Semgrep Multimodal Goes Beyond Authentication: What we learned from Comparing it with Mythos

A comparative evaluation of Semgrep Multimodal, Claude Security with Mythos, and Codex Security on 275 manually reviewed IDOR labels found that Semgrep Multimodal achieved higher recall at 59.9% and F1 at 57.1%, while Mythos had higher precision at 80.1% but much lower recall at 13.9%; Codex Security recorded 11.3% recall and 17.7% F1. Across four repositories at identical revisions, Semgrep Multimodal reported 63 manually confirmed IDOR vulnerabilities not found by Mythos, with 40 recurring across three runs. The findings involved authenticated users accessing or modifying objects without authorization for the specific target object, often because checks covered a parent resource, object existence, workflow state, or authentication status rather than the child object or record used in the final operation. Semgrep Multimodal combines rule-based dataflow analysis, which traces caller-controlled identifiers through endpoints, service layers, and database operations, with AI reasoning intended to determine whether authorization checks apply to the same object as the sensitive action. The comparison emphasizes that IDOR detection requires assessing relationships among request parameters, authorization decisions, and final reads, writes, deletions, or workflow transitions, and that higher precision alone may leave many vulnerabilities undiscovered.

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