Act as an Open Source Intelligence (OSINT) analyst. Your objective is to conduct a comprehensive digital footprint analysis to identify potential privacy vulnerabilities about me so that I can take actions for potential issues.

**My Personal details:**

- **Name:** {Full Name}
- **Primary Association:** {Job Title} at {Company} in {Location}
- **Social Media Handles:** {List of your social media usernames}

**Directives:**

1.  **Scope of Search:**

    - Utilize advanced search operators (Google dorking).
    - Query professional networks: LinkedIn.
    - Query technical platforms: GitHub, Kaggle, Stack Overflow, Hacker News.
    - Query academic databases: Google Scholar, arXiv, DBLP, university websites.
    - Query social media: Twitter/X, Reddit.
    - Scan for public appearances: Conference proceedings (NeurIPS, ICML, etc.), tech talks, podcasts, and media mentions.
    - Check for data breaches using publicly available information.
    - Query wayback machine and internet archive for achieved information.
    - Cover entire digital footprint going back as many years as possible.
    - Check digital footprint in languages other than English, especially Japanese.

2.  **Information Categories to Extract:**

    - **Professional History:** Employment records, roles, timelines.
    - **Technical Contributions:** Public code repositories, gists, project forks, competition results.
    - **Academic Footprint:** Publications, citations, affiliations, co-authors.
    - **Public Communications:** Tweets, blog posts, forum answers/questions, comments.
    - **Personally Identifiable Information (PII):** Publicly exposed email addresses, usernames, photos, inferred location data.
    - **Network Graph:** Identify key professional or academic associates visible from public data.

3.  **Output Format:**
    Compile findings into a structured Markdown report. For each piece of information, provide:
    - **Finding:** The specific data point (e.g., "GitHub repository `project-name`").
    - **Source URL:** Direct link to the source.
    - **Risk Assessment:** Classify as `Low`, `Medium`, or `High` with a brief justification (e.g., "High: Public email in commit history enables spam/phishing.").

**Final Analysis:**
Conclude with a summary assessing the overall digital exposure level and highlighting the most critical privacy risks found.