CAP-PC ENS study plan
CAP-PC ENS · Give each week a clear focus.
8 weeks · About 6 hours per week
Web Application Security & Source-Code Analysis
Map the OWASP Top 10 (2021) categories to concrete HTTP request/response evidence a tester would capture during an assessment
Set up a local lab with a deliberately vulnerable web app and a proxy interceptor, then capture and annotate at least 15 distinct request/response pairs
Trace one reflected XSS payload from browser input through server-side templating to rendered output, documenting each transformation point
Identify the differences between stored, reflected, and DOM-based XSS by constructing one working example of each in the lab
Your checkpoint
A 2-page vulnerability evidence log with 15 annotated HTTP pairs, each labeled by OWASP category and injection context.
Web Application Security
Demonstrate and explain SQL injection, blind SQL injection, and parameterized-query remediation in the lab
Exploit and then fix an access-control flaw (IDOR or missing function-level authorization) in a sample application
Configure and bypass a Content Security Policy in the lab to show how CSP mitigates and fails to mitigate XSS
Compare server-side request forgery, insecure deserialization, and file-upload flaws by writing a short risk note for each
Your checkpoint
A remediation report covering four web flaw classes, each with a proof-of-concept request, impact statement, and code-level fix.
Source-Code Analysis
Perform manual source review of a deliberately vulnerable application, recording each sink and its untrusted source
Run static analysis tooling on the same codebase and reconcile tool findings against your manual list
Classify at least 20 findings by CWE and assign a severity using a documented rubric
Write a secure-code fix for the three highest-severity findings and verify the fix removes the sink-to-source path
Your checkpoint
A source-code review report with 20 CWE-classified findings, tool-vs-manual reconciliation notes, and three verified fixes.
Source-Code Analysis & Cloud Security Assessment
Review infrastructure-as-code and CI/CD configuration files for hardcoded secrets, overly broad IAM permissions, and unencrypted storage
Explain how taint analysis, data-flow analysis, and control-flow analysis differ, and identify which class of bug each catches best
Compare SAST, DAST, SCA, and secret scanning by detection coverage, false-positive profile, and where each fits in a pipeline
Map a sample cloud deployment's trust boundaries and data flows in a threat model
Your checkpoint
A threat model plus pipeline security review of one sample repository, listing every secret, permission, and encryption gap found.
Cloud Security Assessment
Assess an intentionally misconfigured cloud storage bucket and document the enumeration, access, and remediation steps
Evaluate identity and access management in a cloud lab: identify privilege-escalation paths and over-permissive roles
Audit cloud logging and monitoring coverage, then list which events are missing for detection of the lab's simulated attack
Compare shared-responsibility boundaries across IaaS, PaaS, and SaaS for the same workload
Your checkpoint
A cloud assessment worksheet covering storage, IAM, logging, and shared responsibility, with severity ratings and remediation actions.
Cloud Security Assessment & Red Team and AI/ML Security
Execute a scoped red-team engagement against the lab environment, from reconnaissance through privilege escalation
Document each attack step with the exact command or request, the evidence captured, and the detection opportunity it created
Assess container and orchestration security in the lab: image provenance, runtime privileges, and network policy gaps
Write detection rules for the three highest-impact attack steps and test that each rule fires on the recorded activity
Your checkpoint
A red-team engagement report with an attack narrative, evidence appendix, and three tested detection rules.
Red Team and AI/ML Security
Explain the OWASP Top 10 for LLM Applications and map each risk to a concrete test procedure
Demonstrate prompt injection (direct and indirect) against a lab LLM application and document the trust boundary crossed
Assess an ML pipeline for training-data poisoning, model theft, and insecure model supply-chain risks
Evaluate an AI system's input/output handling for data leakage, excessive agency, and unsafe output consumption
Your checkpoint
An AI/ML security assessment of one lab LLM application, with a prompt-injection proof of concept and a risk-ranked findings table.
Web Application Security & Source-Code Analysis & Cloud Security Assessment & Red Team and AI/ML Security
Re-test every deliverable from weeks 1 through 7 and close gaps in evidence or remediation
Complete two timed mixed-domain practice sets and review every missed item by domain
Build a one-page decision aid that routes an observed symptom to the correct domain and next test
Write a personal weak-area list with the specific concept and the remediation action for each entry
Your checkpoint
A consolidated capstone portfolio with all prior deliverables, a weak-area remediation list, and practice-set score tracking.
Milestones
Week 2: Can explain and demonstrate the four main web flaw classes (injection, XSS, access control, SSRF/deserialization) and state the code-level fix for each without notes.
Week 4: Can review an unfamiliar codebase and produce a CWE-classified finding list that reconciles with a static analysis tool's output within a documented margin.
Week 6: Can complete a scoped cloud red-team exercise end to end and show at least three detection rules that fire on the recorded activity.
Week 8: Scores at or above the target threshold on both timed mixed-domain practice sets and has a written remediation plan for every missed item.