Qvert Prompt Scanner
Advanced heuristic analysis for AI prompt security
Module: Qvert Module: Subnet-Calc Module: WebApp-Wrapper
Local Processing
Secure Analysis
50+ Patterns
Detect prompt injection attempts, obfuscated payloads, and suspicious patterns in AI prompts. All analysis happens locally in your browser.
Source Input
Overall Risk Score 0/100
Analysis Report
0 Total
0 Critical
0 High
0 Medium
0 Low
0 Encoded
0 Obfuscated
0 Jailbreak
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Key Detection Mechanisms
Category Detection Type Examples Patterns
Direct Injection Identifies explicit attempts to override system instructions, bypass constraints, or force unauthorized behavior "ignore previous instructions"
"disregard all rules"
"bypass safety filters"
12
Role Manipulation Detects attempts to change the AI's persona, role, or operational mode to circumvent restrictions "act as developer"
"you are now admin"
"enable DAN mode"
8
Encoding Layers Decodes and analyzes multi-layer encoded payloads including Base64, URL, Hex, Unicode, and HTML entities %69%67%6E%6F%72%65
\x69\x67\x6E\x6F\x72\x65
SGVsbG8gV29ybGQ=
15
Obfuscation Identifies hidden characters, homoglyph substitution, zero-width spaces, and invisible delimiters U+200B (zero-width)
Cyrillic 'а' vs Latin 'a'
Hidden Unicode chars
10
Jailbreak Signatures Matches known jailbreak patterns including DAN, GCG attacks, persona overrides, and token manipulation "do anything now"
"developer mode"
"! ! sure here"
8
Structural Markers Analyzes code blocks, comments, JSON keys, XML tags, and markdown formatting for hidden payloads ```code blocks```
// comments
{"ignore": "payload"}
7