analyzing-outlook-pst-for-email-forensics
Analyze Microsoft Outlook PST and OST files for email forensic evidence including message content, headers, attachments, deleted items, and metadata using libpff, pst-utils, and forensic email analysis tools for legal investigations and incident response.
55
62%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/analyzing-outlook-pst-for-email-forensics/SKILL.mdSecurity
1 medium severity finding. This skill can be installed but you should review these findings before use.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Third-party content exposure detected (high risk: 0.85). The required runtime workflow ingests **outsider-authored email content from the PST/OST file** (e.g., message subjects/senders/transport headers and attachment names) via `pypff` in `scripts/agent.py` (`walk_folders()` → `extract_messages()` reads `msg.subject`, `msg.sender_name`, `msg.transport_headers`, and attachment metadata), and those fields are then placed into the agent’s LLM context as part of the generated JSON report.
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Commit
0445030
- Audited
- Security analysis
Is this your skill?
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