Security Bulletin: Multiple Vulnerabilities in IBM watsonx Code Assistant On Prem

Vulnerability Details

CVEID:   CVE-2024-55459
DESCRIPTION:   An issue in keras 3.7.0 allows attackers to write arbitrary files to the user's machine via downloading a crafted tar file through the get_file function.
CWE:   CWE-494: Download of Code Without Integrity Check
CVSS Source:   CISA ADP
CVSS Base score:   6.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N)

CVEID:   CVE-2025-54313
DESCRIPTION:   eslint-config-prettier 8.10.1, 9.1.1, 10.1.6, and 10.1.7 has embedded malicious code for a supply chain compromise. Installing an affected package executes an install.js file that launches the node-gyp.dll malware on Windows.
CWE:   CWE-506: Embedded Malicious Code
CVSS Source:   cve@mitre.org
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:H/A:N)

CVEID:   CVE-2025-46059
DESCRIPTION:   langchain-ai v0.3.51 was discovered to contain an indirect prompt injection vulnerability in the GmailToolkit component. This vulnerability allows attackers to execute arbitrary code and compromise the application via a crafted email message. NOTE: this is disputed by the Supplier because the code-execution issue was introduced by user-written code that does not adhere to the LangChain security practices.
CWE:   CWE-94: Improper Control of Generation of Code ('Code Injection')
CVSS Source:   CISA ADP
CVSS Base score:   9.8
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H)

CVEID:   CVE-2025-3777
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.
CWE:   CWE-20: Improper Input Validation
CVSS Source:   security@huntr.dev
CVSS Base score:   3.5
CVSS Vector:   (CVSS:3.0/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:N/A:N)

CVEID:   CVE-2025-5197
DESCRIPTION:   A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the `convert_tf_weight_name_to_pt_weight_name()` function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern `/[^/]*___([^/]*)/` that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting model conversion processes between TensorFlow and PyTorch formats.
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   security@huntr.dev
CVSS Base score:   5.3
CVSS Vector:   (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:   CVE-2025-1194
DESCRIPTION:   A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file `tokenization_gpt_neox_japanese.py` of the GPT-NeoX-Japanese model. The vulnerability occurs in the SubWordJapaneseTokenizer class, where regular expressions process specially crafted inputs. The issue stems from a regex exhibiting exponential complexity under certain conditions, leading to excessive backtracking. This can result in high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario. The affected version is v4.48.1 (latest).
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   NVD
CVSS Base score:   6.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H)

CVEID:   CVE-2025-3933
DESCRIPTION:   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 `` 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.
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   NVD
CVSS Base score:   5.3
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:   CVE-2025-3262
DESCRIPTION:   A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the huggingface/transformers repository, specifically in version 4.49.0. The vulnerability is due to inefficient regular expression complexity in the `SETTING_RE` variable within the `transformers/commands/chat.py` file. The regex contains repetition groups and non-optimized quantifiers, leading to exponential backtracking when processing 'almost matching' payloads. This can degrade application performance and potentially result in a denial-of-service (DoS) when handling specially crafted input strings. The issue is fixed in version 4.51.0.
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   NVD
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2025-2099
DESCRIPTION:   A vulnerability in the `preprocess_string()` function of the `transformers.testing_utils` module in huggingface/transformers version v4.48.3 allows for a Regular Expression Denial of Service (ReDoS) attack. The regular expression used to process code blocks in docstrings contains nested quantifiers, leading to exponential backtracking when processing input with a large number of newline characters. An attacker can exploit this by providing a specially crafted payload, causing high CPU usage and potential application downtime, effectively resulting in a Denial of Service (DoS) scenario.
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   NVD
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2024-12720
DESCRIPTION:   A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file tokenization_nougat_fast.py. The vulnerability occurs in the post_process_single() function, where a regular expression processes specially crafted input. The issue stems from the regex exhibiting exponential time complexity under certain conditions, leading to excessive backtracking. This can result in significantly high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) scenario. The affected version is v4.46.3 (latest).
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   NVD
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2025-3264
DESCRIPTION:   A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically in the `get_imports()` function within `dynamic_module_utils.py`. This vulnerability affects versions 4.49.0 and is fixed in version 4.51.0. The issue arises from a regular expression pattern `\s*try\s*:.*?except.*?:` used to filter out try/except blocks from Python code, which can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. This vulnerability can lead to remote code loading disruption, resource exhaustion in model serving, supply chain attack vectors, and development pipeline disruption.
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   security@huntr.dev
CVSS Base score:   5.3
CVSS Vector:   (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:   CVE-2025-3263
DESCRIPTION:   A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically in the `get_configuration_file()` function within the `transformers.configuration_utils` module. The affected version is 4.49.0, and the issue is resolved in version 4.51.0. The vulnerability arises from the use of a regular expression pattern `config\.(.*)\.json` that can be exploited to cause excessive CPU consumption through crafted input strings, leading to catastrophic backtracking. This can result in model serving disruption, resource exhaustion, and increased latency in applications using the library.
CWE:   CWE-1333: Inefficient Regular Expression Complexity
CVSS Source:   security@huntr.dev
CVSS Base score:   5.3
CVSS Vector:   (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:   CVE-2025-6985
DESCRIPTION:   The HTMLSectionSplitter class in langchain-text-splitters version 0.3.8 is vulnerable to XML External Entity (XXE) attacks due to unsafe XSLT parsing. This vulnerability arises because the class allows the use of arbitrary XSLT stylesheets, which are parsed using lxml.etree.parse() and lxml.etree.XSLT() without any hardening measures. In lxml versions up to 4.9.x, external entities are resolved by default, allowing attackers to read arbitrary local files or perform outbound HTTP(S) fetches. In lxml versions 5.0 and above, while entity expansion is disabled, the XSLT document() function can still read any URI unless XSLTAccessControl is applied. This vulnerability allows remote attackers to gain read-only access to any file the LangChain process can reach, including sensitive files such as SSH keys, environment files, source code, or cloud metadata. No authentication, special privileges, or user interaction are required, and the issue is exploitable in default deployments that enable custom XSLT.
CWE:   CWE-611: Improper Restriction of XML External Entity Reference
CVSS Source:   security@huntr.dev
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N)

CVEID:   CVE-2025-4287
DESCRIPTION:   A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function torch.cuda.nccl.reduce of the file torch/cuda/nccl.py. The manipulation leads to denial of service. It is possible to launch the attack on the local host. The exploit has been disclosed to the public and may be used. The patch is identified as 5827d2061dcb4acd05ac5f8e65d8693a481ba0f5. It is recommended to apply a patch to fix this issue.
CWE:   CWE-404: Improper Resource Shutdown or Release
CVSS Source:   cna@vuldb.com
CVSS Base score:   3.3
CVSS Vector:   (CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L)

CVEID:   CVE-2025-55557
DESCRIPTION:   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).
CWE:   CWE-248: Uncaught Exception
CVSS Source:   NVD
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2025-55560
DESCRIPTION:   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.
CWE:   CWE-400: Uncontrolled Resource Consumption
CVSS Source:   NVD
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2025-55553
DESCRIPTION:   A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).
CWE:   CWE-248: Uncaught Exception
CVSS Source:   NVD
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2025-55558
DESCRIPTION:   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).
CWE:   CWE-400: Uncontrolled Resource Consumption
CVSS Source:   CISA ADP
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2025-55552
DESCRIPTION:   pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.
CWE:   CWE-190: Integer Overflow or Wraparound
CVSS Source:   NVD
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2024-7592
DESCRIPTION:   There is a LOW severity vulnerability affecting CPython, specifically the 'http.cookies' standard library module. When parsing cookies that contained backslashes for quoted characters in the cookie value, the parser would use an algorithm with quadratic complexity, resulting in excess CPU resources being used while parsing the value.
CWE:   CWE-400: Uncontrolled Resource Consumption
CVSS Source:   CISA ADP
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:   CVE-2024-0397
DESCRIPTION:   A defect was discovered in the Python “ssl” module where there is a memory race condition with the ssl.SSLContext methods “cert_store_stats()” and “get_ca_certs()”. The race condition can be triggered if the methods are called at the same time as certificates are loaded into the SSLContext, such as during the TLS handshake with a certificate directory configured. This issue is fixed in CPython 3.10.14, 3.11.9, 3.12.3, and 3.13.0a5.
CWE:   CWE-362: Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')
CVSS Source:   IBM X-Force
CVSS Base score:   7.4
CVSS Vector:   (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:H)

CVEID:   CVE-2025-46153
DESCRIPTION:   PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
CWE:   CWE-1176: Inefficient CPU Computation
CVSS Source:   CISA ADP
CVSS Base score:   5.3
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N)

CVEID:   CVE-2025-46150
DESCRIPTION:   In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results.
CVSS Source:   CISA ADP
CVSS Base score:   5.3
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N)

CVEID:   CVE-2025-46149
DESCRIPTION:   In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error.
CWE:   CWE-617: Reachable Assertion
CVSS Source:   CISA ADP
CVSS Base score:   5.3
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N)

CVEID:   CVE-2025-59420
DESCRIPTION:   Authlib is a Python library which builds OAuth and OpenID Connect servers. Prior to version 1.6.4, Authlib’s JWS verification accepts tokens that declare unknown critical header parameters (crit), violating RFC 7515 “must‑understand” semantics. An attacker can craft a signed token with a critical header (for example, bork or cnf) that strict verifiers reject but Authlib accepts. In mixed‑language fleets, this enables split‑brain verification and can lead to policy bypass, replay, or privilege escalation. This issue has been patched in version 1.6.4.
CWE:   CWE-345: Insufficient Verification of Data Authenticity
CVSS Source:   security-advisories@github.com
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N)

CVEID:   CVE-2025-1550
DESCRIPTION:   The Keras Model.load_model function permits arbitrary code execution, even with safe_mode=True, through a manually constructed, malicious .keras archive. By altering the config.json file within the archive, an attacker can specify arbitrary Python modules and functions, along with their arguments, to be loaded and executed during model loading.
CWE:   CWE-94: Improper Control of Generation of Code ('Code Injection')
CVSS Source:   NVD
CVSS Base score:   9.8
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H)

CVEID:   CVE-2025-47273
DESCRIPTION:   setuptools is a package that allows users to download, build, install, upgrade, and uninstall Python packages. A path traversal vulnerability in `PackageIndex` is present in setuptools prior to version 78.1.1. An attacker would be allowed to write files to arbitrary locations on the filesystem with the permissions of the process running the Python code, which could escalate to remote code execution depending on the context. Version 78.1.1 fixes the issue.
CWE:   CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
CVSS Source:   NVD
CVSS Base score:   8.8
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H)

CVEID:   CVE-2025-61920
DESCRIPTION:   Authlib is a Python library which builds OAuth and OpenID Connect servers. Prior to version 1.6.5, Authlib’s JOSE implementation accepts unbounded JWS/JWT header and signature segments. A remote attacker can craft a token whose base64url‑encoded header or signature spans hundreds of megabytes. During verification, Authlib decodes and parses the full input before it is rejected, driving CPU and memory consumption to hostile levels and enabling denial of service. Version 1.6.5 patches the issue. Some temporary workarounds are available. Enforce input size limits before handing tokens to Authlib and/or use application-level throttling to reduce amplification risk.
CWE:   CWE-20: Improper Input Validation
CVSS Source:   security-advisories@github.com
CVSS Base score:   7.5
CVSS Vector:   (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)