: 2024-12-23
URL: CVE-2024-56326
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.521%
CVSS 3 Score Details (7.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: Low
- Privileges Required: Low
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Origin: GHSA-q2x7-8rv6-6q7h
Release Date: 2024-12-23
Fix Resolution (Jinja2): 3.1.5
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - Jinja2-3.1.3-py3-none-any.whl
A very fast and expressive template engine.
Library home page: https://files.pythonhosted.org/packages/30/6d/6de6be2d02603ab56e72997708809e8a5b0fbfee080735109b40a3564843/Jinja2-3.1.3-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/Jinja2-3.1.3.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
Jinja is an extensible templating engine. In versions on the 3.x branch prior to 3.1.5, a bug in the Jinja compiler allows an attacker that controls both the content and filename of a template to execute arbitrary Python code, regardless of if Jinja's sandbox is used. To exploit the vulnerability, an attacker needs to control both the filename and the contents of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates where the template author can also choose the template filename. This vulnerability is fixed in 3.1.5.
Publish Date: 2024-12-23
URL: CVE-2024-56201
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.307%
CVSS 3 Score Details (7.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: Low
- Privileges Required: Low
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Origin: GHSA-gmj6-6f8f-6699
Release Date: 2024-12-23
Fix Resolution (Jinja2): 3.1.5
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - filelock-3.13.1-py3-none-any.whl
A platform independent file lock.
Library home page: https://files.pythonhosted.org/packages/81/54/84d42a0bee35edba99dee7b59a8d4970eccdd44b99fe728ed912106fc781/filelock-3.13.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/filelock-3.13.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
filelock is a platform-independent file lock for Python. In versions prior to 3.20.1, a Time-of-Check-Time-of-Use (TOCTOU) race condition allows local attackers to corrupt or truncate arbitrary user files through symlink attacks. The vulnerability exists in both Unix and Windows lock file creation where filelock checks if a file exists before opening it with O_TRUNC. An attacker can create a symlink pointing to a victim file in the time gap between the check and open, causing os.open() to follow the symlink and truncate the target file. All users of filelock on Unix, Linux, macOS, and Windows systems are impacted. The vulnerability cascades to dependent libraries. The attack requires local filesystem access and ability to create symlinks (standard user permissions on Unix; Developer Mode on Windows 10+). Exploitation succeeds within 1-3 attempts when lock file paths are predictable. The issue is fixed in version 3.20.1. If immediate upgrade is not possible, use SoftFileLock instead of UnixFileLock/WindowsFileLock (note: different locking semantics, may not be suitable for all use cases); ensure lock file directories have restrictive permissions (chmod 0700) to prevent untrusted users from creating symlinks; and/or monitor lock file directories for suspicious symlinks before running trusted applications. These workarounds provide only partial mitigation. The race condition remains exploitable. Upgrading to version 3.20.1 is strongly recommended.
Publish Date: 2025-12-16
URL: CVE-2025-68146
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.201%
CVSS 3 Score Details (6.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: High
- Privileges Required: Low
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: High
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2025-12-16
Fix Resolution (filelock): 3.20.1
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - requests-2.31.0-py3-none-any.whl
Python HTTP for Humans.
Library home page: https://files.pythonhosted.org/packages/70/8e/0e2d847013cb52cd35b38c009bb167a1a26b2ce6cd6965bf26b47bc0bf44/requests-2.31.0-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/requests-2.31.0.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
Requests is a HTTP library. Prior to 2.32.0, when making requests through a Requests "Session", if the first request is made with "verify=False" to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of "verify". This behavior will continue for the lifecycle of the connection in the connection pool. This vulnerability is fixed in 2.32.0.
Mend Note: The description of this vulnerability differs from MITRE.
Publish Date: 2024-05-20
URL: CVE-2024-35195
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.34%
CVSS 3 Score Details (5.6)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: High
- Privileges Required: High
- User Interaction: Required
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: High
- Integrity Impact: High
- Availability Impact: None
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Origin: GHSA-9wx4-h78v-vm56
Release Date: 2024-05-20
Fix Resolution (requests): 2.32.0
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
A vulnerability was identified in PyTorch 2.10.0. The affected element is an unknown function of the component pt2 Loading Handler. The manipulation leads to deserialization. The attack can only be performed from a local environment. The exploit is publicly available and might be used. The project was informed of the problem early through a pull request but has not reacted yet.
Publish Date: 2026-03-22
URL: CVE-2026-4538
Threat Assessment
Exploit Maturity: Proof of concept
EPSS: 0.239%
CVSS 3 Score Details (5.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: Low
- Privileges Required: Low
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: Low
- Integrity Impact: Low
- Availability Impact: Low
For more information on CVSS3 Scores, click here.Vulnerable Library - filelock-3.13.1-py3-none-any.whl
A platform independent file lock.
Library home page: https://files.pythonhosted.org/packages/81/54/84d42a0bee35edba99dee7b59a8d4970eccdd44b99fe728ed912106fc781/filelock-3.13.1-py3-none-any.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/filelock-3.13.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
filelock is a platform-independent file lock for Python. Prior to version 3.20.3, a TOCTOU race condition vulnerability exists in the SoftFileLock implementation of the filelock package. An attacker with local filesystem access and permission to create symlinks can exploit a race condition between the permission validation and file creation to cause lock operations to fail or behave unexpectedly. The vulnerability occurs in the _acquire() method between raise_on_not_writable_file() (permission check) and os.open() (file creation). During this race window, an attacker can create a symlink at the lock file path, potentially causing the lock to operate on an unintended target file or leading to denial of service. This issue has been patched in version 3.20.3.
Publish Date: 2026-01-10
URL: CVE-2026-22701
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.12%
CVSS 3 Score Details (5.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Local
- Attack Complexity: High
- Privileges Required: Low
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: Low
- Availability Impact: High
For more information on CVSS3 Scores, click here.Suggested Fix
Type: Upgrade version
Release Date: 2026-01-10
Fix Resolution (filelock): 3.20.3
Direct dependency fix Resolution (sentence-transformers): 2.6.0
In order to enable automatic remediation, please create workflow rules
Vulnerable Library - torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Library home page: https://files.pythonhosted.org/packages/a7/ad/fbe7d4cffb76da4e478438853b51305361c719cff929ab70a808e7fb75e7/torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl
Sample Path to Dependency File: /Pipfile
Path to vulnerable library: /tmp/containerbase/cache/.local/share/virtualenvs/AutoPrompt-jrKn-qKh-python/lib/python3.10/site-packages/torch-2.2.1.dist-info
Dependency Hierarchy:
Found in HEAD commit: 09f51f74740b88648be208302ec569217b51a66f
Found in base branch: main
Reachability Analysis
The vulnerable code is unreachable
Vulnerability Details
pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.
Publish Date: 2025-09-25
URL: CVE-2025-55552
Threat Assessment
Exploit Maturity: Not Defined
EPSS: 0.418%
CVSS 3 Score Details (5.3)
Base Score Metrics:
- Exploitability Metrics:
- Attack Vector: Network
- Attack Complexity: Low
- Privileges Required: None
- User Interaction: None
- Scope: Unchanged
- Impact Metrics:
- Confidentiality Impact: None
- Integrity Impact: None
- Availability Impact: Low
For more information on CVSS3 Scores, click here.In order to enable automatic remediation for this issue, please create workflow rules