diff --git a/.github/workflows/documentation_workflow.yml b/.github/workflows/documentation_workflow.yml
index 9ceef53..998e69d 100644
--- a/.github/workflows/documentation_workflow.yml
+++ b/.github/workflows/documentation_workflow.yml
@@ -13,6 +13,7 @@ jobs:
       - uses: actions/setup-python@v5
       - name: Install dependencies
         run: |
+          python -m pip install --upgrade "pip>=26.2.2"
           pip install sphinx sphinx_mdinclude furo sphinx-copybutton #sphinx-new-tab-link
       - name: Sphinx build
         run: |
diff --git a/doc/source/installation.md b/doc/source/installation.md
index e2f3ad8..bf0efa6 100644
--- a/doc/source/installation.md
+++ b/doc/source/installation.md
@@ -47,6 +47,10 @@ You can find the prepared environment files in the `envs` directory
 - `cuda124_env.yml` - This is appropriate for systems able to run CUDA 12.4 and PyTorch 2.4.0
     - This uses requirements_cuda124.txt to install dependencies via `pip`
 
+> Note: Use pip 26.2.2 or newer. Older pip releases still trust the withdrawn emSign root CA certificate.
+> The environment files do not pin `pip`, so if conda installs an older version, create the environment
+> and install the pip dependencies separately as described in step 1 below.
+
 If you have trouble with these files but they *should* work based on your system specifications here are a few things to try: 
 1. Separate the creation of the environment and the installation of dependencies via pip: 
     1. Remove the last two lines from the above `.yml` files
@@ -54,6 +58,7 @@ If you have trouble with these files but they *should* work based on your system
         ```
         conda env create -f cuda121_env.yml
         conda activate rfd2_env
+        python -m pip install --upgrade pip  # pip 26.2.2 or newer
         pip install -r requirements_cuda121.txt
         ```
     This will force the dependencies you want installed by CUDA to be installed before pip is used. 
@@ -89,6 +94,10 @@ For some useful troubleshooting tips, see the [Troubleshooting](#install_trouble
     > **REMEMBER:** You will need to change your CUDA version based on what is available on your system. This will need to be changed in the 
     > NVIDIA channel, the dglteam channel, the pytorch version, and the pytorch-cuda version. 
 
+1. Upgrade pip to version 26.2.2 or newer:
+    ```
+    python -m pip install --upgrade pip
+    ```
 1. Use pip to install several Python libraries: 
     ```
     pip install \
diff --git a/se3_flow_matching/fm.yml b/se3_flow_matching/fm.yml
index 9b8c4fa..d10cdb3 100644
--- a/se3_flow_matching/fm.yml
+++ b/se3_flow_matching/fm.yml
@@ -30,10 +30,10 @@ dependencies:
   - bzip2=1.0.8=h7f98852_4
   - c-ares=1.19.1=hd590300_0
   - c-blosc2=2.10.2=hb4ffafa_0
-  - ca-certificates=2023.7.22=hbcca054_0
+  - ca-certificates
   - cached-property=1.5.2=hd8ed1ab_1
   - cached_property=1.5.2=pyha770c72_1
-  - certifi=2023.7.22=pyhd8ed1ab_0
+  - certifi>=2026.10.19
   - cffi=1.15.1=py310h255011f_3
   - charset-normalizer=3.2.0=pyhd8ed1ab_0
   - comm=0.1.4=pyhd8ed1ab_0
@@ -188,7 +188,7 @@ dependencies:
   - pexpect=4.8.0=pyh1a96a4e_2
   - pickleshare=0.7.5=py_1003
   - pillow=10.0.0=py310h582fbeb_0
-  - pip=23.2.1=pyhd8ed1ab_0
+  - pip>=26.2.2
   - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_0
   - platformdirs=3.10.0=pyhd8ed1ab_0
   - pooch=1.7.0=pyha770c72_3