Parse and analyze email headers to trace the origin of phishing emails, verify sender authenticity, and identify spoofing through SPF, DKIM, and DMARC validation.
69
62%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Risky
Do not use without reviewing
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/analyzing-email-headers-for-phishing-investigation/SKILL.mdSecurity
2 findings — 1 high severity, 1 medium severity. You should review these findings carefully before considering using this skill.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Insecure credential handling detected (high risk: 1.00). The prompt includes examples that embed API keys/API tokens directly into commands (e.g., curl with "Key: YOUR_API_KEY" and "x-apikey: YOUR_VT_API_KEY"), which requires the LLM to insert secret values verbatim into generated requests/commands, an insecure pattern prone to secret exfiltration.
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.
Third-party content exposure detected (high risk: 0.90). The SKILL.md workflow and scripts explicitly query and ingest public reputation/DNS/URL data (e.g., dig/whois and curl to AbuseIPDB, VirusTotal, URLhaus/PhishTank in Step 3 and Step 5) and the agent/script (scripts/agent.py) reads and acts on those results to generate indicators and risk decisions, so untrusted third-party content can influence its behavior.
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