Security audit

Casely

Security checks for vulnerabilities and agentic risk

Overview

Casely is a coherent QA document-to-test-case workflow, but its setup and Excel export have concrete safety issues users should review before installing.

Install only if you are comfortable with the skill creating project files, reading requirement/example documents, and modifying the repository Python environment during setup. Review or pin the dependencies before running /init, and treat exported XLSX files as untrusted unless formula injection is fixed by escaping values that begin with formula-triggering characters.

A.I.G

Vulnerability Patterns

Insecure DependenciesIntroduces malicious components through unsafe dependency sources
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

Findings (2)

T08 · Insecure Dependencies

Warning

Location: SKILL.md:64
Finding: Unpinned Third-Party Dependencies Installed During Project Initialization
Content: View full analysis
Remediation: View remediation

T09 · Insecure Skill Coding Practices

Error

Location: scripts/export_to_xlsx.py:89
Finding: Spreadsheet Formula Injection Through Untrusted Markdown Cell Values
Content: View full analysis
', '\n').replace('
', '\n') if value else '' cell = ws.cell(row=row_idx, column=col_idx, value=clean_value) ``` ### Technical Analysis The exporter reads Markdown table content and writes both headers and data values directly into XLSX cells. It only replaces HTML line-break markers and does not neutralize values that spreadsheet applications can interpret as formulas. In particular, `openpyxl` treats a string beginning with `=` as a formula when assigning it as a cell value. Spreadsheet applications may also treat values beginning with `+`, `-`, or `@` as formula-like content depending on the application and import behavior. An attacker who can influence a requirement document, generated test case, or Markdown file in `results/` can place a formula payload in a table cell. The payload is preserved in the exported workbook and may be evaluated when a user opens it. The exact effects depend on the spreadsheet application, platform, security configuration, and whether external links or legacy formula features ...[truncated 1853 chars]
Remediation: View remediation
str: if value and value[0] in ("=", "+", "-", "@"): return "'" + value return value ``` 4. Apply the sanitizer to both headers and data values: ```python safe_header = sanitize_excel_text(header) ws.cell(row=1, column=col_idx, value=safe_header) clean_value = value.replace("
", "\n").replace("
", "\n") if value else "" safe_value = sanitize_excel_text(clean_value) cell = ws.cell(row=row_idx, column=col_idx, value=safe_value) ``` 5. Explicitly store untrusted cells as strings where practical, and verify the resulting XLSX cell data types after saving and reopening the workbook. 6. Do not rely solely on blocking `=`; account for all formula-triggering prefixes and leading whitespace or control characters that spreadsheet applications may ignore. 7. Add regression tests using values such as: ```text =1+1 +SUM(1,1) -1+2 @SUM(1,1) =HYPERLINK("https://example.invalid","test") ``` 8. Document that exported workbooks contain untrusted project data and should be opened with external links, macros, and legacy formula execution disabled. ]]>

SkillSpector

Vulnerability Patterns

Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration

Findings (7)

Tp4

High

Category: MCP Tool Poisoning
Confidence: 97% confidence
Finding: The declared behavior presents the skill as a full QA workflow assistant, but the detected implementation appears to provide only document parsing/conversion and additional undeclared format handling. Description-to-behavior mismatch is dangerous because users and orchestrators may grant trust or invoke the skill under false assumptions, leading to unexpected file processing, broader document ingestion, or missed review of undeclared capabilities.
Content: No source excerpt is available for this finding.

Undeclared Tool Scope

Medium

Category: MCP Least Privilege
Confidence: 93% confidence
Finding: The skill instructs file reads and writes across a project workspace but does not declare any explicit tool scope or permissions boundaries. This creates an authorization ambiguity where an agent may perform filesystem actions without a clearly constrained contract, increasing the chance of overbroad access or unsafe execution.
Content: No source excerpt is available for this finding.

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 96% confidence
Finding: The activation description is broad enough to match many ordinary requests involving testing, requirements, PDFs, DOCX, XLSX, or exports. Overbroad triggering can cause the wrong skill to activate and begin suggesting or performing filesystem and document-processing actions in contexts where the user did not intend that level of access.
Content: No source excerpt is available for this finding.

Missing User Warnings

Medium

Category: Not specified by scanner
Confidence: 95% confidence
Finding: The /init workflow instructs creation of directories, dependency installation, and environment modification via uv without an explicit warning or consent checkpoint. This is risky because it can change the local filesystem and Python environment, potentially installing packages or initializing project files unexpectedly.
Content: No source excerpt is available for this finding.

Missing User Warnings

Medium

Category: Not specified by scanner
Confidence: 91% confidence
Finding: The parsing workflow directs processing of requirement and example documents without a privacy or data-handling warning. Requirement documents often contain sensitive business logic, credentials, customer data, or proprietary content, so ingesting them without notice increases the risk of unintended exposure or mishandling.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 90% confidence
Finding: The skill states that future test cases will be generated in the detected project language by default, without indicating an explicit user confirmation step. This can cause unintended language lock-in, especially when source examples are multilingual, attacker-supplied, or contain a misleading dominant language, leading to outputs that are inaccessible to the user or unsuitable for downstream QA workflows.
Content: No source excerpt is available for this finding.

Vague Triggers

Low

Category: Not specified by scanner
Confidence: 84% confidence
Finding: This JSON eval file is a manifest-type file, so vague trigger review applies. The phrase "Everything looks good. Export the generated test cases to a formatted Excel file for my TMS." mixes a generic conversational lead-in with the requested action, and it does not define any narrower activation constraints or exclusions, which could make invocation boundaries less specific.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.