Content safety scanning is the process of analyzing text that flows through an AI agent to detect threats before the agent processes or acts on them. It is a distinct layer from policy enforcement: policy rules match on tool names and argument structure, while content scanning analyzes the actual text content for malicious patterns.
In an AI agent pipeline, text flows in several directions:
Each of these is a potential attack surface. A prompt injection can be embedded in a user message, hidden in a retrieved document, or even planted in a tool response from a compromised server.
A content scanner looks for several categories of threats:
Prompt injection: Text that attempts to override the agent's instructions. Examples include "Ignore previous instructions", fake system messages, and delimiter attacks that break out of the user context.
PII exposure: Personal information (email addresses, phone numbers, social security numbers) that should not be passed to tools or returned to users.
Credential leaks: API keys, tokens, passwords, and other secrets that appear in text. An agent that logs or transmits credentials is a security risk.
Code injection: SQL injection, shell injection, or other code that could execute if passed to a tool that interprets it.
Encoding tricks: Base64-encoded instructions, Unicode homoglyphs, and other obfuscation techniques designed to bypass simpler pattern checks.
The scanner applies pattern matching and heuristic analysis to the input text. Each detector returns a confidence score between 0 and 1. If any score exceeds the configured threshold, the content is flagged as a threat.
Scanning runs synchronously in-process. There is no external API call or network latency. Aegis, Authensor's content scanner, has zero runtime dependencies and runs in microseconds for typical inputs.
A scanner detects threats and flags them. What happens next depends on your configuration. You can block the action entirely, log the threat and allow the action, or escalate to a human reviewer. The scanner provides information; the policy engine decides what to do with it.
Pattern-based scanning catches known attack patterns. Novel attacks using previously unseen techniques may bypass detection. Scanning is one layer in a defense stack that should also include policy enforcement, behavioral monitoring, and output filtering.
Explore more guides on AI agent safety, prompt injection, and building secure systems.
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