In cybersecurity, especially within SOC and DFIR roles, analysts are constantly surrounded by noise: high alert volume, repetitive log parsing, IOC triage, case documentation — and yes, even repetitive job application tasks. The solution? Automation.

This post breaks down a Python script I wrote to automate the process of tailoring cover letters, resumes, and outreach messages for different roles. But beyond job hunting, it’s a blueprint for how automation principles apply directly to real-world cybersecurity operations.

🔍 Why Automate?

In security operations, analysts often automate:

• Parsing log files for patterns
• Replacing indicators across datasets
• Pivoting on artifacts in threat hunts
• Building reports from templated data

This script mirrors those same patterns. It:

• ✅ Replaces dynamic values in .docx templates
• ✅ Maintains text formatting (critical in styled documents)
• ✅ Structures outputs with naming consistency
• ✅ Generates role-specific communication templates

These are the same principles used in incident response scripts or detection engineering pipelines.

🧠 How the Script Works

🧩 1. Placeholder Mappings

cover_replacements = {
    '[[JOB_TITLE]]': job_title,
    '[[COMPANY_NAME]]': company_name,
    '[[CONTACT_TITLE]]': contact_title,
    '[[LAST_NAME]]': last_name
}

Structured mappings allow the script to search and replace pre-defined placeholders. This is similar to replacing variables in detection logic or IOC sweep templates.

📄 2. Handling Styled Documents

def replace_runs(runs):
    full_text = ''.join(run.text for run in runs)
    for old, new in cover_replacements.items():
        full_text = full_text.replace(old, new)
    if runs:
        runs[0].text = full_text
        for run in runs[1:]:
            run.text = ''

MS Word documents store styled text in “runs.” If you don’t handle them properly, your replacements break formatting. This function preserves the formatting by:

• ✔ Merging all runs into a single string
• ✔ Performing replacements
• ✔ Updating only the first run (and clearing the rest)

In security automation, similar logic applies when:

• Preserving formatting in logs and SIEM exports
• Cleaning artifacts without losing context
• Preserving metadata during forensic triage

📝 3. Paragraph-Level Replacements in Resumes

def replace_placeholder_text(paragraph):
    full_text = paragraph.text
    replaced = False
    for old, new in resume_replacements.items():
        if old in full_text:
            full_text = full_text.replace(old, new)
            replaced = True
    if replaced:
        for run in paragraph.runs:
            run.text = ''
        if paragraph.runs:
            paragraph.runs[0].text = full_text

Unlike cover letters, resumes often use full paragraphs for summaries. This method respects that structure — the way many detection rules or Sysmon logs are formatted.

💾 4. Safe File Naming for Output Management

safe_job = job_title.replace(" ", "_")
safe_company = company_name.replace(" ", "_")
base_name = f"{safe_job}({safe_company})"

Well-named files aren’t just a preference — they’re critical in SOC/DFIR workflows, especially when managing:

• Log exports
• Case documentation
• Evidence chains

💬 5. Outreach Message Templates

cold_contact_message = f"""
Hi {contact_title} {last_name},
I hope you're doing well. My name is Adam Gardner, and I’m reaching out to express interest in the {job_title} role at {company_name}.
...
"""

Though technically simple, this function reinforces the idea that even communication processes can (and should) be templated and automated — like analyst-to-IR team handoff emails or daily SOC digests.

🔐 Real-World Cybersecurity Applications

Automation doesn’t always need to involve a threat feed or a YARA scan. It’s a mindset — optimizing for consistency, accuracy, and efficiency in everything you do.

💡 Final Thoughts

This script may have been built for job applications, but it reflects how analysts should think about operational tasks inside the SOC. Every repetitive action — whether it’s parsing alerts or updating templates — is an opportunity to code it once and reuse it often.

This is how real-world cybersecurity work scales:
Not just through tools — but through automation-driven thinking.