| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| WWW::Mechanize::Cached versions before 2.00 for Perl deserialize cached HTTP responses from a world-writable on-disk cache, enabling local response forgery and code execution.
With no explicit cache backend, WWW::Mechanize::Cached constructs a default Cache::FileCache under /tmp/FileCache without overriding the backend's documented directory_umask of 000, so the cache root and its subdirectories are created mode 0777 with no sticky bit. Cache entries are named by sha1_hex of the request and read back through Storable::thaw on the next cache hit.
A local attacker with write access to the cache tree can replace a victim's cache entry for a known URL with an arbitrary frozen HTTP::Response blob, causing the victim's next get() of that URL to return attacker controlled response bytes. Because the bytes are passed to Storable::thaw, a victim process that has loaded any class with a side-effectful STORABLE_thaw, DESTROY, or overload hook can be escalated to arbitrary code execution. |
| A vulnerability was identified in Oinone Pamirs up to 7.2.0. This affects the function JsonUtils.parseMap of the file PamirsParserConfig.java of the component appConfigQuery Interface. Such manipulation leads to deserialization. The attack can be launched remotely. The exploit is publicly available and might be used. The vendor was contacted early about this disclosure but did not respond in any way. |
| SEPPmail Secure Email Gateway before version 15.0.4 insecurely deserializes untrusted data, which can be reached from the new GINA UI and may allow unauthenticated remote attackers to execute code via a crafted serialized object. |
| Crypt::DSA versions through 1.19 for Perl use 2-args open, allowing existing files to be modified. |
| Symlink following in PostgreSQL pg_basebackup plain format and in pg_rewind allows an origin superuser to overwrite local files, e.g. /var/lib/postgres/.bashrc, that hijack the operating system account. It will remain the case that starting the server after these commands implicitly trusts the origin superuser, due to features like shared_preload_libraries. Hence, the attack has practical implications only if one takes relevant action between these commands and server start, like moving the files to a different VM or snapshotting the VM. Versions before PostgreSQL 18.4, 17.10, 16.14, 15.18, and 14.23 are affected. |
| Hono is a Web application framework that provides support for any JavaScript runtime. Prior to 4.12.18, Cache Middleware does not skip caching for responses that declare per-user variance via Vary: Authorization or Vary: Cookie. As a result, a response cached for one authenticated user may be served to subsequent requests from different users. This vulnerability is fixed in 4.12.18. |
| When schema validation is enabled on a collection and an update or insert would violate the collection's schema, the local server log message generated may not have all user data redacted.
This issue impacts MongoDB Server v7.0 versions prior to 7.0.34, v8.0 versions prior to 8.0.23, v8.2 versions prior to 8.2.9 and v8.3 versions prior to 8.3.2. |
| A vulnerability was detected in npitre cramfs-tools up to 2.2. Affected is the function change_file_status of the file cramfsck.c. Performing a manipulation results in symlink following. The attack requires a local approach. The exploit is now public and may be used. The patch is named b4a3a695c9873f824907bd15659f2a6ac7667b4f. It is recommended to apply a patch to fix this issue. |
| The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the Trainer.load() method of the Trainer class. The method loads model checkpoint files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method. |
| The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability (CWE-502) in the BaseLabeler.load() method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load() function on user-supplied file paths without any validation or security controls. Python's pickle module is inherently dangerous for deserializing untrusted data, as it can execute arbitrary code during the deserialization process. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method. |
| The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the MultitaskClassifier.load() method of the MultitaskClassifier class. The method loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method. |
| The torch-checkpoint-shrink.py script in the ml-engineering project in commit 0099885db36a8f06556efe1faf552518852cb1e0 (2025-20-27) contains an insecure deserialization vulnerability (CWE-502). The script uses torch.load() to process PyTorch checkpoint files (.pt) without enabling the security-restrictive weights_only=True parameter. This oversight allows the deserialization of arbitrary Python objects via the pickle module. A remote attacker can exploit this by providing a maliciously crafted checkpoint file, leading to arbitrary code execution in the context of the user running the script. |
| The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) is vulnerable to insecure deserialization (CWE-502). When loading a model state dictionary from a state_dict.pt file via torch.load(), the function does not enable the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects through the Pickle module. A remote attacker can exploit this by providing a maliciously crafted state_dict.pt file within a directory specified via the --model argument, leading to arbitrary code execution during the deserialization process on the victim's system. |
| The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) is vulnerable to insecure deserialization (CWE-502). When a user provides a single model file path (e.g., .pt or .pth) via the --model command-line argument, the function loads the file using torch.load() without enabling the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects through the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution during deserialization on the victim's system. |
| Valtimo is an open-source business process automation platform. From 12.4.0 to 12.33.0 and 13.26.0, the LoggingRestClientCustomizer in the web module automatically intercepts all outgoing HTTP calls made via Spring's RestClient and logs the full request body, response body, and response headers. When an error response is received, this information is included in the thrown HttpClientErrorException message, which is logged at ERROR level by Spring's default exception handling — regardless of the application's DEBUG log level setting. This vulnerability is fixed in 12.33.0 and 13.26.0. |
| python-utcp is the python implementation of UTCP. Prior to 1.1.3, _prepare_environment() in cli_communication_protocol.py passes a full copy of os.environ to every CLI subprocess. When combined with CVE-2026-45369, an attacker can exfiltrate all process-level secrets in a single tool call. This vulnerability is fixed in 1.1.3. |
| Microsoft APM is an open-source, community-driven dependency manager for AI agents. From 0.5.4 to 0.12.4, two primitive integrators in apm-cli enumerate package files with bare Path.glob() / Path.rglob() calls and read each match with Path.read_text(), transparently following symbolic links. A symlink committed inside a remote APM dependency under .apm/prompts/<x>.prompt.md or .apm/agents/<x>.agent.md is preserved verbatim into apm_modules/ on clone and then dereferenced during integration, with the resolved content written as a regular file into the project's deploy directories. The package content_hash, the pre-deploy SecurityGate scan, and apm audit do not flag this. The deploy roots are not added to the auto-generated .gitignore, so the resulting files are staged by git add by default. This vulnerability is fixed in 0.13.0. |
| GitLab has remediated an issue in GitLab EE affecting all versions from 11.9 before 18.9.7, 18.10 before 18.10.6, and 18.11 before 18.11.3 that could have allowed an unauthenticated user to cause denial of service by uploading a specially crafted file due to improper validation. |
| DataHub is an open-source metadata platform. Prior to 1.5.0.3, The DataHub frontend (datahub-frontend-react) deserializes attacker-controlled Java objects from the REDIRECT_URL HTTP cookie during the OIDC callback flow, with no integrity protection (no HMAC, no encryption). This is a Deserialization of Untrusted Data vulnerability (CWE-502) affecting the GET /callback/oidc endpoint. Successful exploitation requires a valid user account in the configured OIDC identity provider This vulnerability is fixed in 1.5.0.3. |
| Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. From version 4.0.0 to before version 4.0.5, the workflow executor logs all artifact repository credentials (S3 access keys, secret keys, GCS service account keys, Azure account keys, Git passwords, etc.) in plaintext on artifact operation. Any user with read access to workflow pod logs can extract these credentials. This issue has been patched in version 4.0.5. |
