Verify incoming emails to prevent phishing-style exploits
If an agent processes email or inbox data, attackers can exploit this as an entry point. Guardrails analyze sender metadata and content patterns to detect phishing attempts.
What's at stake
- Email is a primary vector for attacking AI agents with inbox access
- Attackers can send crafted emails that manipulate agent behavior when processed
- Phishing-style attacks can trick agents into revealing information or taking actions
- Emails may contain attachments or links with additional attack payloads
- Enterprise agents with email access represent high-value targets for adversaries
How to solve this
When your AI agent processes emails—for summarization, response drafting, or action taking—it becomes vulnerable to email-based attacks. An attacker sends an email crafted to manipulate the agent: hidden instructions in the body, malicious payloads in attachments, or social engineering patterns that exploit agent behavior.
The solution combines multiple verification layers:
- Sender verification: checking domain reputation, SPF/DKIM/DMARC, and known threat intelligence
- Content analysis: scanning body text for prompt injection patterns and social engineering indicators
- Attachment inspection: analyzing files for hidden instructions or malicious content
- Link analysis: evaluating URLs for phishing or payload delivery
Only emails that pass all layers should be processed by your agent.
How Superagent prevents this
Superagent provides guardrails for AI agents—small language models purpose-trained to detect and prevent failures in real time. These models sit at the boundary of your agent and inspect inputs, outputs, and tool calls before they execute.
For email workflows, Superagent's Guard model inspects incoming emails before your agent processes them. Guard analyzes multiple signals: sender metadata for reputation and authenticity, body content for injection attempts and social engineering, and attachment content for hidden instructions.
The model is trained to recognize email-based attacks specifically targeting AI agents. These attacks differ from traditional phishing—they're designed to manipulate agent behavior rather than trick humans. Guard catches these patterns and blocks malicious emails before they enter your agent's context.
When threats are detected, Guard blocks the email and logs the attempt with full metadata for your security team. Safe emails pass through normally, with your agent processing them as intended.