Merge branch 'lauraschauer-evaluation-scripts'

.gitignore

@@ -62,6 +62,8 @@ prospector/test_report.json
 prospector/.idea/*
 prospector/*.html
 prospector/*.json
-prospector/evaluation
+prospector/evaluation/data/input/*
+prospector/evaluation/data/reports/*
+prospector/evaluation/config.yaml
 .DS_Store
 prospector/pipeline/reports/*

prospector/datamodel/advisory.py

@@ -108,7 +108,7 @@ def analyze(self):
 
         # for k, v in self.references.items():
         #     print(k, v)
-        logger.debug("References: " + str(self.references))
+        # logger.debug("References: " + str(self.references))
 
         # TODO: I should extract interesting stuff from the references immediately ad maintain them just for a fast lookup
         logger.debug(f"Relevant references: {len(self.references)}")
@@ -210,6 +210,7 @@ def get_commits_in_advisory_references(self) -> List[str]:
             }
             limit += 1
 
+        # Filter out references that are not commit hashes, eg. commit::master
         return [
             ref.split("::")[1]
             for ref in self.references

prospector/datamodel/nlp.py

@@ -50,10 +50,14 @@ def extract_words_from_text(text: str) -> List[str]:
     ]
 
 
-def find_similar_words(adv_words: Set[str], commit_msg: str, exclude: str) -> Set[str]:
+def find_similar_words(
+    adv_words: Set[str], commit_msg: str, exclude: str
+) -> Set[str]:
     """Extract nouns from commit message that appears in the advisory text"""
     commit_words = {
-        word for word in extract_words_from_text(commit_msg) if word not in exclude
+        word
+        for word in extract_words_from_text(commit_msg)
+        if word not in exclude
     }
     return commit_words.intersection(adv_words)
     # return [word for word in extract_words_from_text(commit_msg) if word in adv_words]
@@ -63,7 +67,9 @@ def extract_versions(text: str) -> List[str]:
     """
     Extract all versions mentioned in the text
     """
-    return list(set(re.findall(r"(\d+(?:\.\d+)+)", text)))  # Should be more accurate
+    return list(
+        set(re.findall(r"(\d+(?:\.\d+)+)", text))
+    )  # Should be more accurate
     # return re.findall(r"[0-9]+\.[0-9]+[0-9a-z.]*", text)
 
 
@@ -134,7 +140,8 @@ def extract_filename(text: str, relevant_extensions: List[str]) -> List[str]:
     # This regex covers cases with various camelcase filenames and underscore, dash names
     if bool(
         re.search(
-            r"(?:[a-z]|[A-Z])[a-zA-Z]+[A-Z]\w*|(?:[a-zA-Z]{2,}[_-])+[a-zA-Z]{2,}", text
+            r"(?:[a-z]|[A-Z])[a-zA-Z]+[A-Z]\w*|(?:[a-zA-Z]{2,}[_-])+[a-zA-Z]{2,}",
+            text,
         )
     ):
         return [text], None
@@ -195,7 +202,12 @@ def extract_cve_references(text: str) -> List[str]:
     Extract CVE identifiers
     """
     return list(
-        set([result.group(0) for result in re.finditer(r"CVE-\d{4}-\d{4,8}", text)])
+        set(
+            [
+                result.group(0)
+                for result in re.finditer(r"CVE-\d{4}-\d{4,8}", text)
+            ]
+        )
     )
 
 

prospector/docker-compose.yml

@@ -16,20 +16,16 @@ services:
       GIT_CACHE: /tmp/gitcache
       CVE_DATA_PATH: /app/cve_data
       REDIS_URL: redis://redis:6379/0
-      #POSTGRES_HOST: db
-      #POSTGRES_PORT: 5432
-      #POSTGRES_USER: postgres
-      #POSTGRES_PASSWORD: example
-      #POSTGRES_DBNAME: postgres
-      #NVD_API_KEY: ${NVD_API_KEY}
 
   worker:
     build:
       context: .
       dockerfile: docker/worker/Dockerfile
     volumes:
       - ./:/app
-      # - ./pipeline/reports:/app/pipeline/reports
+      - ./data_sources/reports:/app/data_sources/reports
+      - ./evaluation/data/reports/:/app/evaluation/data/reports
+      - ./../../../data/gitcache:/tmp/gitcache
     depends_on:
       - redis
     environment:

prospector/docker/Dockerfile

@@ -1,7 +1,15 @@
 FROM python:3.10-slim
 
-COPY . /app
+RUN mkdir -p /app
+COPY ./requirements.txt /app/
 WORKDIR /app
+# Create log files with permissions for host user
+RUN touch evaluation.log
+RUN touch prospector.log
+RUN chown ${UID}:${GID} evaluation.log
+RUN chown ${UID}:${GID} prospector.log
+
+# Install dependencies with pip
 RUN pip install --upgrade pip
 RUN apt update && apt install -y --no-install-recommends gcc g++ libffi-dev python3-dev libpq-dev git curl
 RUN pip install --no-cache-dir -r requirements.txt

prospector/docker/worker/etc_supervisor_confd_rqworker.conf.j2

@@ -8,7 +8,7 @@ command=/usr/local/bin/python3 /usr/local/bin/rq worker {{env['RQ_QUEUE']}} -u r
 process_name=%(program_name)s%(process_num)01d
 
 ; If you want to run more than one worker instance, increase this
-numprocs=2
+numprocs=10
 redirect_stderr=true
 
 ; This is the directory from which RQ is ran. Be sure to point this to the

prospector/evaluation/README.md

@@ -0,0 +1,60 @@
+# Evaluate Prospector
+
+This folder contains the scripts used for evaluating Prospector's reports and data needed for it (created and used in Summer 2024). The folder is structured as follows:
+
+1. **Data** folder: contains input data, Prospector reports and results of the analysis of the Prospector reports.
+2. **Scripts**: The scripts used for running Prospector on a batch of CVEs, and for analysing the created reports.
+
+Prospector is run in the following way in this evaluation:
+
+First, the five docker containers must be started with `make docker-setup` or manually with `docker` commands. Once they are running, `docker ps` should show the following:
+
+```bash
+CONTAINER ID   IMAGE                COMMAND                  CREATED          STATUS          PORTS                                       NAMES
+c73aed108475   prospector_backend   "python ./service/ma…"   47 minutes ago   Up 47 minutes   0.0.0.0:8000->8000/tcp, :::8000->8000/tcp   prospector_backend_1
+2e9da86b09a8   prospector_worker    "/usr/local/bin/star…"   47 minutes ago   Up 47 minutes                                               prospector_worker_1
+b219fd6219ed   adminer              "entrypoint.sh php -…"   47 minutes ago   Up 47 minutes   0.0.0.0:8080->8080/tcp, :::8080->8080/tcp   prospector_adminer_1
+9aacdc04f7c5   postgres             "docker-entrypoint.s…"   47 minutes ago   Up 47 minutes   0.0.0.0:5432->5432/tcp, :::5432->5432/tcp   db
+7c540450ab76   redis:alpine         "docker-entrypoint.s…"   47 minutes ago   Up 47 minutes   0.0.0.0:6379->6379/tcp, :::6379->6379/tcp   prospector_redis_1
+```
+
+[`dispatch_jobs.py`](#running-prospector-on-multiple-cves-dispatch_jobspy) creates jobs with the `prospector()` function in them and enqueues
+them in a Redis Queue, from which the `prospector_worker` container fetches jobs and executes them. To visualise what is going on, run
+`docker attach prospector_worker_1` to see the usual console output. In order to change something inside the container, run `docker exec -it prospector_worker_1 bash` to open an interactive bash shell.
+
+You can set the number of workers in `docker/worker/etc_supervisor_confd_rqworker.conf.j2`.
+
+## Configuration File
+
+The configuration file has two parts to it: a main part and a Prospector settings part, which is a copy of a part of the original Prospector `config.yaml` file.
+
+The main part at the top allows you to set the path to where the input data can be found, where Prospector reports should be saved to and where analysis results should be saved to.
+
+The Prospector part allows you to set the settings for Prospector (independent from the Prospector settings used when running Prospector with `./run_prospector`). **Watch out**: Since the `prospector_worker` container is created in the beginning with the current state of the `config.yaml`, simply saving any changes in `config.yaml` and dispatching new jobs will still run them with the old configuration. For new configuration parameters to take effect, either destroy the containers with `make docker-clean` and rebuild them with `make docker-setup` or open an interactive shell to the container and make your changes to the code in there.
+
+## Script Files explained
+
+### Running Prospector on multiple CVEs (`dispatch_jobs.py`)
+
+The code for running Prospector is in `dispatch_jobs.py`. It exctracts CVE IDs from the data given in the path constructed as: `input_data_path` + the `-i` CL parameter. It then dispatches a job for each CVE ID to the queue, from where these jobs get executed. The path to the input file is split into two components (`input_data_path` in `config.yaml` and the `-i` parameter) because you might have one folder in which you have several different input data files of the same format. This keeps you from typing the full path, but still allows you to switch between the files between different runs.
+
+The reports are generated in the worker container, and saved to `prospector_reports_path_container`. This folder is mounted into the container, so you can see any newly generated reports in the same folder on the host.
+
+Do not confuse this paramter with `prospector_reports_path_host`, which sets the path to a batch of reports on the host (used for analysis). Your workflow should be as follows:
+
+1. Dispatch reports
+2. When the report generation has finished, move the reports to any other folder (preferably outside of the `prospector/` folder to keep the build context for the container from getting too big).
+3. Analyse the reports by setting the `prospector_reports_path_host` to the folder where you moved the reports to.
+
+### Analysing the generated reports (`analyse.py`)
+
+Start an analysis with
+
+```bash
+python3 evaluation/main.py -i <your_input_data_csv_file> -a
+```
+
+This will start the `analyse_prospector_reports()` function in `analyse.py`, which re-creates the summary execution table from [AssureMOSS D6.3](https://assuremoss.eu/en/resources/Deliverables/D6.3):
+![D6.3 Summary Execution Table](images/summary_execution_table.png)
+
+It also creates a detailed JSON file (listing CVEs in each category) in `data/results/summary_execution/` to inspect which CVEs are in which category.