chore: patch libxml2 cve

data/ignore_ids_safety_scan.json

@@ -1435,7 +1435,16 @@
                 "71601": "Transformers version upgrade needs to be handled in a separate image",
                 "71670": "Pytorch version upgrade needs to be handled in a separate image",
                 "71671": "Pytorch version upgrade needs to be handled in a separate image",
-                "71672": "Pytorch version upgrade needs to be handled in a separate image"
+                "71672": "Pytorch version upgrade needs to be handled in a separate image",
+                "77740": "Affected versions of this package are vulnerable to a potential Denial of Service (DoS) attack due to unbounded recursion when parsing untrusted Protocol Buffers data. The pure-Python implementation fails to enforce recursion depth limits when processing recursive groups, recursive messages, or a series of SGROUP tags, leading to stack overflow conditions that can crash the application by exceeding Python's recursion limit.",
+                "78828": "Affected versions of the PyTorch package are vulnerable to Denial of Service (DoS) due to improper handling in the MKLDNN pooling implementation. The torch.mkldnn_max_pool2d function fails to properly validate input parameters, allowing crafted inputs to trigger resource exhaustion or crashes in the underlying MKLDNN library. An attacker with local access can exploit this vulnerability by passing specially crafted tensor dimensions or parameters to the max pooling function, causing the application to become unresponsive or crash.",
+                "78153": "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 4.51.3 and earlier, and is fixed in version 4.52.1. The issue arises from the regex pattern <s_(.*?)> 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.",
+                "77986": "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.",
+                "78688": "Affected versions of the Hugging Face Transformers package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an inefficient regex pattern in weight name conversion. The convert_tf_weight_name_to_pt_weight_name() function uses the regular expression pattern /[^/]___([^/])/, which is susceptible to catastrophic backtracking when processing specially crafted TensorFlow weight names. An attacker can exploit this vulnerability by providing malicious weight names during model conversion between TensorFlow and PyTorch formats, causing excessive CPU consumption and potentially rendering the service unresponsive.",
+                "77744": "urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.",
+                "79077": "Affected versions of the h2 package are vulnerable to HTTP Request Smuggling due to improper validation of illegal characters in HTTP headers. The package allows CRLF characters to be injected into header names and values without proper sanitisation, which can cause request boundary manipulation when HTTP/2 requests are downgraded to HTTP/1.1 by downstream servers.",
+                "79595": "Affected versions of the transformers package are vulnerable to Regular Expression Denial of Service (ReDoS) due to inefficient regular expressions in the EnglishNormalizer.normalize_numbers() method",
+                "79596": "Affected versions of the transformers package are vulnerable to Regular Expression Denial of Service (ReDoS) due to inefficient regular expressions in the MarianTokenizer.remove_language_code() method"
             }
         },
         "inference-neuron": {

huggingface/pytorch/inference/docker/2.6/py3/Dockerfile.cpu

@@ -139,7 +139,7 @@ RUN pip install --upgrade pip --trusted-host pypi.org --trusted-host files.pytho
 
 # Install Common python packages
 RUN pip install --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu -U \
-    opencv-python \
+    "opencv-python==4.11.0.86" \
     "pyopenssl>=24.0.0" \
     "cryptography>=42.0.5" \
     "ipython>=8.10.0,<9.0" \
@@ -231,7 +231,8 @@ ENV HF_HUB_USER_AGENT_ORIGIN="aws:sagemaker:cpu:inference:regular"
 
 # IPEx installation installs the numpy==1.25.1. That causes a pip check failure due to incompatibility with numba.
 # Re-installing numpy after IPEx installation to get the appropriate numpy version and fix pip checks.
-# RUN pip install --no-cache-dir \
+RUN pip install --no-cache-dir \
+  "opencv-python==4.11.0.86"
 #     "numpy<1.25" \
 #     "pyyaml>=5.4"
 
@@ -244,7 +245,7 @@ RUN HOME_DIR=/root \
  && ${HOME_DIR}/oss_compliance/generate_oss_compliance.sh ${HOME_DIR} ${PYTHON} \
  && rm -rf ${HOME_DIR}/oss_compliance*
 
-RUN curl -o /license.txt  https://aws-dlc-licenses.s3.amazonaws.com/pytorch-2.3/license.txt
+RUN curl -o /license.txt  https://aws-dlc-licenses.s3.amazonaws.com/pytorch-2.6/license.txt
 
 ## Cleanup ##
 RUN pip cache purge \
@@ -255,4 +256,4 @@ RUN pip cache purge \
 
 EXPOSE 8080 8081
 ENTRYPOINT ["python", "/usr/local/bin/dockerd-entrypoint.py"]
-CMD ["serve"]
+CMD ["serve"]

huggingface/pytorch/inference/docker/2.6/py3/cu124/Dockerfile.gpu

@@ -119,6 +119,8 @@ RUN apt-get update \
     tk-dev \
     libffi-dev \
     ffmpeg \
+    libxml2 \
+    linux-libc-dev \
  && apt-get autoremove -y \
  && rm -rf /var/lib/apt/lists/* \
  && apt-get clean
@@ -162,8 +164,6 @@ RUN /opt/conda/bin/conda install -y -c conda-forge \
     "mkl<2024.1.0" \
     mkl-include \
     parso \
-    scipy \
-    numpy \
     pandas \
     pyarrow \
     typing \
@@ -190,7 +190,8 @@ RUN pip install --upgrade pip --no-cache-dir --trusted-host pypi.org --trusted-h
 
 # Install Common python packages
 RUN pip install --no-cache-dir -U \
-    opencv-python \
+    "opencv-python==4.11.0.86" \
+    scipy \
     # "nvgpu" is a dependency of TS but is disabled in SM DLC build,
     # via ENV Variable "TS_DISABLE_SYSTEM_METRICS=true" in the SM section of this file.
     # due to incompatibility with SM hosts 
@@ -265,7 +266,8 @@ RUN pip install --no-cache-dir \
     diffusers==${DIFFUSERS_VERSION} \
     peft==${PEFT_VERSION} \
     accelerate==${ACCELERATE_VERSION} \
-	sagemaker-huggingface-inference-toolkit==${SAGEMAKER_HF_INFERENCE_VERSION}
+    sagemaker-huggingface-inference-toolkit==${SAGEMAKER_HF_INFERENCE_VERSION} \
+    "opencv-python==4.11.0.86"
 
 # hf_transfer will be a built-in feature, remove the env variavle then
 ENV HF_HUB_ENABLE_HF_TRANSFER="1"
@@ -280,7 +282,7 @@ RUN HOME_DIR=/root \
  && ${HOME_DIR}/oss_compliance/generate_oss_compliance.sh ${HOME_DIR} ${PYTHON} \
  && rm -rf ${HOME_DIR}/oss_compliance*
 
-RUN curl -o /license.txt  https://aws-dlc-licenses.s3.amazonaws.com/pytorch-2.3/license.txt
+RUN curl -o /license.txt  https://aws-dlc-licenses.s3.amazonaws.com/pytorch-2.6/license.txt
 
 ## Cleanup ##
 RUN pip cache purge \
@@ -289,4 +291,4 @@ RUN pip cache purge \
 
 EXPOSE 8080 8081
 ENTRYPOINT ["python", "/usr/local/bin/dockerd-entrypoint.py"]
-CMD ["serve"]
+CMD ["serve"]