A financial services company hosts an online banking platform accessible via a public web portal.

This rule is signature-based because it matches a known malicious pattern (a specific string payload) within network traffic. Snort’s content keyword searches for an exact sequence of bytes/characters in the packet payload—in this case, a classic SQL injection tautology pattern intended to manipulate application logic. Signature detection is high-confidence when the signature is precise and the payload is strongly associated with malicious intent. In SOC operations, signature-based rules are commonly used for well-known exploit strings, malware beacons, and protocol abuse patterns. The tradeoff is that signatures can be bypassed with encoding, obfuscation, payload variations, or different injection strategies that avoid the exact string. Behavioral/anomaly/statistical methods, by contrast, focus on deviations from baseline or broader behavioral patterns (for example, unusual login rates, uncommon HTTP methods, or atypical data transfer volumes). Here, the detection trigger is explicitly the presence of a known SQL injection payload string, which is the defining characteristic of signature-based detection. The SIEM correlation with failed logins adds context and confidence, but the rule itself is still signature-driven.