Master comprehensive static analysis workflows for AI security using industry-standard tools like Bandit, Semgrep, and pip-audit. Learn to identify AI-specific vulnerabilities including insecure pickle deserialization, hardcoded secrets in training scripts, and dependency risks that traditional security tools miss. Through hands-on labs with real vulnerable ML codebases, you'll configure automated security scanning in CI/CD pipelines, create custom detection rules for TensorFlow/PyTorch patterns, and implement supply chain security with SBOM generation. Address the unique challenges of ML projects with 50+ dependencies while establishing production-ready security policies.
Secure AI Code & Libraries with Static Analysis
Enjoy unlimited growth with a year of Coursera Plus for $199 (regularly $399). Save now.
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
4 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Configure Bandit, Semgrep, PyLint to detect AI vulnerabilities: insecure model deserialization, hardcoded secrets, unsafe system calls in ML code.
Apply static analysis to fix AI vulnerabilities (pickle exploits, input validation, dependencies); create custom rules for AI security patterns.
Implement pip-audit, Safety, Snyk for dependency scanning; assess AI libraries for vulnerabilities, license compliance, and supply chain security.
Skills you'll gain
- Secure Coding
- AI Security
- PyTorch (Machine Learning Library)
- Analysis
- Vulnerability Assessments
- Continuous Integration
- Dependency Analysis
- Vulnerability Scanning
- Program Implementation
- DevSecOps
- AI Personalization
- MLOps (Machine Learning Operations)
- Application Security
- Supply Chain
- Open Source Technology
- Threat Modeling
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
December 2025
Taught in English
See how employees at top companies are mastering in-demand skills
There are 3 modules in this course
This module establishes the foundation for secure AI development by teaching learners why traditional security approaches fall short for machine learning systems and how static analysis tools provide proactive vulnerability detection. Students will master the essential skills of configuring and integrating industry-standard security tools like Bandit, Semgrep, and PyLint into their AI development workflows, while understanding the unique threat landscape that AI/ML systems face in production environments.
What's included
4 videos2 readings1 peer review
This module focuses on practical application of static analysis techniques to detect real security weaknesses commonly found in AI codebases. Students will learn to identify and remediate critical vulnerabilities including insecure model deserialization, hardcoded credentials in training scripts, and unsafe data pipeline operations, while developing custom detection rules tailored to AI-specific security patterns that generic tools often miss.
What's included
3 videos1 reading1 peer review
This module extends security analysis beyond first-party code to address the complex supply chain risks inherent in AI development's heavy reliance on external libraries. Students will master automated dependency scanning workflows using tools like pip-audit and Snyk to identify vulnerabilities in AI libraries, ensure license compliance across diverse open-source packages, and implement comprehensive supply chain security policies with Software Bill of Materials (SBOM) generation for production ML systems.
What's included
4 videos1 reading1 assignment2 peer reviews
Offered by
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions
Financial aid available,
Âą Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.