Security audit

Afm Force Curve Analyzer 1.0.0

Security checks for vulnerabilities and agentic risk

Overview

This is a purpose-aligned AFM data analysis skill that reads user-selected files and writes analysis reports, with a bounded report-output sanitization weakness users should understand.

Install only if you intend to analyze AFM force-curve data locally. Treat input filenames and custom labels as untrusted when sharing or opening generated CSV/Markdown reports, especially in spreadsheet software, because crafted labels could affect report rendering or spreadsheet formulas.

A.I.G

Vulnerability Patterns

Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally

Findings (1)

T09 · Insecure Skill Coding Practices

Warning

Location: analyze.py:478
Finding: Unescaped User-Controlled Labels Enable CSV Formula and Markdown Content Injection
Content: View full analysis
Remediation: View remediation

SkillSpector

Vulnerability Patterns

Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code

Findings (3)

Ae4

Medium

Category: analysis-evasion
Confidence: 80% confidence
Finding: Suspicious Unicode normalization or mixed-script content
Content: No source excerpt is available for this finding.

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 89% confidence
Finding: The trigger list includes broad scientific phrases such as 'force spectroscopy', 'nanoindentation', and 'adhesion force' that may appear in ordinary discussion, causing unintended invocation of the skill. Over-broad activation can route unrelated user content or files into this analyzer, increasing the chance of inappropriate tool use, data handling beyond user intent, or prompt/workflow hijacking through accidental activation.
Content: No source excerpt is available for this finding.

Ae4

Medium

Category: analysis-evasion
Confidence: 80% confidence
Finding: Suspicious Unicode normalization or mixed-script content
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.